diff --git a/docs/api/_category_.json b/docs/api/_category_.json new file mode 100644 index 00000000..f376ffa3 --- /dev/null +++ b/docs/api/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "API & Reference", + "position": 8, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "api/api-overview" + } +} diff --git a/docs/api/api-overview.md b/docs/api/api-overview.md new file mode 100644 index 00000000..684bae2e --- /dev/null +++ b/docs/api/api-overview.md @@ -0,0 +1,175 @@ +--- +title: API Overview +slug: /api/overview +track: dev +content_type: reference +seo_title: API Overview -- Pixee Docs +description: "Pixee REST API reference: authentication, endpoints, rate limits, and SARIF input format." +sidebar_position: 1 +--- + +# API Overview + +Pixee provides a REST API for programmatic access to vulnerability triage and remediation workflows. The API enables querying fix status, managing repository configurations, consuming webhook events for CI/CD integration, and ingesting SARIF scanner output. Authentication uses organization-scoped API tokens. This page covers available endpoints, authentication, rate limits, and links to detailed specifications. + +## API architecture + +The Pixee API follows standard REST conventions: + +- **Protocol:** HTTPS only. All requests must use TLS. +- **Format:** JSON request and response bodies. Responses include standard HTTP status codes. +- **Base URL:** `https://app.pixee.ai/api/v1` +- **Versioning:** Path-based (`/v1/`). Breaking changes ship under a new version prefix. + +## Authentication + +Pixee uses bearer tokens for API authentication. Tokens are scoped to your organization and generated from the Pixee dashboard. + +**Generate a token:** + +1. Navigate to **Settings > API Tokens** in the Pixee dashboard. +2. Click **Create Token**. +3. Name the token and select the scope (organization-wide or repository-specific). +4. Copy the token immediately. It is displayed only once. + +**Include the token in every request:** + +```bash +curl -H "Authorization: Bearer YOUR_API_TOKEN" \ + https://app.pixee.ai/api/v1/repositories +``` + +```python +import requests + +headers = {"Authorization": "Bearer YOUR_API_TOKEN"} +response = requests.get( + "https://app.pixee.ai/api/v1/repositories", + headers=headers +) +repositories = response.json() +``` + +**Token best practices:** + +- Rotate tokens every 90 days. +- Use repository-scoped tokens for CI/CD pipelines that operate on a single repository. +- Store tokens in your secrets manager (Vault, AWS Secrets Manager, GitHub Actions secrets). Never commit tokens to source control. + +## Rate limits + +| Tier | Requests per minute | Burst | +| ---------- | ------------------- | ----- | +| Standard | 60 | 10 | +| Enterprise | 300 | 50 | + +Rate-limited responses return `429 Too Many Requests` with a `Retry-After` header indicating seconds until the next available request window. + +## Available endpoints + +| Category | Method | Endpoint | Description | +| ------------ | -------- | ----------------------------- | ------------------------------------------------ | +| Repositories | `GET` | `/repositories` | List repositories connected to your organization | +| Repositories | `GET` | `/repositories/{id}` | Get repository configuration and status | +| Repositories | `PATCH` | `/repositories/{id}` | Update repository settings | +| Fixes | `GET` | `/repositories/{id}/fixes` | List fix results for a repository | +| Fixes | `GET` | `/fixes/{id}` | Get fix details including diff and rationale | +| Scans | `GET` | `/repositories/{id}/scans` | List scan history | +| Scans | `POST` | `/repositories/{id}/scans` | Trigger a new scan | +| Triage | `GET` | `/repositories/{id}/findings` | List triaged findings | +| Triage | `GET` | `/findings/{id}` | Get finding details and triage classification | +| Webhooks | `POST` | `/webhooks` | Register a webhook endpoint | +| Webhooks | `GET` | `/webhooks` | List registered webhooks | +| Webhooks | `DELETE` | `/webhooks/{id}` | Remove a webhook | + +For webhook event types and payload schemas, see [Webhooks](/api/webhooks). + +## Error handling + +All error responses use a consistent JSON structure: + +```json +{ + "error": { + "code": "not_found", + "message": "Repository with ID 'abc123' not found.", + "request_id": "req_7f8a9b2c" + } +} +``` + +| Status code | Meaning | +| ----------- | --------------------------------------------------------------------------------------------------- | +| `400` | Bad request. Check request body and parameters. | +| `401` | Invalid or missing API token. | +| `403` | Token does not have permission for this resource. | +| `404` | Resource not found. | +| `429` | Rate limit exceeded. Retry after the interval in the `Retry-After` header. | +| `500` | Internal server error. Retry with exponential backoff. Include the `request_id` in support tickets. | + +## Quick start + +List your repositories and retrieve recent fix results in two calls: + +```bash +# 1. List repositories +curl -s -H "Authorization: Bearer $PIXEE_TOKEN" \ + https://app.pixee.ai/api/v1/repositories | jq '.data[].name' + +# 2. Get fixes for a repository +curl -s -H "Authorization: Bearer $PIXEE_TOKEN" \ + https://app.pixee.ai/api/v1/repositories/REPO_ID/fixes | jq '.data[:3]' +``` + +```python +import requests + +TOKEN = "YOUR_API_TOKEN" +BASE = "https://app.pixee.ai/api/v1" +headers = {"Authorization": f"Bearer {TOKEN}"} + +# List repositories +repos = requests.get(f"{BASE}/repositories", headers=headers).json() +repo_id = repos["data"][0]["id"] + +# Get recent fixes +fixes = requests.get( + f"{BASE}/repositories/{repo_id}/fixes", + headers=headers, + params={"limit": 5} +).json() + +for fix in fixes["data"]: + print(f"{fix['codemod']} - {fix['status']} - {fix['pr_url']}") +``` + +## Input format + +Pixee consumes scanner output in **SARIF** -- the OASIS standard for static analysis results -- from natively integrated scanners and any SARIF-producing tool. See the [SARIF Reference](/api/sarif). + +## SDKs and OpenAPI specification + +An OpenAPI 3.0 specification is available for generating client libraries in any language: + +```bash +curl -o pixee-openapi.json \ + https://app.pixee.ai/api/v1/openapi.json +``` + +Use the specification with standard code generators: + +```bash +# Python client +openapi-python-client generate --path pixee-openapi.json + +# TypeScript client +npx @openapitools/openapi-generator-cli generate \ + -i pixee-openapi.json -g typescript-fetch +``` + +## Related pages + +- [SARIF Reference](/api/sarif) -- How Pixee consumes SARIF from scanners +- [Webhooks](/api/webhooks) -- Event-driven integration for CI/CD and automation +- [CI/CD Integration](/integrations/ci-cd) -- Common API consumer patterns +- [Configuration Overview](/configuration/overview) -- Repository management diff --git a/docs/api/cli.md b/docs/api/cli.md new file mode 100644 index 00000000..a7a90779 --- /dev/null +++ b/docs/api/cli.md @@ -0,0 +1,147 @@ +--- +title: Pixee CLI +slug: /api/cli +track: dev +content_type: tutorial +seo_title: "Pixee CLI | Command-Line Client for the Pixee Platform" +description: Install the Pixee CLI to authenticate against a Pixee deployment and drive the REST API from your terminal, scripts, or coding agents. +sidebar_position: 6 +--- + +The Pixee CLI (`pixee`) is the command-line client for the Pixee platform. It authenticates against a Pixee deployment, exposes dedicated subcommands for the most common operations (listing repositories, inspecting scans, configuring workflows), and provides a generic `pixee api` passthrough for any other REST endpoint. The CLI is intended for Pixee customers — it talks _to_ a Pixee deployment, it does not run analysis or generate fixes locally. Source distribution: [github.com/pixee/pixee-cli](https://github.com/pixee/pixee-cli). + +## When to Use the CLI + +The CLI complements the SCM integrations (GitHub App, GitLab, Azure DevOps, Bitbucket); it does not replace them. Triage and remediation continue to run on the Pixee platform, triggered by your SCM integration. Use the CLI when you need to: + +- **Query platform state from scripts.** List registered repositories, fetch scan history, inspect workflows. +- **Configure workflows from the command line.** Create, update, or delete schedule / new-scan / pull-request-scan workflows on a repository. +- **Drive the API from a coding agent.** Bundled `skills.sh`-formatted skills teach Claude Code, OpenAI Codex, and other agents how to use the CLI safely. +- **Hit any REST endpoint without writing curl.** The `pixee api` subcommand handles authentication, pagination, and HAL link traversal. + +## Installation + +### Homebrew (macOS and Linux) + +```bash +brew tap pixee/pixee +brew install pixee +``` + +### Direct download + +Pre-compiled binaries for `linux-x64`, `darwin-arm64`, and `windows-x64` are published as assets on every [GitHub Release](https://github.com/pixee/pixee-cli/releases/latest). Download the archive, extract `pixee`, place it on your `PATH`. + +Verify: + +```bash +pixee --version +``` + +## Authenticate + +You need a Pixee API token (generated from the admin console's **API Tokens** page) and the URL of your Pixee deployment. + +```bash +# Interactive login — stores token + server in a platform-appropriate config file. +pixee auth login --server https://pixee.example.com --token pixee_xxx + +# Stdin form — keeps the token off the command line and out of shell history. +echo -n "$PIXEE_TOKEN" | pixee auth login --server https://pixee.example.com --token - + +# Confirm. +pixee auth status +# Logged in to https://pixee.example.com as api-token +# Token: valid +``` + +The token is written with `0600` permissions on Unix; Windows inherits the per-user directory's NTFS ACL. + +**Credential resolution.** For every subcommand except `pixee auth login`, the CLI resolves credentials in this order: + +- **Token:** `PIXEE_TOKEN` env var → stored config. +- **Server:** `--server` flag → `PIXEE_SERVER` env var → stored config. + +Setting `PIXEE_TOKEN` and `PIXEE_SERVER` is the standard CI/CD path — no `pixee auth login` step is required in pipelines. + +## Common Commands + +| Command | What It Does | +| ------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- | +| `pixee repo list` | List repositories registered with the platform. Filter with `--name `. | +| `pixee scan list --repo ` | List scans for a repository. Filter with `--branch`, `--tool`, `--analysis-state`, `--has-analysis`. | +| `pixee scan get ` | Fetch a single scan by UUID. | +| `pixee workflow list --repo ` | List workflows on a repository. | +| `pixee workflow create schedule --repo --cadence weekly ...` | Create a schedule workflow. Sibling subcommands: `new-scan`, `pull-request-scan`. | +| `pixee workflow update ...` | Update an existing workflow (partial-update semantics). | +| `pixee workflow delete ` | Remove a workflow. | +| `pixee api /api/v1/repositories --paginate` | Send an authenticated GET to any endpoint, walking pagination. | +| `pixee api /api/v1/ --method POST --input body.json` | POST a JSON body. | +| `pixee --help` | Show all available commands. | +| `pixee --help` | Show command-specific flags. | + +The dedicated subcommands cover the common cases. `pixee api` is the escape hatch — use it when a dedicated subcommand does not yet exist, or when a coding agent needs to compose multi-step operations directly. + +## Output Format + +All subcommands accept `--output text` (default — flat, line-oriented, suitable for `grep`/`awk`) or `--output json` (machine-readable, pipe to `jq`). The `--json` shorthand is equivalent to `--output json`. + +```bash +pixee repo list --json | jq '.[] | select(.type == "github") | .full_name' +``` + +## Exit Codes + +Scripts and agents can branch on these without parsing stderr: + +| Code | Meaning | +| ---- | ------------------------------------------------------------------------- | +| 0 | Success | +| 1 | General error | +| 2 | Authentication failure (token missing, expired, invalid, or wrong server) | +| 3 | Resource not found | + +Errors from the Pixee API are returned as `application/problem+json`. With `--output text`, the CLI renders the problem document in compact human-readable form; with `--output json` the raw document passes through unchanged. + +## HAL Discovery via `pixee api` + +The Pixee REST API is a HAL (Hypertext Application Language) API. Every response includes `_links` to related resources. Start at `/api/v1` and follow links rather than hardcoding paths: + +```bash +# Inspect the root. +pixee api /api/v1 + +# Follow the "repositories" link. +pixee api /api/v1/repositories --paginate + +# Drill into a specific repository — its _links lead to scans, workflows, etc. +pixee api /api/v1/repositories/ +``` + +## Coding-Agent Skills + +The CLI ships [skills.sh](https://skills.sh)-formatted skills that teach coding agents (Claude Code, OpenAI Codex, and others) how to drive the CLI without you re-explaining the conventions every time. Skills cover global flags and exit codes (`pixee-shared`), authentication (`pixee-auth`), the `pixee api` escape hatch (`pixee-api`), and each command group (`pixee-repo`, `pixee-scan`, `pixee-workflow`). + +```bash +# Install all skills. +npx skills add pixee/pixee-cli --all + +# Or pick interactively. +npx skills add pixee/pixee-cli +``` + +The skills are licensed separately under Apache 2.0 and live in the [`skills/`](https://github.com/pixee/pixee-cli/tree/main/skills) directory of the CLI repo. + +## CLI in CI/CD + +The CLI is well-suited to running inside CI: set `PIXEE_TOKEN` and `PIXEE_SERVER` as secrets, install the binary, and call any subcommand. Common patterns: + +```bash +# Inspect platform state during a release pipeline. +pixee scan list --repo "$REPO" --branch main --tool codeql --json + +# Create or update a workflow as part of repository provisioning. +pixee workflow create new-scan --repo "$REPO" --tool codeql ... +``` + +The CLI does not run analysis or generate fixes — those happen on the platform, triggered by your SCM integration. See [CI/CD Integration](/integrations/ci-cd) for the end-to-end pipeline patterns. diff --git a/docs/api/sarif.md b/docs/api/sarif.md new file mode 100644 index 00000000..28f2f8e9 --- /dev/null +++ b/docs/api/sarif.md @@ -0,0 +1,191 @@ +--- +title: SARIF Reference +slug: /api/sarif +track: dev +content_type: reference +seo_title: SARIF Reference -- Pixee Docs +description: How Pixee consumes SARIF from scanners. Field mapping, required fields, validation, and integration examples. +sidebar_position: 2 +--- + +# SARIF Reference + +SARIF (Static Analysis Results Interchange Format) is the OASIS standard that Pixee uses to ingest security findings from its named scanner integrations and any SARIF-producing tool. Pixee reads SARIF files to understand what vulnerabilities were found, where they are located, and what dataflow information is available -- then routes each finding to the appropriate triage and remediation engine. This page documents how Pixee consumes SARIF. + +## What is SARIF? + +SARIF is an [OASIS open standard](https://docs.oasis-open.org/sarif/sarif/v2.1.0/sarif-v2.1.0.html) for representing static analysis tool output. It provides a common JSON format for any scanner to express findings, locations, code flows, and rule metadata. + +Pixee supports **SARIF version 2.1.0**, the current stable release of the standard. + +SARIF matters to Pixee's architecture because it enables scanner-agnostic remediation. Rather than building custom parsers for every scanner output format, Pixee normalizes all findings through SARIF. Any tool that produces valid SARIF can feed findings into Pixee for triage and remediation. + +## How Pixee uses SARIF + +``` +Scanner --> SARIF file --> Pixee ingestion --> Triage --> Fix --> PR +``` + +1. **Ingestion.** SARIF files arrive via webhook from native scanner integrations, via the Universal SARIF integration, or via API upload. +2. **Normalization.** Scanner-specific handlers extract maximum metadata from each tool's SARIF output. When a native handler does not exist, the Universal SARIF handler processes any valid SARIF document. +3. **Triage routing.** Normalized findings enter the three-tier triage engine. Findings with richer SARIF data (code flows, related locations) receive higher-quality triage and remediation. +4. **Output.** Remediation results are delivered as pull requests on the target repository. + +## Required and optional SARIF fields + +Pixee reads specific SARIF fields to route findings and generate fixes. Richer SARIF input produces better results. + +### Required fields + +These fields must be present for Pixee to process a finding: + +| SARIF Field | Type | Pixee Usage | +| -------------------------------------------------------------------- | ------- | ------------------------------------------------------- | +| `runs[].tool.driver.name` | string | Scanner identification and handler routing | +| `runs[].results[].ruleId` | string | Rule matching for fix routing and knowledge base lookup | +| `runs[].results[].message.text` | string | Finding description for triage context | +| `runs[].results[].locations[].physicalLocation.artifactLocation.uri` | string | File path of the vulnerability | +| `runs[].results[].locations[].physicalLocation.region.startLine` | integer | Line number of the vulnerability | + +### Recommended fields + +These fields are not required, but significantly improve triage accuracy and fix quality: + +| SARIF Field | Type | Pixee Usage | +| -------------------------------------------- | ------ | --------------------------------------------------------------------- | +| `runs[].results[].codeFlows[]` | array | Dataflow and taint propagation paths. Enables cross-file fix context. | +| `runs[].results[].codeFlows[].threadFlows[]` | array | Step-by-step execution paths through the vulnerability | +| `runs[].results[].relatedLocations[]` | array | Additional code context (sink locations, intermediate variables) | +| `runs[].results[].level` | string | Severity classification (`error`, `warning`, `note`) | +| `runs[].tool.driver.rules[]` | array | Rule metadata including descriptions and help text | +| `runs[].tool.extensions[]` | array | Extension packs with additional rule documentation | + +### Optional fields + +| SARIF Field | Type | Pixee Usage | +| -------------------------------------- | ------ | ------------------------------------------------------ | +| `runs[].results[].fingerprints` | object | Finding deduplication across scans | +| `runs[].results[].partialFingerprints` | object | Fuzzy matching for findings that shift between scans | +| `runs[].results[].suppressions[]` | array | Previously suppressed findings (Pixee respects these) | +| `runs[].results[].properties` | object | Custom scanner metadata preserved through the pipeline | + +## Dataflow quality and fix quality + +The richness of SARIF `codeFlows` data directly affects fix quality. Pixee classifies dataflow quality into four tiers: + +| Tier | SARIF Signal | Fix Impact | +| ---------------------- | ------------------------------------------------------ | ---------------------------------------------------------------------------------------- | +| **STRONG_MULTI_FILE** | `codeFlows` with `threadFlows` spanning multiple files | Highest fix quality. Cross-file context enables precise remediation. | +| **STRONG_SINGLE_FILE** | `codeFlows` with `threadFlows` within a single file | High fix quality. Full taint path available for context-aware fixes. | +| **WEAK** | Partial or low-confidence `codeFlows` | Moderate fix quality. Pixee uses heuristics to supplement incomplete paths. | +| **SINGLE_LOCATION** | Only `locations[]`, no `codeFlows` | Baseline fix quality. Pixee relies on rule knowledge base and surrounding code analysis. | + +**Recommendation:** Configure your scanner to export `codeFlows` and `threadFlows` when available. CodeQL and Semgrep produce rich dataflow by default. Some scanners require explicit configuration to include flow data in SARIF output. + +## SARIF validation + +Pixee validates incoming SARIF documents against the 2.1.0 schema before processing. + +**Common validation failures:** + +| Issue | Cause | Fix | +| ----------------------------------- | ---------------------------------------------- | --------------------------------------------------------------------------------------- | +| Missing `runs` array | Malformed SARIF document | Ensure the top-level object contains a `runs` array with at least one run | +| Empty `results` | Scanner found no findings | Expected behavior -- Pixee logs the scan but generates no fixes | +| Missing `locations` on a result | Scanner omitted location data | Configure scanner to include file and line information | +| Invalid `uri` in `artifactLocation` | Path uses backslashes or absolute system paths | Use forward slashes and repository-relative paths | +| Missing `ruleId` | Scanner omitted the rule identifier | Ensure scanner output includes rule IDs. Pixee cannot route findings without a rule ID. | + +Validate your SARIF files before upload using the [SARIF Multitool](https://github.com/microsoft/sarif-sdk): + +```bash +sarif validate my-results.sarif +``` + +## Integration examples + +### Upload SARIF via API + +```bash +curl -X POST \ + -H "Authorization: Bearer $PIXEE_TOKEN" \ + -H "Content-Type: application/json" \ + -d @scanner-results.sarif \ + https://app.pixee.ai/api/v1/repositories/REPO_ID/sarif +``` + +### Python: Upload and poll for results + +```python +import requests +import time + +TOKEN = "YOUR_API_TOKEN" +BASE = "https://app.pixee.ai/api/v1" +REPO_ID = "your-repo-id" +headers = {"Authorization": f"Bearer {TOKEN}"} + +# Upload SARIF +with open("scanner-results.sarif", "r") as f: + sarif_data = f.read() + +upload = requests.post( + f"{BASE}/repositories/{REPO_ID}/sarif", + headers={**headers, "Content-Type": "application/json"}, + data=sarif_data +) +scan_id = upload.json()["scan_id"] + +# Poll for completion +while True: + status = requests.get( + f"{BASE}/repositories/{REPO_ID}/scans/{scan_id}", + headers=headers + ).json() + + if status["state"] in ("completed", "failed"): + break + time.sleep(10) + +print(f"Scan {status['state']}: {status.get('fixes_generated', 0)} fixes generated") +``` + +### CI/CD pipeline: Scanner to Pixee to PR + +```yaml +# GitHub Actions example +- name: Run CodeQL + uses: github/codeql-action/analyze@v3 + with: + output: sarif-results + +- name: Upload to Pixee + run: | + curl -X POST \ + -H "Authorization: Bearer ${{ secrets.PIXEE_TOKEN }}" \ + -H "Content-Type: application/json" \ + -d @sarif-results/results.sarif \ + https://app.pixee.ai/api/v1/repositories/${{ vars.PIXEE_REPO_ID }}/sarif +``` + +## Scanner-specific SARIF notes + +Native scanner integrations handle SARIF automatically. These notes apply when you generate SARIF manually or use the Universal SARIF integration. + +| Scanner | SARIF Notes | +| ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **CodeQL** | Produces rich SARIF with `codeFlows`, `threadFlows`, and `tool.extensions[].rules[].help.markdown`. Pixee extracts all of these for maximum triage context. | +| **Semgrep** | Exports SARIF via `semgrep --sarif`. Rule explanations are in `fullDescription.text`. Include `--verbose` for richer output. | +| **SonarQube** | SARIF export varies by edition. Ensure `codeFlows` are included when available. | +| **Checkmarx** | Produces metadata-sparse SARIF. Pixee compensates with rule-ID-based prompting from its knowledge base. | +| **Snyk** | Use `snyk code test --sarif` for SAST results. | +| **Trivy** | Use `trivy fs --format sarif` for filesystem scanning results. | + +For full setup guides per scanner, see [Integrations Overview](/integrations/overview). + +## Related pages + +- [API Overview](/api/overview) -- Authentication and endpoint reference +- [Universal SARIF Integration](/integrations/sarif-universal) -- Setup guide for SARIF ingestion +- [Integrations Overview](/integrations/overview) -- All supported scanners +- [Scanner Integration](/platform/scanner-integration) -- Technical depth on scanner normalization diff --git a/docs/api/webhooks.md b/docs/api/webhooks.md new file mode 100644 index 00000000..db2d669f --- /dev/null +++ b/docs/api/webhooks.md @@ -0,0 +1,304 @@ +--- +title: Webhooks +slug: /api/webhooks +track: dev +content_type: reference +seo_title: Webhooks -- Pixee Docs +description: Configure Pixee webhooks for real-time notifications on fix generation, PR status, triage decisions, and remediation events. +sidebar_position: 3 +--- + +# Webhooks + +Pixee webhooks deliver real-time HTTP POST notifications when remediation events occur -- fix generated, PR opened, triage decision made, or fix merged. Configure webhook endpoints to integrate Pixee with your ticketing system, SIEM, Slack channels, or custom automation pipelines. This page documents available event types, payload schemas, authentication, retry behavior, and setup instructions. + +## Event types + +| Event | Trigger | Payload Includes | +| ------------------ | ------------------------------------------------- | -------------------------------------------------------------------------------------- | +| `fix.generated` | A fix passes evaluation and is ready for delivery | Fix summary, finding metadata, repository, codemod ID | +| `pr.opened` | A pull request or merge request is created | PR URL, fix summary, affected files, target branch | +| `pr.merged` | A fix PR is merged by a developer | PR URL, merge metadata, fix details, merge timestamp | +| `pr.closed` | A fix PR is closed without merging | PR URL, close reason, closed-by metadata | +| `triage.completed` | A finding finishes triage classification | Finding ID, classification (TRUE_POSITIVE, FALSE_POSITIVE, WONT_FIX), evidence summary | +| `scan.completed` | A repository scan finishes processing | Repository, findings count, fixes generated, scan duration | + +Subscribe to individual event types or use `*` to receive all events. + +## Payload schema + +Every webhook payload includes a common envelope with event-specific data nested under `data`. + +### Common envelope + +```json +{ + "id": "evt_a1b2c3d4e5", + "type": "pr.merged", + "created_at": "2026-04-25T14:30:00Z", + "organization": "acme-corp", + "repository": "backend-api", + "data": {} +} +``` + +| Field | Type | Description | +| -------------- | ------ | ---------------------------- | +| `id` | string | Unique event identifier | +| `type` | string | Event type (see table above) | +| `created_at` | string | ISO 8601 timestamp | +| `organization` | string | Organization slug | +| `repository` | string | Repository name | +| `data` | object | Event-specific payload | + +### fix.generated payload + +```json +{ + "id": "evt_f1x2g3n4", + "type": "fix.generated", + "created_at": "2026-04-25T14:30:00Z", + "organization": "acme-corp", + "repository": "backend-api", + "data": { + "fix_id": "fix_9a8b7c", + "codemod": "pixee:python/secure-random", + "summary": "Replaced insecure random with cryptographically secure alternative", + "files_changed": 1, + "detection_tool": "codeql", + "ai_generated": false, + "finding_ids": ["py/insecure-randomness"] + } +} +``` + +### pr.opened payload + +```json +{ + "id": "evt_p1r2o3", + "type": "pr.opened", + "created_at": "2026-04-25T14:31:00Z", + "organization": "acme-corp", + "repository": "backend-api", + "data": { + "pr_url": "https://github.com/acme-corp/backend-api/pull/142", + "pr_number": 142, + "title": "Fix insecure randomness in token generation", + "target_branch": "main", + "files": ["src/auth/token_generator.py"], + "fix_id": "fix_9a8b7c", + "codemod": "pixee:python/secure-random" + } +} +``` + +### triage.completed payload + +```json +{ + "id": "evt_t1r2g3", + "type": "triage.completed", + "created_at": "2026-04-25T14:29:00Z", + "organization": "acme-corp", + "repository": "backend-api", + "data": { + "finding_id": "f_abc123", + "rule_id": "py/insecure-randomness", + "classification": "TRUE_POSITIVE", + "severity": "high", + "justification": "The random.random() call generates session tokens passed to authentication middleware. The value is predictable and exploitable in a network-accessible context.", + "confidence": 0.95 + } +} +``` + +## Setup and configuration + +### Register via API + +```bash +curl -X POST \ + -H "Authorization: Bearer $PIXEE_TOKEN" \ + -H "Content-Type: application/json" \ + -d '{ + "url": "https://your-app.example.com/webhooks/pixee", + "events": ["pr.merged", "triage.completed", "scan.completed"], + "secret": "your-webhook-secret" + }' \ + https://app.pixee.ai/api/v1/webhooks +``` + +### Register via dashboard + +1. Navigate to **Settings > Webhooks** in the Pixee dashboard. +2. Click **Add Webhook**. +3. Enter your endpoint URL (must be HTTPS). +4. Select the event types to subscribe to. +5. Set a webhook secret for signature verification. +6. Click **Save**. + +### Endpoint requirements + +- HTTPS only. HTTP endpoints are rejected. +- Must respond with `2xx` within 10 seconds. +- Must accept `POST` requests with `Content-Type: application/json`. + +## Webhook signature verification + +Pixee signs every webhook payload with HMAC-SHA256 using your webhook secret. Verify signatures to confirm payloads originate from Pixee and have not been tampered with. + +The signature is sent in the `X-Pixee-Signature` header as a hex digest. + +### Verification example (Python) + +```python +import hmac +import hashlib +from flask import Flask, request, abort + +app = Flask(__name__) +WEBHOOK_SECRET = b"your-webhook-secret" + +@app.route("/webhooks/pixee", methods=["POST"]) +def handle_webhook(): + signature = request.headers.get("X-Pixee-Signature") + if not signature: + abort(401) + + expected = hmac.new( + WEBHOOK_SECRET, + request.data, + hashlib.sha256 + ).hexdigest() + + if not hmac.compare_digest(signature, expected): + abort(401) + + event = request.json + print(f"Received {event['type']} for {event['repository']}") + + # Process event + return "", 200 +``` + +### Verification example (Node.js) + +```javascript +const crypto = require("crypto"); +const express = require("express"); +const app = express(); + +const WEBHOOK_SECRET = "your-webhook-secret"; + +app.post( + "/webhooks/pixee", + express.raw({ type: "application/json" }), + (req, res) => { + const signature = req.headers["x-pixee-signature"]; + const expected = crypto + .createHmac("sha256", WEBHOOK_SECRET) + .update(req.body) + .digest("hex"); + + if ( + !crypto.timingSafeEqual(Buffer.from(signature), Buffer.from(expected)) + ) { + return res.status(401).send("Invalid signature"); + } + + const event = JSON.parse(req.body); + console.log(`Received ${event.type} for ${event.repository}`); + res.sendStatus(200); + }, +); +``` + +## Retry behavior + +When a webhook delivery fails, Pixee retries with exponential backoff: + +| Attempt | Delay | Cumulative Time | +| ----------- | ---------- | --------------- | +| 1 (initial) | Immediate | 0 | +| 2 | 30 seconds | 30s | +| 3 | 2 minutes | 2m 30s | +| 4 | 10 minutes | 12m 30s | +| 5 | 1 hour | 1h 12m 30s | + +A delivery is considered failed when: + +- The endpoint returns a non-`2xx` status code. +- The connection times out (10-second limit). +- DNS resolution or TLS handshake fails. + +After 5 failed attempts, the delivery is marked as failed. Review failed deliveries in **Settings > Webhooks > Delivery Log**. + +## Testing + +Send a test event to verify your endpoint is configured correctly: + +```bash +curl -X POST \ + -H "Authorization: Bearer $PIXEE_TOKEN" \ + https://app.pixee.ai/api/v1/webhooks/WEBHOOK_ID/test +``` + +The test event uses the `ping` type with a minimal payload: + +```json +{ + "id": "evt_test_ping", + "type": "ping", + "created_at": "2026-04-25T14:30:00Z", + "organization": "acme-corp", + "repository": null, + "data": { + "message": "Webhook configured successfully" + } +} +``` + +## Integration patterns + +### Slack notification on fix merged + +```python +import requests +from flask import Flask, request + +SLACK_WEBHOOK_URL = "https://hooks.slack.com/services/T00/B00/xxx" + +@app.route("/webhooks/pixee", methods=["POST"]) +def handle_webhook(): + event = request.json + + if event["type"] == "pr.merged": + requests.post(SLACK_WEBHOOK_URL, json={ + "text": f":white_check_mark: Fix merged in *{event['repository']}*\n" + f"<{event['data']['pr_url']}|{event['data']['title']}>" + }) + + return "", 200 +``` + +### Jira ticket on triage completion + +```python +if event["type"] == "triage.completed": + data = event["data"] + if data["classification"] == "TRUE_POSITIVE" and data["severity"] == "critical": + # Create Jira ticket for critical true positives + jira.create_issue( + project="SEC", + summary=f"Critical finding: {data['rule_id']} in {event['repository']}", + description=data["justification"], + priority="High" + ) +``` + +## Related pages + +- [API Overview](/api/overview) -- Authentication and endpoint reference +- [SARIF Reference](/api/sarif) -- Input format that triggers scan events +- [CI/CD Integration](/integrations/ci-cd) -- Common webhook consumer patterns diff --git a/docs/code-scanning-tools/_category_.json b/docs/code-scanning-tools/_category_.json deleted file mode 100644 index 86bdec71..00000000 --- a/docs/code-scanning-tools/_category_.json +++ /dev/null @@ -1,8 +0,0 @@ -{ - "label": "Code scanner support", - "position": 4, - "link": { - "type": "doc", - "id": "code-scanning-tools/overview" - } -} diff --git a/docs/code-scanning-tools/codeql.md b/docs/code-scanning-tools/codeql.md deleted file mode 100644 index b8dcb0b1..00000000 --- a/docs/code-scanning-tools/codeql.md +++ /dev/null @@ -1,12 +0,0 @@ ---- -title: "CodeQL" -sidebar_position: 4 ---- - -# CodeQL - -Pixee can automatically fix and triage issues detected by [CodeQL](https://codeql.github.com/). - -# GitHub Advanced Security - -No setup is required for GitHub Advanced Security (GHAS) users to receive fixes from CodeQL results that are uploaded as Code Scanning alerts. Triage for GHAS is best experienced through [our dashboard](https://app.pixee.ai). diff --git a/docs/code-scanning-tools/contrast.md b/docs/code-scanning-tools/contrast.md deleted file mode 100644 index e8d40cd7..00000000 --- a/docs/code-scanning-tools/contrast.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -title: "Contrast Security (IAST)" -sidebar_position: 4 ---- - -# Contrast Security Assess (IAST) - -Pixee can automatically fix and triage issues detected by [Contrast Assess (IAST)](https://contrastsecurity.com/). - -Use the [pixee/upload-tool-results-action](https://github.com/pixee/upload-tool-results-action) GitHub Action to synchronize Contrast findings with Pixee. diff --git a/docs/code-scanning-tools/overview.md b/docs/code-scanning-tools/overview.md deleted file mode 100644 index 2d96d508..00000000 --- a/docs/code-scanning-tools/overview.md +++ /dev/null @@ -1,54 +0,0 @@ ---- -sidebar_position: 4 ---- - -# Code Scanner support - -Pixee automatically triages and fixes issues detected by code scanning tools when synced with the results of those scans. This page explains how to integrate code scanning tools with Pixee. - -# Supported Tools - -- [Sonar (SonarCloud and SonarQube)](/code-scanning-tools/sonar) -- [Semgrep](/code-scanning-tools/semgrep) -- [CodeQL](/code-scanning-tools/codeql) -- [Snyk](/code-scanning-tools/snyk) -- [Contrast Security](/code-scanning-tools/contrast) -- HCL AppScan -- Checkmarx -- GitLab SAST -- Veracode -- Coverity on Polaris - -# Supported Rules - -Pixee can triage (T) and/or fix (F) a wide range of security issues detected by code scanning tools. Many of these issues are common across tools and languages, such as: - -- SQL Injection (T+F) -- Cross-Site Scripting (XSS) (T+F) -- Insecure Deserialization (T+F) -- Insecure Randomness (T+F) -- XML External Entity (XXE) (F) -- Insecure Cookie Handling (F) -- Command Injection (T+F) -- Insecure Configuration (T) -- Sensitive Data Logging (T) -- Resource Leak (F) -- Detailed Error Messages (T+F) -- SSRF (T+F) -- Hardcoded Passwords (T) -- XPath Injection (T+F) -- HTTP Response Splitting / Response Smuggling / Header Injection (T+F) -- Log Forging (T+F) -- Path Traversal (T) -- Open Redirect (T) -- ... and more! - -In addition, Pixee can triage and fix a variety of tool-specific, language-specific and code quality issues, too! - -Note that we won't claim support for a code scanner until we offer significant rule coverage, and we will then continue to mature our offering until complete. In this sense, we are always improving and expanding our rule coverage on all tools as we continue adding more triage and fix capabilities. - -# GitHub Action - -Pixee provides a [GitHub Action](https://github.com/marketplace/actions/upload-tool-results-to-pixeebot) that can be used to upload the results of code scanning tools to Pixee. - -We are also working to support "native" integrations with code scanning tools. If you need support for a tool not listed here, please [contact us](https://pixee.ai/demo-landing-page). diff --git a/docs/code-scanning-tools/semgrep-issue-dashlist.png b/docs/code-scanning-tools/semgrep-issue-dashlist.png deleted file mode 100644 index bc512cdb..00000000 Binary files a/docs/code-scanning-tools/semgrep-issue-dashlist.png and /dev/null differ diff --git a/docs/code-scanning-tools/semgrep.md b/docs/code-scanning-tools/semgrep.md deleted file mode 100644 index f2b3af2a..00000000 --- a/docs/code-scanning-tools/semgrep.md +++ /dev/null @@ -1,68 +0,0 @@ ---- -title: "Semgrep" -sidebar_position: 3 ---- - -# Semgrep - -Pixee can automatically triage and fix issues detected by [Semgrep OSS](https://semgrep.dev/). - -# GitHub Advanced Security - -No setup is required for GitHub Advanced Security (GHAS) users to receive fixes from Semgrep results that are uploaded as Code Scanning alerts. Simply installing the Pixeebot GitHub App is sufficient. - -# Others - -Use the [pixee/upload-tool-results-action](https://github.com/pixee/upload-tool-results-action) GitHub Action together with the Pixeebot GitHub App to synchronize Semgrep findings with Pixee. - -The following GitHub Action workflow example demonstrates how to include Semgrep OSS vulnerability detection with Pixee fixes in a Java application: - -```yaml -name: Analyze with Semgrep and Fix with Pixee - -on: - push: - branches: - - main - pull_request: - branches: - - main - -permissions: - contents: read - id-token: write - -jobs: - build: - runs-on: ubuntu-latest - - steps: - - name: Checkout repository - uses: actions/checkout@v4 - - - name: Install Semgrep - run: | - python3 -m pip install semgrep - - - name: Run Semgrep - run: | - semgrep --config auto --sarif --output semgrep-results.sarif.json - - - name: Fix with Pixee - uses: pixee/upload-tool-results-action@v2 - with: - tool: semgrep - file: semgrep-results.sarif.json -``` - -This workflow: - -1. Runs Semgrep OSS on the project and stores the results in a standard SARIF file. -2. Runs the pixee/upload-tool-results-action that sends the SARIF file to Pixee. - -Once Pixee receives the Semgrep OSS vulnerabilities, it recalls them on its next analysis of this commit. - -- When this commit the head of a pull request, then Pixee triggers its _PR Hardening_ analysis to fix as many Semgrep findings in this PR as it can. -- When this commit is the head of the main branch, then Pixee uses these findings the next time its _Continuous Improvement Campaign_ analysis runs. Users may trigger such an analysis to occur immediately by issuing the chat command `@pixeebot next` in any PR or issue comment on this repository. Pixee's continuous improvement campaign shows the queue of fixes in Pixeebot Acitvity Dashboard issue. - - ![Pixeebot Activity Dashboard issue](./semgrep-issue-dashlist.png) diff --git a/docs/code-scanning-tools/snyk.md b/docs/code-scanning-tools/snyk.md deleted file mode 100644 index 2ca1a3a7..00000000 --- a/docs/code-scanning-tools/snyk.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -title: "Snyk Code" -sidebar_position: 4 ---- - -# Snyk Code - -Pixee can automatically fix and triage issues detected by [Snyk Code](https://snyk.io/). - -# GitHub Advanced Security - -No setup is required for GitHub Advanced Security (GHAS) users to receive fixes from Snyk results that are uploaded as Code Scanning alerts. Triage for GHAS is best experienced through [our dashboard](https://app.pixee.ai). - -# Others - -Use the [pixee/upload-tool-results-action](https://github.com/pixee/upload-tool-results-action) GitHub Action to synchronize Snyk Code findings with Pixee. diff --git a/docs/code-scanning-tools/sonar.md b/docs/code-scanning-tools/sonar.md deleted file mode 100644 index 25d33d44..00000000 --- a/docs/code-scanning-tools/sonar.md +++ /dev/null @@ -1,29 +0,0 @@ ---- -title: "SonarCloud" -sidebar_position: 1 ---- - -# SonarCloud - -Pixee can automatically fix issues detected by [SonarCloud](https://www.sonarsource.com/products/sonarcloud/). This page explains how to integrate your SonarCloud results with Pixee. - -:::info -Looking to fix [SonarQube](https://www.sonarsource.com/products/sonarqube/) issues? See [SonarQube](./sonarqube.md) -::: - -## How to Get Started - -1. Install [Pixee GitHub Application](https://github.com/marketplace/pixeebot-automated-code-fixes) -2. Install [Sonar GitHub Application](https://github.com/marketplace/sonarcloud) -3. Add [Upload Tool Results GitHub Action](https://github.com/marketplace/actions/upload-tool-results-to-pixeebot) -4. Start receiving Pull Requests from Pixee that address Sonar findings. - -## More Information - -Pixee fixes issues detected by SonarCloud when repositories have both the Pixee and SonarCloud GitHub Apps installed. - -For public repositories using SonarCloud, Pixee retrieves results from sonarcloud.io automatically with no further configuration required from the user. - -For private repositories using SonarCloud, use the [pixee/upload-tool-results-action](https://github.com/pixee/upload-tool-results-action) GitHub Action to synchronize SonarCloud findings with Pixee. - - diff --git a/docs/code-scanning-tools/sonarqube.md b/docs/code-scanning-tools/sonarqube.md deleted file mode 100644 index 834262db..00000000 --- a/docs/code-scanning-tools/sonarqube.md +++ /dev/null @@ -1,24 +0,0 @@ ---- -title: "SonarQube" -sidebar_position: 2 ---- - -# SonarQube - -Pixee can automatically fix issues detected by [SonarQube](https://www.sonarsource.com/products/sonarqube/). - -For a given Sonar rule, Pixee's fixes are the same, regardless of whether the issue was detected by either SonarCloud or SonarQube. However, the steps required to integrate Pixee with these systems is different. - -## How to Get Started - -1. Install [Pixee GitHub Application](https://github.com/marketplace/pixeebot-automated-code-fixes) -2. Add [Upload Tool Results GitHub Action](https://github.com/marketplace/actions/upload-tool-results-to-pixeebot) to workflows that run SonarQube analysis. -3. Start receiving Pull Requests from Pixee that address Sonar findings. - -## More Information - -Pixee offers an on premises solution that can be deployed alongside your SonarQube instance. Please contact us at help@pixee.ai for detailed setup instructions. - -SonarQube Community Edition lacks the features necessary to integrate with Pixee's PR experience. - - diff --git a/docs/configuration/_category_.json b/docs/configuration/_category_.json new file mode 100644 index 00000000..f308fb5f --- /dev/null +++ b/docs/configuration/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Configuration", + "position": 5, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "configuration/config-overview" + } +} diff --git a/docs/configuration/ai-settings.md b/docs/configuration/ai-settings.md new file mode 100644 index 00000000..f84ad543 --- /dev/null +++ b/docs/configuration/ai-settings.md @@ -0,0 +1,91 @@ +--- +title: AI Settings +slug: /configuration/ai-settings +track: dev +content_type: guide +seo_title: AI Settings -- Pixee Docs +description: Configure triage sensitivity, fix quality thresholds, and LLM provider settings for Pixee triage and remediation. +sidebar_position: 7 +--- + +# AI Settings + +Pixee's AI settings let you control how aggressively the triage engine classifies findings and how the remediation engine generates fixes. Adjust triage sensitivity to match your team's false positive tolerance, configure which finding categories receive AI-powered analysis versus deterministic codemods, and set quality thresholds for fix acceptance. Enterprise deployments can additionally configure LLM providers and model routing. + +## What AI Settings Control + +AI settings govern two behaviors: + +1. **Triage Automation behavior.** How aggressively Pixee classifies findings as true positives, false positives, or won't-fix. Higher sensitivity catches more issues but may surface more borderline findings. +2. **Remediation Automation behavior.** Which finding types receive AI-generated fixes versus deterministic code transformations (codemods), and the quality threshold fixes must meet before being presented as PRs. + +These settings tune behavior. They do not bypass validation. Every fix Pixee generates -- whether from a deterministic codemod or an AI-powered fix -- passes through the same multi-layer evaluation pipeline before reaching your PR queue. + +## Security Gates vs. Guardrails + +This distinction matters for understanding what AI settings do and do not control. + +**Security gates** block deployments when thresholds are exceeded. Your CI/CD pipeline owns these -- Pixee does not replace your existing gates. + +**Guardrails** guide behavior without blocking. Pixee's AI settings act as guardrails that tune how aggressively Triage Automation and Remediation Automation operate. They shape what Pixee proposes; your team and your CI pipeline decide what gets merged and deployed. + +Pixee operates as a guardrail layer. It proposes fixes through PRs. Your existing gates (CI checks, code review, deployment policies) remain in control of what ships. + +## Triage Settings + +Triage settings control how Pixee classifies scanner findings. + +| Setting | What It Controls | +| -------------------- | ---------------------------------------------------------------------------------------------------------------------------- | +| Triage sensitivity | How aggressively findings are classified. Higher sensitivity surfaces more findings; lower sensitivity is more conservative. | +| Category controls | Enable or disable triage for specific finding types (SAST, SCA, secrets, etc.) | +| Finding type filters | Which CWE categories receive AI-powered triage analysis | + +### How sensitivity affects results + +- **Conservative:** Fewer findings surfaced. Pixee only classifies findings it has high confidence in. Good for teams new to automated triage who want to build trust incrementally. +- **Balanced (default):** Moderate confidence threshold. Surfaces the majority of actionable findings while filtering obvious false positives. +- **Aggressive:** Surfaces more findings, including borderline cases. Useful for teams with mature triage workflows who want maximum coverage. + +### Relationship to scanner quality + +Triage accuracy depends on the quality of scanner input. Pixee integrates with a growing list of named scanner integrations and accepts any SARIF-producing scanner via universal SARIF import. Higher-quality scanner output yields higher-confidence triage results. + +## Remediation Settings + +Remediation settings control how Pixee generates fixes. + +| Setting | What It Controls | +| ----------------- | ------------------------------------------------------------------------- | +| Fix categories | Which CWE categories receive automated fixes | +| Fix mode | Whether a category uses deterministic codemods, AI-powered fixes, or both | +| Quality threshold | Minimum evaluation score a fix must meet before being presented as a PR | + +### The hybrid model + +Pixee uses a hybrid approach to fix generation: + +- **Deterministic codemods** apply well-known, deterministic code transformations. No LLM involved. These are the same open-source transformations available through [Codemodder](/open-source/codemodder). +- **AI-powered fixes** handle complex scenarios where deterministic patterns are insufficient. These use LLM-powered analysis to understand context and generate fixes. + +By default, both modes are active. You can disable AI-powered fixes entirely and run only deterministic codemods, or restrict AI-powered fixes to specific CWE categories. + +### Gradual automation + +The recommended approach is progressive expansion: + +1. **Start conservative.** Enable deterministic codemods only. Review merge rates and fix quality. +2. **Expand by category.** Enable AI-powered fixes for specific CWE categories where your team sees high fix quality. +3. **Broaden over time.** As confidence builds (tracked via merge rate and quality scores in [Reporting](/configuration/operations)), expand the scope of AI-powered fixes. + +The [Phased Rollout Guide](/enterprise/phased-rollout) covers this progression in detail. + +## Enterprise AI Configuration + +Self-hosted Pixee deployments have additional AI configuration beyond the behavioral settings described above: + +- **Bring Your Own Model (BYOM).** Choose your LLM provider (OpenAI, Azure AI Foundry, Anthropic, Azure Anthropic). Own your keys and control costs. See [Enterprise > BYOM](/enterprise/byom). +- **Model routing.** Enterprise deployments can route different analysis tasks to different models, balancing cost, latency, and quality per workflow stage. +- **Data flow controls.** Control what data reaches the LLM and through which network path. See [Enterprise > Security Architecture](/enterprise/security-architecture). + +These infrastructure-level settings are managed through the admin console or Helm values, not through the Pixee dashboard's AI settings page. diff --git a/docs/configuration/config-overview.md b/docs/configuration/config-overview.md new file mode 100644 index 00000000..2966d644 --- /dev/null +++ b/docs/configuration/config-overview.md @@ -0,0 +1,70 @@ +--- +title: Configuration Overview +slug: /configuration/overview +track: dev +content_type: guide +seo_title: Configuration Overview -- Pixee Docs +description: Configure Pixee behavior via PIXEE.yaml, organization settings, and AI settings. Covers repository management, scheduling, notifications, and reporting. +sidebar_position: 1 +--- + +# Configuration Overview + +Pixee is configurable at three levels: a PIXEE.yaml file in each repository for developer-controlled behavior, organization-wide settings in the Pixee dashboard for security team policies, and AI settings for tuning triage and remediation behavior. Most teams run Pixee with zero configuration on day one and customize as they scale. This section covers every configuration surface. + +## Configuration Philosophy + +Pixee works out of the box. The default settings enable Triage Automation and Remediation Automation for all supported languages and vulnerability types across your connected repositories. No PIXEE.yaml file, no dashboard toggles, no AI tuning required to start receiving pull requests with validated fixes. + +Configuration exists for when defaults are not enough. Maybe your team wants to exclude a test directory, batch PRs into weekly review cycles, or route Slack notifications to a security channel. Pixee's configuration model is designed around progressive customization: start with zero config, then layer on settings as you understand your team's needs. + +Two principles guide the model: + +- **Developer agency.** PIXEE.yaml lives in the repository root, version-controlled alongside your code. Developers own the behavior of Pixee in their repos the same way they own `.eslintrc` or `dependabot.yml`. +- **Security team governance.** Organization-wide settings in the Pixee dashboard let security leads enforce policy across all repositories without touching individual repos. + +## Configuration Layers + +Pixee settings operate across three layers. When a setting is defined at multiple layers, the more specific layer takes precedence. + +| Layer | Scope | Who Controls | Mechanism | +| ------------ | ----------------- | ------------- | ----------------------- | +| Repository | Single repo | Developers | PIXEE.yaml in repo root | +| Organization | All repos | Security team | Pixee dashboard | +| AI Settings | Analysis behavior | Security team | Pixee dashboard | + +**Precedence:** Repository-level PIXEE.yaml settings override organization defaults where applicable. Organization-level policies may restrict which PIXEE.yaml overrides are honored, giving security teams guardrails over developer-controlled configuration. + +If a PIXEE.yaml file is invalid or contains syntax errors, Pixee falls back to organization defaults and logs a warning. No analysis is skipped. + +## Quick Reference: What Goes Where + +Use this table to jump to the right page for your configuration task. + +| I want to... | Go to | +| ----------------------------------------------------- | ---------------------------------------------------- | +| Exclude specific files or directories from analysis | [PIXEE.yaml Reference](/configuration/pixee-yaml) | +| Ignore specific findings or CWE categories | [PIXEE.yaml Reference](/configuration/pixee-yaml) | +| Enable or disable specific fix types | [PIXEE.yaml Reference](/configuration/pixee-yaml) | +| Customize PR formatting (labels, title prefix) | [PIXEE.yaml Reference](/configuration/pixee-yaml) | +| Add or remove repositories from monitoring | [Repository Management](/configuration/repositories) | +| Organize repos by team or business unit | [Repository Management](/configuration/repositories) | +| Set scan schedules or switch to on-demand analysis | [Operations](/configuration/operations) | +| Route notifications to Slack or email | [Notifications](/configuration/operations) | +| Set up webhook integrations for custom workflows | [Notifications](/configuration/operations) | +| Manage team member access and roles | [Users & Access](/configuration/users) | +| Configure SSO with your identity provider | [Users & Access](/configuration/users) | +| Tune AI triage sensitivity | [AI Settings](/configuration/ai-settings) | +| Control which finding categories get AI-powered fixes | [AI Settings](/configuration/ai-settings) | +| Configure reporting exports or dashboards | [Reporting](/configuration/operations) | +| Export data for compliance audits | [Reporting](/configuration/operations) | + +## Getting Started with Configuration + +If you just installed Pixee, the recommended approach is: + +1. **Week one: run with defaults.** Let Pixee analyze your repositories and open PRs with its default settings. Review the fixes, check the triage results, and get a feel for the baseline behavior. +2. **Week two: customize per-repo behavior.** Add a PIXEE.yaml file to repositories that need specific exclusions, ignored findings, or PR formatting preferences. See [PIXEE.yaml Reference](/configuration/pixee-yaml) for common recipes. +3. **Ongoing: tune organization settings.** As you scale to more repositories, use the Pixee dashboard to set organization-wide policies for scheduling, notifications, and AI behavior. + +Enterprise self-hosted deployments have additional configuration surfaces for infrastructure (LLM providers, authentication, observability) managed through the admin console or Helm values. See [Enterprise > Deployment Options](/enterprise/deployment) for details. diff --git a/docs/configuration/operations-config.md b/docs/configuration/operations-config.md new file mode 100644 index 00000000..64a30a99 --- /dev/null +++ b/docs/configuration/operations-config.md @@ -0,0 +1,222 @@ +--- +title: Operations Configuration +slug: /configuration/operations +track: both +content_type: guide +seo_title: Operations Configuration -- Pixee Docs +description: Configure Pixee scheduling, notifications (Slack, email, webhooks), and reporting. Control analysis timing, alert routing, and metric exports. +sidebar_position: 4 +--- + +# Operations Configuration + +This page covers three operational areas: when Pixee runs analysis (scheduling), how your team hears about results (notifications), and how you track outcomes (reporting). + +## Scheduling + +Pixee can analyze code on every new scanner finding, on a fixed schedule, or on demand. By default, Pixee runs analysis when new findings are available from connected scanners. Customize scheduling to align with your team's development cadence -- running analysis during off-hours, batching PRs for weekly review, or triggering analysis only on specific branches. + +### Trigger Modes + +| Mode | How It Works | Best For | +| -------------------------- | ----------------------------------------------- | --------------------------------------------------------- | +| **Event-driven** (default) | Pixee analyzes when new scanner findings arrive | Teams that want immediate feedback on new vulnerabilities | +| **Scheduled** | Pixee analyzes on a cron schedule you define | Teams that prefer batched PRs at predictable times | +| **On-demand** | Trigger analysis via the dashboard or API | POC evaluations, testing, or ad-hoc analysis | + +Event-driven is the default and requires no configuration. Pixee watches for new SARIF uploads and native scanner results, then runs Triage Automation and Remediation Automation as findings arrive. + +### Cron Schedules + +Set a cron expression per repository or organization to control when Pixee runs analysis. Standard cron syntax is supported: + +``` +# Every weekday at 2:00 AM UTC +0 2 * * 1-5 + +# Every Monday at 6:00 AM UTC +0 6 * * 1 + +# Every 6 hours +0 */6 * * * +``` + +Configure schedules in the Pixee dashboard under repository or organization settings. + +### Timezone + +Cron schedules use UTC by default. Set a timezone in the dashboard to align schedules with your team's working hours. + +### Branch Filtering + +By default, Pixee analyzes findings from all branches. Restrict analysis to specific branches (for example, `main`, `develop`, or release branches) to focus on production-relevant code. + +### PR Timing and Batching + +Scheduling affects when PRs appear in your team's queue. + +- **Event-driven mode** creates PRs as soon as analysis completes. Expect PRs shortly after scanner findings arrive. +- **Scheduled mode** batches all findings discovered during the analysis window into PRs created at the scheduled time. +- **On-demand mode** creates PRs immediately after the manually triggered analysis completes. + +**Avoiding PR storms.** If Pixee discovers many findings during a scheduled run, it may open several PRs at once. To manage this: + +- Use PR labels (configured in [PIXEE.yaml](/configuration/pixee-yaml)) to filter Pixee PRs in your queue. +- Schedule analysis for off-hours so PRs are ready for review at the start of the workday. +- Set notification filters to surface only high-severity fixes. See [Notifications](#notifications) below. + +### Enterprise Scheduling + +Self-hosted Pixee deployments have additional scheduling considerations: + +- **Maintenance windows.** Schedule analysis outside your cluster's maintenance windows to avoid resource contention. +- **Concurrency controls.** Large deployments can configure how many repositories are analyzed concurrently to balance throughput with infrastructure load. +- **Monitoring.** Use the bundled observability stack to track analysis duration and queue depth. See [Enterprise > Observability](/enterprise/observability) for details. + +## Notifications + +Pixee delivers notifications through your existing communication channels -- SCM-native notifications (PR comments, status checks), Slack, email, and webhooks. Most teams use the default SCM notifications and add Slack for security team visibility. Configure notification routing so the right people see the right events without creating alert fatigue. + +### Notification Channels + +| Channel | Events | Configuration | +| -------------- | ------------------------------------------- | ----------------------------------------------------- | +| **SCM-native** | PR created, status checks, review comments | Automatic via your SCM integration -- no setup needed | +| **Slack** | New fixes, triage summaries, weekly digests | Connect the Slack App or provide a webhook URL | +| **Email** | Digest summaries, critical alerts | Per-user or team email addresses in the dashboard | +| **Webhooks** | All events (for custom integrations) | Webhook URL with optional secret for verification | + +SCM-native notifications are always active. Pixee PRs appear in your normal PR queue, status checks integrate with your CI pipeline, and PR comments provide triage context. No additional configuration is required for this channel. + +### Configuring Slack + +Connect Pixee to Slack to notify your security team when new fixes are available, triage results are ready, or weekly digests are generated. + +**Setup:** + +1. In the Pixee dashboard, navigate to notification settings. +2. Connect the Slack App or provide an incoming webhook URL for your target channel. +3. Select which event types to route to the channel. + +**Filtering options:** + +- **By severity:** Notify only on critical and high-severity findings, or include medium and low. +- **By repository:** Route different repositories to different Slack channels. +- **By fix type:** Separate SAST fix notifications from SCA dependency updates. + +Per-repository Slack routing is useful for large organizations where different teams own different services. + +### Email + +Email notifications deliver digest summaries and critical alerts to individual users or team distribution lists. + +| Setting | Options | +| ---------- | ----------------------------------------------------------------- | +| Frequency | Per-event, daily digest, weekly digest | +| Scope | All repositories, specific repositories, specific severity levels | +| Recipients | Individual email addresses or team distribution lists | + +Configure email preferences per-user in the Pixee dashboard. Each team member can choose their own notification frequency and scope. + +### Webhooks + +Webhooks send event payloads to any HTTP endpoint, enabling integration with PagerDuty, ServiceNow, Jira, or custom dashboards. + +**Configuration:** + +- Provide a webhook URL in the Pixee dashboard. +- Optionally configure a shared secret for payload verification. +- Select which event types trigger the webhook. + +Webhook payloads are JSON-formatted. For the full payload specification, see [API > Webhooks](/api/webhooks). + +**Common integrations:** + +| System | Use Case | +| ----------------- | --------------------------------------------------- | +| Jira | Auto-create tickets for high-severity findings | +| ServiceNow | Feed remediation data into ITSM workflows | +| PagerDuty | Alert on-call teams for critical vulnerabilities | +| Custom dashboards | Aggregate Pixee data alongside other security tools | + +### Reducing Notification Noise + +The goal is signal, not volume. Teams running Pixee at scale use these strategies: + +- **Severity filtering.** Notify on critical and high findings immediately; batch medium and low findings into daily or weekly digests. +- **Per-repository overrides.** High-traffic repositories get digest-only notifications. Production-critical repos get per-event alerts. +- **Channel separation.** Route developer-facing notifications (PR events) through SCM-native channels. Route security-team notifications (triage summaries, compliance digests) through Slack or email. +- **Webhook filtering.** When using webhooks, filter by event type at the source to avoid processing irrelevant payloads downstream. + +## Reporting + +Pixee tracks every triage decision and remediation outcome, giving your team visibility into what was analyzed, what was fixed, and what remains. Use built-in reports for day-to-day monitoring, export data for compliance evidence, or connect to external dashboards via the API. + +### Available Reports and Metrics + +| Report | What It Shows | Who Uses It | +| ------------------------ | ------------------------------------------------------------------------ | ------------------------------------------------------------ | +| **Triage Summary** | Findings classified by outcome: true positive, false positive, won't fix | Security leads reviewing triage quality | +| **Fix Activity** | PRs created, merged, closed, and pending review | Developers and security leads tracking remediation progress | +| **Merge Rate** | Percentage of Pixee PRs merged by developers | Management and security leads measuring developer acceptance | +| **Remediation Velocity** | Time from finding to merged fix | Compliance teams tracking MTTR reduction | +| **Repository Status** | Per-repo analysis state, last scan time, recent activity | Developers checking individual repo health | + +**Merge rate** is the percentage of Pixee PRs that developers review and merge. It is a primary indicator of fix quality and relevance. See [Security & Trust](/platform/security) for production metrics. + +**Remediation velocity** measures the elapsed time from when a finding is detected to when its fix is merged. This metric maps directly to Mean Time to Remediation (MTTR), a standard compliance metric. + +**Triage volume** tracks how many findings Pixee classified, broken down by true positive, false positive, and won't-fix outcomes. See [Triage](/platform/triage) for details on false positive reduction. + +### Dashboard + +The Pixee dashboard provides real-time visibility into triage and remediation activity across your organization. It is the primary interface for security leads monitoring program health and for developers tracking fix status. + +**Primary views:** + +| View | What It Shows | +| ----------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Overview** | Organization-wide summary: total findings triaged, true positive rate, open PRs, merged PRs, and remediation velocity. Entry point for daily monitoring. | +| **Findings** | All findings across connected repositories, filterable by status (triaged, awaiting fix, fixed), severity, scanner, language, and repository. Click any finding for the full triage verdict and evidence trail. | +| **Pull Requests** | All Pixee-generated PRs across repositories — open, merged, and closed. Shows PR status, fix type (deterministic or AI), quality scores, and time since creation. | +| **Repositories** | Per-repository status: last scan time, finding count, triage coverage, and PR activity. Shows which repositories are active and which have pending configuration. | +| **Reports** | Access to metric summaries, trend charts, and export controls. See [Exporting Data](#exporting-data) below. | + +**Filtering options:** + +| Filter | Options | +| ---------- | -------------------------------------------------- | +| Repository | Single repo, multiple repos, or all repos | +| Time range | Last 7 days, 30 days, 90 days, custom range | +| Severity | Critical, High, Medium, Low | +| Language | Java, Python, JavaScript/TypeScript, .NET, Go, PHP | +| Scanner | Filter by the source scanner for a finding or PR | + +**Trend views** show how metrics change over time — track merge rate improvement as your team builds confidence in automated fixes, watch triage volume shift as false positives are eliminated, and monitor remediation velocity across release cycles. Trend data is available for any custom time range and can be exported for compliance reporting or executive review. + +### Exporting Data + +| Format | Use Case | +| -------- | ---------------------------------------------------------------- | +| **CSV** | Import into spreadsheets, BI tools, or custom analysis pipelines | +| **JSON** | Programmatic consumption, custom dashboard integration | +| **API** | Real-time data access for automated reporting workflows | + +### Compliance Exports + +Every triage decision is persisted with a timestamp and LLM justification explaining why the finding was classified as a true positive, false positive, or won't-fix. Export this data as evidence for SOC 2, ISO 27001, or other compliance frameworks. + +Compliance exports include: + +- Finding ID and CWE category +- Triage classification with justification +- Fix outcome (PR merged, closed, pending) +- Timestamps for each state transition + +For custom reporting, use the Pixee API to query triage and remediation data programmatically. See [API Overview](/api/overview) for endpoints and authentication. + +### Enterprise Observability + +Self-hosted Pixee deployments include a bundled observability stack with metrics, logs, traces, and dashboards. Enterprise reporting data feeds into this stack, giving SRE teams visibility into both application-level metrics (triage volume, fix quality) and infrastructure-level metrics (analysis duration, queue depth). + +For full observability configuration, see [Enterprise > Observability](/enterprise/observability). diff --git a/docs/configuration/pixee-yaml.md b/docs/configuration/pixee-yaml.md new file mode 100644 index 00000000..bce403d2 --- /dev/null +++ b/docs/configuration/pixee-yaml.md @@ -0,0 +1,255 @@ +--- +title: PIXEE.yaml Reference +slug: /configuration/pixee-yaml +track: dev +content_type: reference +seo_title: PIXEE.yaml Reference -- Pixee Docs +description: Complete reference for PIXEE.yaml, the per-repository configuration file for controlling Pixee triage, fix, and ignore behavior. +sidebar_position: 2 +--- + +# PIXEE.yaml Reference + +PIXEE.yaml is a configuration file placed in the root of any repository to control Pixee's behavior for that project. It lets developers specify which findings to ignore, which directories to exclude, which fix types to enable or disable, and how PRs should be formatted. The file is version-controlled alongside your code, giving your team full ownership of Pixee's behavior in each repository. + +## File Location and Format + +Place a file named `PIXEE.yaml` in the root of your repository (the same directory as your `README.md` or `.gitignore`). + +- **Format:** YAML (UTF-8 encoding) +- **Required:** No. Pixee works without it. Every setting has a sensible default. +- **Version-controlled:** Changes to PIXEE.yaml are tracked in git history like any other configuration file. +- **SCM support:** PIXEE.yaml is read from the repository root on GitHub, GitLab, Azure DevOps, and Bitbucket. + +## Complete Schema Reference + +Below is the annotated schema showing all available top-level keys. + +```yaml +# PIXEE.yaml — Full annotated reference + +# Exclude paths from analysis +excludes: + paths: + - "tests/**" + - "docs/**" + - "vendor/**" + - "**/generated/**" + +# Ignore specific findings +ignores: + # Suppress by CWE category + cwes: + - "CWE-79" + - "CWE-502" + # Suppress by specific finding ID + finding-ids: + - "pixee:java/secure-random" + +# Control which fix types are active +fixes: + # Enable or disable entire categories + categories: + sast: true + sca: false + # Enable or disable specific codemods + codemods: + - name: "pixee:java/sql-parameterizer" + enabled: true + - name: "pixee:python/secure-flask-cookie" + enabled: false + +# PR formatting preferences +pr: + title-prefix: "[Pixee]" + labels: + - "security" + - "automated-fix" + reviewers: + - "security-team" + draft: false + +# Language-specific overrides +languages: + java: + excludes: + paths: + - "src/legacy/**" + python: + fixes: + codemods: + - name: "pixee:python/url-sandbox" + enabled: false +``` + +### `excludes` + +Controls which files and directories Pixee skips during analysis. + +| Field | Type | Default | Description | +| ---------------- | --------------- | ------------------------- | ----------------------------------------------- | +| `excludes.paths` | list of strings | `[]` (analyze everything) | Glob patterns for files and directories to skip | + +Glob patterns follow standard syntax: `*` matches within a directory, `**` matches across directories, and `?` matches a single character. + +### `ignores` + +Suppresses specific findings without excluding entire paths. + +| Field | Type | Default | Description | +| --------------------- | --------------- | ------- | ------------------------------------------- | +| `ignores.cwes` | list of strings | `[]` | CWE identifiers to suppress across the repo | +| `ignores.finding-ids` | list of strings | `[]` | Specific finding identifiers to suppress | + +Use `cwes` when an entire vulnerability category is not relevant to your project (for example, CWE-79 XSS in a backend-only service). Use `finding-ids` for surgical suppression of individual findings. + +### `fixes` + +Controls which fix types Pixee generates. + +| Field | Type | Default | Description | +| -------------------------- | ------- | ------- | --------------------------- | +| `fixes.categories.sast` | boolean | `true` | Enable SAST-related fixes | +| `fixes.categories.sca` | boolean | `true` | Enable SCA/dependency fixes | +| `fixes.codemods[].name` | string | -- | Codemod identifier | +| `fixes.codemods[].enabled` | boolean | `true` | Whether this codemod runs | + +Disabling a category disables all codemods in that category. Per-codemod settings override category-level settings. + +### `pr` + +Controls how Pixee formats the pull requests it opens. + +| Field | Type | Default | Description | +| ----------------- | --------------- | ------- | --------------------------------------------- | +| `pr.title-prefix` | string | `""` | Prefix prepended to PR titles | +| `pr.labels` | list of strings | `[]` | Labels applied to Pixee PRs | +| `pr.reviewers` | list of strings | `[]` | Reviewers or teams auto-assigned to Pixee PRs | +| `pr.draft` | boolean | `false` | Open PRs as drafts | + +### `languages` + +Applies overrides scoped to a specific language. Any key valid at the top level (`excludes`, `ignores`, `fixes`) can be nested under a language key. + +| Field | Type | Default | Description | +| --------------------------- | ------ | ------------------ | ----------------------------------- | +| `languages..excludes` | object | inherits top-level | Language-scoped path exclusions | +| `languages..fixes` | object | inherits top-level | Language-scoped fix controls | +| `languages..ignores` | object | inherits top-level | Language-scoped finding suppression | + +Supported language keys: `java`, `python`, `javascript`, `typescript`, `csharp`, `go`, `php`. + +## Common Configuration Recipes + +### Exclude test directories + +```yaml +excludes: + paths: + - "tests/**" + - "__tests__/**" + - "**/*_test.go" + - "**/*.test.ts" + - "**/*.spec.js" +``` + +Skip test files where security findings are typically non-exploitable. + +### Ignore a specific CWE across the repo + +```yaml +ignores: + cwes: + - "CWE-79" +``` + +Useful when your project is a backend API with no user-facing HTML, making XSS findings irrelevant. + +### Disable SCA fixes, keep SAST fixes + +```yaml +fixes: + categories: + sast: true + sca: false +``` + +Keep Pixee's SAST remediation active while managing dependency updates through a separate tool (Dependabot, Renovate). + +### Add team labels and reviewers to PRs + +```yaml +pr: + title-prefix: "[Security]" + labels: + - "security" + - "pixee" + - "team-platform" + reviewers: + - "security-team" + draft: true +``` + +Auto-label and assign Pixee PRs for filtering in your PR queue. Opening as drafts gives reviewers a chance to inspect before CI runs. + +### Restrict analysis to specific languages + +```yaml +languages: + java: + fixes: + categories: + sast: true + sca: true + python: + fixes: + categories: + sast: true + sca: false +``` + +Combined with top-level `fixes.categories` set to `false`, this pattern restricts Pixee to specific languages. + +### Suppress a single noisy finding + +```yaml +ignores: + finding-ids: + - "pixee:java/secure-random" +``` + +Surgical suppression when a specific codemod triggers on code that intentionally uses a weaker pattern (for example, non-cryptographic random number generation in test data). + +## Precedence Rules + +1. **PIXEE.yaml overrides organization defaults** for the repository it lives in. If your org default enables SCA fixes but your repo disables them, the repo setting wins. +2. **Organization policies may restrict PIXEE.yaml.** Security teams can configure policies that PIXEE.yaml cannot override, ensuring baseline governance across all repositories. +3. **Language-scoped settings override top-level settings** within that language. A top-level `excludes` applies to all languages unless a language-specific `excludes` is defined. +4. **Invalid PIXEE.yaml falls back to org defaults.** If the file has syntax errors, Pixee ignores it, falls back to organization defaults, and logs a validation warning. No analysis is skipped. + +## Validation and Troubleshooting + +### Validating locally + +PIXEE.yaml is standard YAML. Validate syntax before committing with any YAML linter: + +```bash +# Using yamllint +yamllint PIXEE.yaml + +# Using yq (quick parse check) +yq eval '.' PIXEE.yaml > /dev/null +``` + +### Confirming Pixee loaded your file + +Check the Pixee dashboard for your repository. The configuration status indicates whether PIXEE.yaml was detected and parsed. Pixee also annotates PRs with a note when repository-level configuration is active. + +### Common errors + +| Symptom | Likely Cause | Fix | +| ------------------------------------- | --------------------------------------------------- | --------------------------------------------------------------- | +| PIXEE.yaml ignored, org defaults used | YAML syntax error (bad indentation, missing quotes) | Run `yamllint` and fix reported issues | +| Exclusions not working | Incorrect glob pattern | Test patterns locally; remember `**` matches across directories | +| Codemod still running after disabling | Codemod name typo | Verify the exact codemod identifier in the Pixee dashboard | +| Labels not appearing on PRs | SCM permissions | Ensure the Pixee integration has permission to apply labels | diff --git a/docs/configuration/repositories.md b/docs/configuration/repositories.md new file mode 100644 index 00000000..0fa8101a --- /dev/null +++ b/docs/configuration/repositories.md @@ -0,0 +1,99 @@ +--- +title: Repository Management +slug: /configuration/repositories +track: dev +content_type: guide +seo_title: Repository Management -- Pixee Docs +description: Add, remove, pause, and organize repositories monitored by Pixee across GitHub, GitLab, Azure DevOps, and Bitbucket. +sidebar_position: 3 +--- + +# Repository Management + +Pixee can monitor any repository accessible through your connected SCM platform. Add repositories individually or in bulk, organize them by team or business unit, and control which repos receive Triage Automation, Remediation Automation, or both. Repository management is handled through the Pixee dashboard and works identically across GitHub, GitLab, Azure DevOps, and Bitbucket. + +## Adding Repositories + +### Single repository + +From the Pixee dashboard, select your SCM connection and choose the repository to add. Pixee runs an initial analysis and opens PRs for any findings it can triage or fix. First results typically appear within minutes. + +### Bulk onboarding + +For organizations with dozens or hundreds of repositories, Pixee supports bulk addition. Select multiple repositories from the dashboard or use the API to onboard repositories programmatically. + +### What happens when a repo is added + +1. Pixee scans the repository for connected scanner findings (SARIF imports, native scanner integrations). +2. Triage Automation classifies findings as true positives, false positives, or won't-fix. +3. Remediation Automation generates fixes for actionable findings using deterministic codemods plus AI-powered fixes. +4. PRs appear in your normal SCM workflow for review and merge. + +### Platform-specific notes + +How Pixee discovers repositories depends on the SCM platform: + +| Platform | Discovery Method | Notes | +| ------------ | --------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | +| GitHub | GitHub App installation | Select "All repositories" or specific repos during App install. Auto-discovers new repos if granted org-wide access. | +| GitLab | Personal access token (PAT) | Scopes: `api`, `read_user`, `read_repository`, `read_api`, `write_repository`. Use `member_projects_only` to restrict to explicit-member projects. | +| Azure DevOps | Personal access token (PAT) | Supports webhook configuration and optional work-item linking for orgs with branch policies. | +| Bitbucket | API token | Supports Bitbucket Cloud and Bitbucket Server. | + +## Removing and Pausing Repositories + +### Removing a repository + +Remove a repository from the Pixee dashboard to stop all analysis and PR creation. Existing open PRs remain in your SCM (close them manually or let Pixee clean them up during removal). No Pixee data is retained for removed repositories. + +### Pausing vs. removing + +| Action | Effect | Use when | +| ---------- | --------------------------------------------------- | ---------------------------------------------------------------- | +| **Pause** | Stops analysis temporarily; configuration preserved | Repository is under heavy development, team wants a quiet period | +| **Remove** | Stops analysis permanently; configuration cleared | Repository is decommissioned or no longer in scope | + +Pausing keeps your PIXEE.yaml and dashboard settings intact so you can resume without reconfiguration. + +## Repository Organization + +### Grouping and filtering + +The Pixee dashboard supports organizing repositories by team, business unit, or application. Use filters and search to navigate large repository counts. + +For each repository, the dashboard shows: + +- **Last analysis:** When Pixee last scanned the repo +- **Active PRs:** Open Pixee PRs awaiting review +- **Merge rate:** Percentage of Pixee PRs merged by developers +- **Triage summary:** Breakdown of findings by classification + +### Scaling to many repositories + +Teams with 50+ repositories benefit from grouping. Assign repositories to logical groups that match your organizational structure. This also simplifies notification routing and reporting -- configure alerts at the group level rather than per-repo. + +## Repository-Level Settings + +Each repository inherits organization-wide defaults. Override specific settings in two ways: + +- **PIXEE.yaml** (in-repo): Developers control path exclusions, finding suppressions, fix toggles, and PR formatting. See [PIXEE.yaml Reference](/configuration/pixee-yaml). +- **Dashboard overrides**: Security leads can override scheduling and notification settings per-repository from the Pixee dashboard. + +Settings that can be overridden at the repository level: + +| Setting | PIXEE.yaml | Dashboard | +| -------------------- | ---------- | --------- | +| Path exclusions | Yes | -- | +| Finding suppressions | Yes | -- | +| Fix type toggles | Yes | -- | +| PR formatting | Yes | -- | +| Scan schedule | -- | Yes | +| Notification routing | -- | Yes | + +## Multi-SCM Support + +A single Pixee deployment supports repositories from multiple SCM platforms simultaneously. Connect GitHub, GitLab, Azure DevOps, and Bitbucket to the same Pixee organization and manage all repositories from one dashboard. + +Cross-platform visibility means your security team sees triage results and fix activity across every connected repository, regardless of which SCM hosts it. + +Enterprise self-hosted deployments have the same multi-SCM support. See [Enterprise > Deployment Options](/enterprise/deployment) for infrastructure details. diff --git a/docs/configuration/users.md b/docs/configuration/users.md new file mode 100644 index 00000000..17dfaf1a --- /dev/null +++ b/docs/configuration/users.md @@ -0,0 +1,71 @@ +--- +title: "Users & Access" +slug: /configuration/users +track: dev +content_type: guide +seo_title: "Users & Access -- Pixee Docs" +description: Manage user access, roles, and SSO integration in Pixee. Covers Admin, Security Lead, and Member roles. +sidebar_position: 6 +--- + +# Users & Access + +Pixee supports role-based access that aligns with how security and development teams already work. Security leads configure organization-wide policies and view triage results across all repositories. Developers interact with Pixee through PRs in their normal SCM workflow and can customize behavior per-repository via PIXEE.yaml. Enterprise deployments integrate with your corporate identity provider for SSO. + +## Access Model Overview + +Pixee has two interaction surfaces, each serving a different audience: + +**SCM workflow (developers).** Developers never need a Pixee login for day-to-day use. Pixee delivers fixes as standard pull requests in GitHub, GitLab, Azure DevOps, or Bitbucket. Developers review and merge them using their existing tools, the same way they handle any other PR. Triage context is embedded in the PR description. + +**Pixee dashboard (security team).** Security leads and admins use the Pixee dashboard to configure organization-wide policies, review triage results across all repositories, manage user access, and view reporting. The dashboard is where governance happens. + +This separation means Pixee adds no new tools to developer workflows. Developers see PRs in their existing SCM. Security teams get a centralized policy and reporting surface. + +## Roles and Permissions + +Pixee uses three roles to control dashboard access: + +| Role | Capabilities | +| ----------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Admin** | Full configuration access. Manage users, set organization policies, configure SCM connections, adjust AI settings, and view all repositories and reports. | +| **Security Lead** | View all repositories and triage results. Configure policies and notification routing. Cannot manage users or SCM connections. | +| **Member** | View assigned repositories and their triage results. Interact with PRs in the SCM. Configure per-repository behavior via PIXEE.yaml. | + +**How roles map to SCM permissions:** Pixee respects your SCM's access model. A developer who has write access to a repository in GitHub can merge Pixee PRs for that repository. Pixee dashboard roles control what users can do in the Pixee interface, not what they can do in the SCM. + +**Principle of least privilege:** Assign the Admin role only to the team member responsible for Pixee administration. Use Security Lead for team members who need cross-repo visibility. Use Member for everyone else -- they interact with Pixee through PRs, not the dashboard. + +## Inviting and Managing Users + +### Adding team members + +Invite users from the Pixee dashboard. Enter their email address and assign a role. The invited user receives an email with a link to set up their account. + +### Managing existing users + +From the dashboard, admins can: + +- Change a user's role +- Revoke access (removes dashboard access immediately) +- View last login and activity + +### Access revocation + +When a user is removed from Pixee, their dashboard access is revoked immediately. Their SCM access is unaffected -- SCM permissions are managed by your SCM platform, not by Pixee. + +## SSO and Identity Provider Integration + +Pixee integrates with corporate identity providers for single sign-on: + +| Provider | Integration | +| ---------------------- | -------------------------------- | +| **Google Workspace** | Direct login via Google OAuth | +| **Microsoft Entra ID** | Direct login via Microsoft OAuth | +| **Okta** | Direct login via Okta OIDC | + +SSO maps your identity provider's user accounts to Pixee roles. When a user authenticates through SSO, their Pixee role is determined by role mapping configured in the dashboard. + +Enterprise self-hosted deployments also support embedded OIDC (via Authentik running in-cluster), which federates to your upstream corporate identity provider. This means SSO works even when Pixee runs inside your infrastructure with no external IdP dependency. + +For full SSO configuration details on self-hosted deployments, see [Enterprise > Security Architecture](/enterprise/security-architecture). diff --git a/docs/enterprise/_category_.json b/docs/enterprise/_category_.json new file mode 100644 index 00000000..4164d936 --- /dev/null +++ b/docs/enterprise/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Enterprise", + "position": 6, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "enterprise/enterprise-overview" + } +} diff --git a/docs/enterprise/byom.md b/docs/enterprise/byom.md new file mode 100644 index 00000000..12e2509a --- /dev/null +++ b/docs/enterprise/byom.md @@ -0,0 +1,94 @@ +--- +title: Bring Your Own Model +slug: /enterprise/byom +track: leader +content_type: guide +seo_title: Bring Your Own Model - Choose Your LLM Provider for Pixee +description: Configure Pixee with your preferred LLM provider. Supports OpenAI, Anthropic, Azure AI Foundry, AWS Bedrock, Google Vertex AI, and more with hierarchical model routing. +sidebar_position: 8 +--- + +Pixee lets you choose your LLM provider instead of locking you into a single vendor. You own the API keys, pick the vendor, and control the bill. This is the opposite of a black-box AI product. + +## Supported Providers + +| Provider | Description | +| ---------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | +| **OpenAI** | Direct OpenAI API | +| **Anthropic** | Direct Anthropic API with Anthropic-optimized prompts | +| **Azure AI Foundry** | Azure-hosted models in customer's Azure tenant (OpenAI and Anthropic models available) | +| **AWS Bedrock** | AWS-hosted model marketplace in customer's AWS account | +| **Google Cloud Vertex AI** | Google Cloud-hosted model platform | +| **Oracle Cloud OCI Generative AI** | Oracle Cloud-hosted generative AI service | +| **Any OpenAI-compatible endpoint** | Self-hosted, private, or custom API gateway — covers air-gapped deployments, self-hosted models, and enterprise API gateways | + +**Custom endpoint support** allows routing through enterprise API gateways. Custom header name/value pairs handle gateway authentication, so Pixee fits into your existing API management infrastructure. + +**Provider-aware prompting:** Pixee optimizes prompts for each provider rather than using a one-size-fits-all approach. This matters for triage accuracy and fix quality. + +## Supported Model Families + +Each provider platform gives access to a broad and evolving set of model families. The list below is indicative — model availability expands continuously across platforms. + +- **OpenAI models** — available via OpenAI and Azure AI Foundry +- **Anthropic Claude models** — available via Anthropic, AWS Bedrock, and Azure AI Foundry +- **Google Gemini models** — available via Google Cloud Vertex AI +- **Meta Llama models** — available via AWS Bedrock and self-hosted endpoints +- **Mistral models** — available via AWS Bedrock, Azure AI Foundry, and self-hosted endpoints +- **Amazon Nova models** — available via AWS Bedrock +- **Any model behind an OpenAI-compatible API** — self-hosted or custom + +Model versions evolve rapidly. Pixee provides a current recommendation for each customer based on benchmarks across quality, speed, and cost. See [Model Recommendations](#model-recommendations) below. + +## Model Recommendations + +Pixee benchmarks model performance for security triage and fix generation tasks across quality, speed, and cost dimensions. The right model configuration depends on your cloud platform, compliance constraints, data residency requirements, and cost targets — there is no single best answer. + +Based on your available cloud platforms and constraints, Pixee provides a recommended model configuration for your deployment. Contact your account team or [reach out here](https://pixee.ai/demo) for a model recommendation tailored to your environment. + +## Hierarchical Model Routing + +Pixee uses hierarchical routing to assign the right model capability to each task type — triage classification, deep reasoning, fix generation, and dependency analysis each have different requirements. You can assign different models to different task categories, letting you optimize for cost, latency, and quality independently. + +**Cost optimization.** Route straightforward classifications to faster, cheaper models. Reserve high-capability models for complex decisions that justify the cost. + +**Quality optimization.** Each task type gets a model matched to its requirements — not a single model handling everything. + +**Latency control.** Speed-sensitive tasks use low-latency models. Quality-sensitive tasks use higher-capability models regardless of latency. + +Contact your account team for guidance on model-to-task assignment for your deployment. + +## Configuration + +**During installation:** Select your LLM provider through the admin console (embedded cluster) or Helm values (BYO Kubernetes). Provide the API key and endpoint URL. + +**Per-task model configuration:** After initial setup, assign specific models to each task category based on your cost, quality, and latency requirements. + +**Preflight checks:** Every provider configuration is validated at install time. Preflight checks catch LLM misconfiguration immediately -- not when your first analysis runs and fails. This is a small detail that saves hours of debugging. + +**Switching providers:** LLM provider configuration can be changed after initial deployment through the admin console or Helm values update. No data migration or reprocessing is required. + +## Governance Controls + +:::info +Bring Your Own Model is not just a technical feature — it is a governance feature. You own the API keys, control which model handles your code, and see all LLM costs on your own cloud bill. +::: + +| Control | Detail | +| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------- | +| **Key ownership** | Customer owns all API keys. Pixee never stores or accesses customer LLM credentials. | +| **Traffic routing** | All LLM traffic routes through the customer's account. Pixee does not proxy LLM calls for self-hosted deployments. | +| **Cost visibility** | LLM usage appears on the customer's standard cloud billing. No hidden costs or Pixee-side LLM charges for self-hosted deployments. | +| **Audit trail** | Every triage decision includes the LLM justification. Auditors can see what the model was asked and what it answered. | + +For full data flow details and credential handling, see [Security Architecture](/enterprise/security-architecture). + +## LLM Resilience + +When an LLM provider is unavailable, Pixee handles the degradation: + +- **Task queuing.** Analysis tasks are queued and retried automatically when the provider becomes available. No manual intervention is needed. +- **Deterministic codemods continue.** Deterministic codemods that require no LLM involvement function regardless of LLM availability. A provider outage does not stop all remediation -- it stops AI-powered remediation only. +- **Existing results are unaffected.** Triage decisions and PRs that have already been delivered are not affected by provider unavailability. Historical data persists independently. + +This resilience architecture means an LLM outage degrades Pixee's capability without halting it entirely. diff --git a/docs/enterprise/compliance.md b/docs/enterprise/compliance.md new file mode 100644 index 00000000..29ac94f6 --- /dev/null +++ b/docs/enterprise/compliance.md @@ -0,0 +1,87 @@ +--- +title: Compliance +slug: /enterprise/compliance +track: leader +content_type: conceptual +seo_title: Compliance - SOC 2, HIPAA, FedRAMP, PCI-DSS, and NIST 800-53 Mapping +description: Pixee compliance mapping for SOC 2, HIPAA, FedRAMP, PCI-DSS, NIST 800-53, and ISO 27001. Covers audit evidence, data residency, and AI governance. +sidebar_position: 6 +--- + +Pixee supports compliance requirements by providing audit-ready evidence for every triage decision and remediation action. Every finding classification includes a timestamped, reasoned record with LLM justification. Every fix is delivered as a traceable pull request with full diff visibility. This page maps Pixee capabilities to SOC 2, HIPAA, FedRAMP, PCI-DSS, NIST 800-53, and ISO 27001 control requirements. + +## How Pixee Supports Compliance + +Pixee's compliance value rests on four architectural properties: + +**Audit trail.** Every triage decision is persisted with a timestamp, the classification outcome (true positive, false positive, won't fix), and the LLM justification that produced the verdict. This record exists for the lifetime of the deployment and is backfilled for findings analyzed before the audit feature was added. + +**Traceability.** Every fix is a Git commit within a pull request. The PR includes the proposed diff, quality scores (safety, effectiveness, cleanliness), the vulnerability that triggered the fix, and the merge status. Standard Git history provides the full chain from finding to resolution. + +**No bypass.** The PR-only workflow is an architectural constraint, not an optional setting. All changes go through your existing code review, CI/CD pipelines, and branch protection rules. Pixee adds validation layers before your existing gates -- it does not bypass them. + +**Compliance acceleration.** Automated triage and remediation help organizations meet contractual timeframes for critical and high-severity findings. Banking and healthcare teams with two-month remediation windows have reported that automation changes the math from "physically impossible" to "consistently achievable." + +## Framework Mapping + +The table below maps Pixee capabilities to specific controls in six compliance frameworks. Pixee describes how its capabilities align with these controls -- not claims of formal certification unless explicitly stated. + +| Framework | Relevant Controls | How Pixee Supports | +| ---------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **SOC 2 Type II** | CC6.1 (logical access controls), CC7.1 (system monitoring), CC8.1 (change management) | Audit-ready triage records with timestamped justification. PR-based change tracking for every remediation. Role-based access via SSO (Google, Microsoft Entra ID, Okta). Every disposition persisted for control sampling. | +| **HIPAA** | 164.312(a)(1) access control, 164.312(c)(1) integrity controls, 164.312(d) authentication | Self-hosted deployment keeps PHI-adjacent data in customer network. SSO integration. Audit trail for all triage and remediation actions. PR workflow preserves change integrity. | +| **FedRAMP** | AC-2 (account management), AU-2 (auditable events), CM-3 (configuration change control) | Air-gapped deployment with no source code leaving the network. Comprehensive audit event logging. Configuration changes documented through PR workflow. | +| **PCI-DSS** | 6.3 (secure development), 6.5 (common vulnerability remediation), 10.2 (audit trails) | Automated vulnerability remediation with full audit evidence. Triage decisions provide evidence for vulnerability management requirements. PR history for change documentation. | +| **NIST 800-53** | RA-5 (vulnerability monitoring and scanning), SA-11 (developer testing), SI-2 (flaw remediation) | Automated triage with classification evidence. Remediation with traceable fixes. Continuous monitoring via native scanner integrations and triage automation. | +| **ISO 27001** | A.12.6.1 (management of technical vulnerabilities), A.14.2.2 (system change control) | Vulnerability management automation with audit evidence. Change control integration through PR workflow. Exportable records for audit review. | +| **OCC 2013-29** (Third-Party Risk) | Third-party risk management, vendor due diligence, ongoing monitoring | Pixee supports vendor risk assessment via documented security controls, data classification, and audit trail. Self-hosted deployment keeps all data within customer network. | +| **FFIEC IT Examination Handbook** | Outsourced Technology Services examination procedures | Audit trail for vulnerability management lifecycle maps to examination procedures. Event-sourced triage decisions provide examiner-ready evidence. | +| **NYDFS 23 NYCRR 500** | 500.5 (vulnerability assessment), 500.6 (audit trail), 500.7 (access controls), 500.15 (data encryption), 500.17 (incident response and notification) | Cybersecurity requirements addressed via: access controls (500.7), audit trail (500.6), vulnerability assessment (500.5), and data encryption (500.15). Incident response (500.17) and notification handled via customer's existing IR process with Pixee audit data as evidence input. | + +**SOC 2 receives the most detailed treatment** because it is the most frequently requested framework in enterprise evaluation. SOC 2 control sampling relies on evidence that every change is authorized, reviewed, and documented -- properties that Pixee's PR workflow provides by architectural design. + +For the current status of Pixee's own SOC 2 certification, contact the Pixee team. + +## Audit Evidence + +Pixee generates and persists the following evidence for every analysis: + +| Evidence Type | What It Contains | Export Format | +| ----------------------- | ------------------------------------------------------------------------------------- | ------------------- | +| **Triage records** | Classification (TP/FP/won't fix), LLM justification, timestamp, finding metadata | CSV, JSON, API | +| **Fix evidence** | PR link, full diff, quality scores (safety, effectiveness, cleanliness), merge status | CSV, JSON, API | +| **Activity feed** | Event-sourced analysis history with outcome banners | API (SSE streaming) | +| **Historical backfill** | Activity persistence backfilled for findings analyzed before audit features | Automatic | + +Evidence is exportable via the reporting API in CSV and JSON formats for integration with compliance platforms and GRC tools. The API supports automated evidence collection workflows -- your compliance team does not need to manually extract data from the Pixee UI. + +## Data Residency and Data Handling + +Compliance-driven organizations frequently ask where data lives. The answer depends on your deployment model: + +| Deployment Model | Data Residency | LLM Data Handling | +| -------------------- | ------------------------------------------------------------------------------------------------ | --------------------------------------------------- | +| **Dedicated SaaS** | Pixee cloud — dedicated, single-tenant environment per customer (see Pixee data handling policy) | Pixee-managed LLM providers | +| **Embedded Cluster** | Customer network | Customer's LLM provider in customer's chosen region | +| **Helm / BYO K8s** | Customer network | Customer's LLM provider in customer's chosen region | +| **Air-Gapped** | Customer network (isolated) | Customer's private LLM endpoint | + +For self-hosted deployments, source code and scanner findings stay in the customer's network. LLM inference uses the customer's chosen provider in the customer's chosen region. The only outbound connection is license validation, which can be proxied. + +**Banking teams** with data residency requirements: self-hosted deployment keeps all analysis data within your network perimeter. **Healthcare teams** with HIPAA requirements: the same applies, with the additional benefit of audit-ready evidence for vulnerability management controls. **Federal teams** with FedRAMP requirements: air-gapped deployment provides the strictest data isolation. See [Air-Gapped Deployment](/enterprise/air-gap) for capabilities and limitations. + +For full data flow details, see [Security Architecture](/enterprise/security-architecture). + +## Responsible AI Governance + +For organizations with AI governance committees or Responsible AI councils: + +The architecture provides verifiable answers to common governance questions: + +- **Multiple documented validation layers** -- constrained generation, independent evaluation, PR review, CI/CD testing, SAST re-scanning +- **Human-in-the-loop** -- PR-only workflow is an architectural constraint, not a configuration option +- **No bypass of existing governance gates** -- Pixee adds layers before your existing review process +- **Narrow scope** -- security fixes only (1-5 lines applying OWASP/SANS patterns), not general-purpose code generation +- **Deterministic floor** -- deterministic codemods use zero LLM involvement with zero hallucination risk (see [Codemodder](/open-source/codemodder) for the full catalog) + +For the full technical trust framework, see [Security & Trust](/platform/security). diff --git a/docs/enterprise/deployment/_category_.json b/docs/enterprise/deployment/_category_.json new file mode 100644 index 00000000..aaa5f769 --- /dev/null +++ b/docs/enterprise/deployment/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Deployment Options", + "position": 2, + "collapsible": true, + "collapsed": true, + "link": { + "type": "doc", + "id": "enterprise/deployment/deployment-overview" + } +} diff --git a/docs/enterprise/deployment/air-gap.md b/docs/enterprise/deployment/air-gap.md new file mode 100644 index 00000000..8a491488 --- /dev/null +++ b/docs/enterprise/deployment/air-gap.md @@ -0,0 +1,89 @@ +--- +title: Air-Gapped Deployment +slug: /enterprise/air-gap +track: leader +content_type: guide +seo_title: Air-Gapped Deployment - Run Pixee Without Internet Access +description: Deploy Pixee in air-gapped environments with private LLM endpoints. Covers capabilities, requirements, and known limitations for disconnected deployments. +sidebar_position: 5 +--- + +Pixee supports air-gapped deployment for regulated and classified environments that cannot call public AI APIs. Source code and findings never leave your network. LLM inference runs against a customer-hosted private endpoint (Azure AI Foundry, Azure Anthropic, or any OpenAI-compatible gateway). This page covers what works, what is required, and what limitations exist in disconnected environments. + +## What "Air-Gapped" Means for Pixee + +In Pixee's air-gapped deployment: + +- **Source code** never traverses the public internet +- **Scanner findings** stay within your network +- **LLM requests** route to a customer-hosted private endpoint +- **Fixes** are delivered as PRs to your internal SCM + +The same Pixee platform, the same Helm chart, and the same upgrade path apply as in connected deployments. Air-gapped mode changes where LLM inference runs and how network traffic flows -- not what the product does. + +:::warning[Not fully zero-internet] +"Air-gapped" in this context means LLM inference is private and code stays internal. License validation still requires a network path to Pixee servers — either direct or through a proxy. If your policy prohibits all outbound connections without exception, read [Known Limitations](#known-limitations) below and contact Pixee solutions engineering before proceeding. +::: + +## Supported Private LLM Endpoints + +| Provider | Description | Notes | +| --------------------------------- | --------------------------------------------------- | ---------------------------------------------------------- | +| **Azure AI Foundry** | Azure-hosted models in customer's Azure tenant | Customer-owned keys, runs in customer's Azure subscription | +| **Azure Anthropic** | Anthropic models via Azure marketplace | Customer-owned keys, Azure-hosted | +| **OpenAI-compatible gateway** | Self-hosted endpoint exposing OpenAI-compatible API | Custom header auth supported for enterprise gateways | +| **Anthropic via private network** | Direct Anthropic API over private path | Requires network path to Anthropic from within the cluster | + +All providers support custom endpoint URLs and custom header name/value pairs for enterprise gateway authentication. Per-provider preflight checks validate LLM connectivity at install time, catching misconfiguration before your first analysis runs. + +## Requirements + +| Requirement | Specification | +| ---------------------- | ----------------------------------------------------------------------- | +| **Kubernetes** | Same as Helm deployment -- EKS, GKE, AKS, or self-managed | +| **LLM endpoint** | Customer-hosted, accessible from the Pixee namespace within the cluster | +| **Network** | Proxy support (`httpProxy`, `httpsProxy`, `noProxy`) | +| **TLS** | CA cert injection for TLS-intercepting proxies | +| **License validation** | Outbound path to Pixee license server (direct or proxied) | + +Infrastructure requirements (CPU, RAM, storage) match the [Helm / BYO Kubernetes](/enterprise/helm) deployment. + +## Known Limitations + +This section is direct about what air-gapped deployment does not support. Discovering a limitation during a proof of concept that was not disclosed in documentation wastes everyone's time. + +**License validation requires a network path.** Pixee cannot operate in a truly zero-internet-connectivity environment. License validation must reach Pixee servers, either directly or through a proxy. If your security policy prohibits all outbound connections, contact Pixee solutions engineering before proceeding. There is no offline license mode. + +**LLM quality depends on the private endpoint.** The quality of triage decisions and remediation fixes depends on the LLM model available at the private endpoint. If the private model is equivalent to production defaults, triage and fix quality will be identical. Models with lower capability may produce lower merge rates and less accurate triage classifications. + +**Model updates require manual intervention.** In connected deployments, Pixee can leverage updated model configurations automatically. In air-gapped environments, model upgrades require manual endpoint configuration changes and testing. + +**Web search and external research features are unavailable.** LLM tiers that depend on internet access (web search, deep research) do not function in air-gapped deployments. Triage and remediation that rely on code analysis continue to work. The affected capabilities are research-augmented features, not core triage and remediation. + +**Initial deployment takes longer.** Expect additional time for image loading into the local container registry, private endpoint configuration, network verification, and proxy setup compared to connected deployments. + +**Deterministic codemods are unaffected.** Deterministic codemods that require no LLM involvement function identically in air-gapped environments. These fixes carry zero dependency on any LLM endpoint. + +## Proxy and TLS Configuration + +Air-gapped environments frequently involve proxy servers and TLS-intercepting proxies. Pixee supports both. + +**Proxy configuration:** Set `httpProxy`, `httpsProxy`, and `noProxy` in Helm values. Per-provider endpoint overrides are available if different LLM providers require different proxy paths. + +**TLS-intercepting proxy support:** If your network uses a TLS-intercepting proxy, inject your CA certificate so Pixee can establish trust with internal endpoints. This is configured during installation. + +**Verification:** After configuration, validate that the Pixee platform can reach the LLM endpoint and the license server through the proxy. Preflight checks cover LLM connectivity. License validation can be verified from the admin console. + +## Industry Context + +Air-gapped deployments serve specific regulatory environments: + +- **Federal and defense** -- Classified environments where source code cannot traverse public networks. Government customer approval processes require documented data flow before deployment. +- **Financial services** -- Banking regulators require strict data controls. Air-gapped deployment with Azure AI Foundry in the customer's Azure tenant satisfies data residency requirements while enabling AI-powered triage and remediation. +- **Healthcare** -- HIPAA requirements for protected health information (PHI) proximity. Self-hosted deployment with private LLM endpoints keeps all analysis within the healthcare organization's network boundary. + +All three contexts share the same technical deployment. The difference is in the LLM provider choice and network topology. + +## Installation + +Air-gapped installation follows the same Helm deployment process with additional configuration for container image transfer to a local registry, private LLM endpoint settings, proxy configuration, and CA certificates. Preflight checks validate LLM endpoint connectivity and license server access before the first analysis runs. For the current installation procedure and common issues, see the [deployment guide](https://app.pixee.ai/docs/deploy) and [Enterprise Troubleshooting](/enterprise/troubleshooting). diff --git a/docs/enterprise/deployment/deployment-overview.md b/docs/enterprise/deployment/deployment-overview.md new file mode 100644 index 00000000..dd3ffb9f --- /dev/null +++ b/docs/enterprise/deployment/deployment-overview.md @@ -0,0 +1,140 @@ +--- +title: Deployment Options +slug: /enterprise/deployment +track: leader +content_type: guide +seo_title: Deployment Options - SaaS, Self-Hosted, and Air-Gapped Security Automation +description: "Compare Pixee deployment models: Dedicated SaaS, embedded cluster, Helm/BYO Kubernetes, and air-gapped. Includes data flow tables and infrastructure requirements." +sidebar_position: 1 +--- + +Pixee offers four deployment models: Dedicated SaaS, a turnkey embedded cluster for organizations without Kubernetes, a standard Helm chart for existing EKS/GKE/AKS clusters, and a fully air-gapped deployment with private LLM endpoints. Every model delivers the same triage and remediation engine. The only difference is where the infrastructure runs and how data flows through your network. + +This page provides architecture descriptions, data flow tables, and infrastructure requirements for each model. Security teams reviewing Pixee for enterprise deployment should start here. + +## Deployment Model Comparison + +### Dedicated SaaS Architecture + +Pixee manages all infrastructure. The customer installs a GitHub App, GitLab PAT, Azure DevOps PAT, or Bitbucket API token. Source code access flows through the SCM integration. Analysis, triage, and LLM inference run on Pixee-managed infrastructure. Fixes are delivered as pull requests back to the customer's SCM. + +**Single-tenant.** Each customer is provisioned into a dedicated, isolated environment — your code, findings, triage decisions, and LLM inference requests are never co-mingled with another organization's data. + +**Component layout:** Pixee platform (Pixee-managed cloud) connects to customer SCM via API. LLM inference runs on Pixee-managed providers. All processing happens outside the customer network. Results return as PRs through the SCM API. + +### Embedded Cluster Architecture + +A single Linux VM hosts the complete Pixee platform as a turnkey appliance. The installer provisions K3s (current stable Kubernetes), storage, authentication, and observability automatically. The KOTS admin console provides a form-based UI for configuration. No Kubernetes expertise is required. + +**Component layout:** Customer VM runs Pixee platform, analysis service, and user platform. LLM inference routes to the customer's chosen provider (OpenAI, Azure AI Foundry, Anthropic, or Azure Anthropic) from within the customer network. SCM integration connects to internal or cloud-hosted SCM. Admin console runs on port 30000. + +### Helm / BYO Kubernetes Architecture + +The Pixee Helm chart deploys into an existing customer-managed Kubernetes cluster. Conditional subcharts let platform engineering teams swap embedded components for their own services -- BYO database, object store, observability, and identity provider. + +**Component layout:** Customer Kubernetes cluster (EKS, GKE, AKS, or self-managed) runs Pixee platform, analysis service, and user platform as pods. Embedded subcharts (SeaweedFS, CloudNativePG, VictoriaMetrics, Grafana, Authentik) are each independently replaceable. LLM inference routes to the customer's provider. SCM integration connects via the cluster's network. + +### Air-Gapped Architecture + +The same Helm chart deploys into a disconnected environment. LLM inference runs against a customer-hosted private endpoint. Source code and findings never traverse the public internet. + +**Component layout:** Customer Kubernetes cluster in an isolated network runs the full Pixee stack. LLM inference routes to a private endpoint (Azure AI Foundry, Azure Anthropic, or OpenAI-compatible gateway) within the customer's network boundary. The only outbound connection is license validation, which can be proxied. SCM integration connects to the internal SCM instance. + +| Model | Infrastructure | LLM | Data Residency | K8s Required | Best For | +| -------------------- | -------------- | --------------- | --------------------------- | ---------------- | --------------------------------- | +| **Dedicated SaaS** | Pixee-managed | Pixee-managed | Pixee cloud (single-tenant) | No | Zero-infra teams | +| **Embedded Cluster** | Customer VM | Customer-chosen | Customer network | No (K3s bundled) | No-K8s orgs, regulated industries | +| **Helm / BYO K8s** | Customer K8s | Customer-chosen | Customer network | Yes | Platform-engineering teams | +| **Air-Gapped** | Customer K8s | Customer-hosted | Air-gapped network | Yes | Federal, finance, healthcare | + +## Data Flow by Deployment Model + +This table answers the question security teams ask first: "What data leaves my network?" + +| Data Type | Dedicated SaaS | Embedded Cluster | Helm / BYO K8s | Air-Gapped | +| ------------------------ | ------------------- | ------------------------- | ------------------------- | ---------------------------- | +| Source code snippets | Sent to Pixee cloud | Stays in customer network | Stays in customer network | Stays in customer network | +| Scanner findings (SARIF) | Sent to Pixee cloud | Stays in customer network | Stays in customer network | Stays in customer network | +| LLM inference requests | Pixee-managed | Customer's LLM provider | Customer's LLM provider | Customer's private endpoint | +| PR/MR content | Via SCM API | Via SCM API (internal) | Via SCM API (internal) | Via SCM API (internal) | +| License validation | Pixee cloud | Pixee cloud (or proxy) | Pixee cloud (or proxy) | Pixee cloud (proxy required) | +| Telemetry (opt-in) | Pixee cloud | Pixee cloud (toggleable) | Pixee cloud (toggleable) | Blocked | + +**Key takeaway for self-hosted models:** Source code, scanner findings, and LLM requests stay in your network. The only outbound connection is license validation, which supports proxy configuration. + +## Infrastructure Requirements + +| Requirement | Embedded Cluster | Helm / BYO K8s | +| -------------------- | ----------------------------------------------------------- | ----------------------------------------------------- | +| **Compute** | 8 vCPU, 32 GB RAM | 8+ vCPU, 32+ GB RAM | +| **Storage** | 100 GB+ SSD/NVMe (under 10 ms write latency) | 100 GB+ SSD/NVMe | +| **Operating system** | Ubuntu 24.04+ (recommended), RHEL 9, Rocky Linux, AlmaLinux | N/A (Kubernetes cluster) | +| **Kubernetes** | K3s bundled (current stable) | EKS, GKE, AKS, or self-managed | +| **Helm CLI** | N/A | Current stable version | +| **Network** | Port 443 (HTTPS), Port 30000 (admin console) | Port 443 (HTTPS) | +| **Internet** | Required for initial install; proxy support available | Required for initial install; proxy support available | + +## Multi-Tenancy and Business Unit Isolation + +A single Pixee deployment supports multiple SCM organizations simultaneously. Repository-level access controls restrict which users can view and act on which repositories, providing organizational boundaries within a shared deployment. + +**Role-based access control.** Three roles -- Admin, Security Lead, and Member -- provide access granularity within a deployment. Admins manage configuration and user access. Security Leads oversee triage decisions and fix policies. Members interact with PRs in their assigned repositories. + +**Regulatory data isolation.** For business units with strict data separation requirements -- such as investment banking and consumer banking divisions, or units subject to different regulatory regimes -- separate Pixee deployments are recommended. Separate deployments ensure that code, findings, triage decisions, and LLM inference requests from one business unit never share infrastructure with another. + +Contact Pixee solutions engineering for guidance on multi-deployment architectures for regulated environments. + +## Network Connections by Deployment Model + +For security teams conducting network reviews, this table maps every external connection Pixee requires. + +| Connection | Purpose | Dedicated SaaS | Embedded Cluster | Helm / BYO K8s | Air-Gapped | +| ----------------------------- | ----------------------------- | -------------- | ------------------- | ------------------- | ---------------- | +| SCM webhooks (inbound 443) | Repository events | Pixee cloud | Customer network | Customer network | Customer network | +| LLM endpoint (outbound) | AI inference | Pixee-managed | Customer's provider | Customer's provider | Private endpoint | +| License server (outbound) | License validation | Pixee cloud | Direct or proxy | Direct or proxy | Proxy required | +| Telemetry (outbound, opt-in) | Usage metrics | Pixee cloud | Toggleable | Toggleable | Blocked | +| Container registry (outbound) | Image pulls (install/upgrade) | N/A | Required | Required | Pre-loaded | + +No other outbound connections are required. Self-hosted deployments require no inbound connections except SCM webhooks on port 443. + +## Choosing a Deployment Model + +Use this decision tree to narrow down your model: + +1. **Can you manage Kubernetes?** + - Yes -- [Helm / BYO Kubernetes](/enterprise/helm) + - No -- [Embedded Cluster](/enterprise/embedded-cluster) + +2. **Do you require air-gapped deployment?** + - Yes -- [Air-Gapped Deployment](/enterprise/air-gap) + - No -- continue + +3. **Do you want zero infrastructure management?** + - Yes -- Dedicated SaaS + - No -- embedded cluster or Helm (based on step 1) + +4. **Do you have regulatory data residency requirements?** + - Banking or healthcare with strict data residency -- embedded cluster or air-gapped + - Federal or classified environments -- air-gapped + - Standard enterprise -- any self-hosted model based on your Kubernetes posture + +## Security Review Summary + +**Data classification:** Pixee analyzes vulnerability-relevant code snippets -- not entire repositories. No absolute paths, repository URLs, git metadata, commit hashes, or author information are sent to LLM inference. Scanner findings (SARIF data) stay within the deployment boundary for all self-hosted models. + +**Network requirements:** Self-hosted deployments require outbound access for license validation only (proxyable). LLM inference routes to the customer's chosen provider within the customer's network. No inbound connections are required except SCM webhooks on port 443. + +**Credential management:** SCM tokens (GitHub App private key, GitLab PAT, Azure DevOps PAT, Bitbucket API token) and LLM API keys are stored in Kubernetes secrets. External secret manager integration (Vault, External Secrets Operator, SOPS) is supported via `existingSecret` references. No credentials are stored in Helm values. + +**For the full security review:** See [Security Architecture](/enterprise/security-architecture) for data flow diagrams, access control details, AI governance controls, and credential handling specifics. + +## Sizing Guidance + +| Deployment Size | Repositories | Recommended Resources | Deployment Model | +| --------------- | ------------ | ---------------------------------- | --------------------------- | +| Small | Up to 50 | 8 vCPU, 32 GB RAM, 100 GB SSD | Embedded Cluster | +| Medium | 50-500 | 16 vCPU, 64 GB RAM, 250 GB SSD | Helm / BYO K8s | +| Large | 500+ | 32+ vCPU, 128+ GB RAM, 500+ GB SSD | Helm / BYO K8s (multi-node) | + +These are starting recommendations. Actual resource requirements depend on finding volume, concurrent analysis workload, and LLM inference latency. Contact Pixee solutions engineering for sizing guidance on large deployments. diff --git a/docs/enterprise/deployment/embedded-cluster.md b/docs/enterprise/deployment/embedded-cluster.md new file mode 100644 index 00000000..4be55186 --- /dev/null +++ b/docs/enterprise/deployment/embedded-cluster.md @@ -0,0 +1,99 @@ +--- +title: Embedded Cluster +slug: /enterprise/embedded-cluster +track: leader +content_type: guide +seo_title: Embedded Cluster - Deploy Pixee on a Single VM Without Kubernetes Expertise +description: Deploy Pixee Enterprise as a turnkey appliance on a single Linux VM. K3s-based with KOTS admin console. No Kubernetes expertise required. +sidebar_position: 3 +--- + +The embedded cluster deployment installs the full Pixee platform -- Kubernetes runtime, storage, authentication, and observability -- as a turnkey single-tenant appliance on a single Linux VM. No Kubernetes expertise is needed. A single command installs K3s, the Pixee platform, and a form-based admin console for day-two operations. This is the fastest path to self-hosted Pixee for organizations without existing Kubernetes infrastructure. + +## Who This Is For + +The embedded cluster is built for organizations that need self-hosted deployment but do not have (or do not want to use) existing Kubernetes infrastructure: + +- **Regulated industries** (finance, healthcare, public sector) requiring dedicated-tenant deployment inside the customer perimeter +- **Teams without Kubernetes engineers** that still need self-hosted security automation +- **Evaluation environments** where standing up a full Kubernetes cluster is not justified for a proof of concept + +Most AI-assisted AppSec tools are cloud-only SaaS. The embedded cluster delivers the same triage and remediation engine as the cloud offering, running entirely within your network, without requiring platform engineering expertise. + +## Prerequisites + +Verify these requirements with your infrastructure team before installation. + +| Requirement | Specification | +| -------------------- | ----------------------------------------------------------- | +| **Operating system** | Ubuntu 24.04+ (recommended), RHEL 9, Rocky Linux, AlmaLinux | +| **CPU** | 8 vCPU minimum | +| **RAM** | 32 GB minimum | +| **Storage** | 100 GB+ SSD/NVMe, under 10 ms write latency | +| **Network** | Port 443 (HTTPS), Port 30000 (admin console) | +| **Internet** | Required for initial install; proxy support available | + +The VM can run on any infrastructure: physical servers, VMware, Hyper-V, cloud VMs (EC2, Azure VMs, GCE), or any other virtualization platform. + +**Storage performance matters.** The 10 ms write latency requirement is not optional. Pixee persists triage decisions, fix metadata, and analysis state to disk. Slow storage causes analysis timeouts and degraded platform performance. Use SSD or NVMe -- not spinning disk or network-attached storage with high latency. + +**Proxy environments.** If your VM accesses the internet through a proxy, proxy configuration is supported during installation. TLS-intercepting proxies are also supported via CA cert injection. + +## Installation + +The embedded cluster installs with a single command on a Linux VM meeting the prerequisites above. The installer provisions K3s (current stable Kubernetes), deploys the Pixee platform, and starts a KOTS-powered admin console on port 30000. The admin console provides a form-based UI for all configuration -- domain, TLS, authentication, LLM provider, and SCM connections. No YAML editing or manual Kubernetes configuration is required at any point. For the current installer command and step-by-step walkthrough, see the [deployment guide](https://app.pixee.ai/docs/deploy). + +**Configuration options available in the admin console:** + +| Configuration | Options | +| -------------------- | ---------------------------------------------------------------------------- | +| **Domain and TLS** | Upload certificate, self-signed certificate, or Let's Encrypt | +| **Authentication** | None (evaluation), embedded OIDC, Google Workspace, Microsoft Entra ID, Okta | +| **LLM provider** | OpenAI, Azure AI Foundry, Anthropic, Azure Anthropic | +| **SCM integrations** | GitHub App, GitLab PAT, Azure DevOps PAT, Bitbucket API token | + +Each provider selection includes preflight checks that catch misconfiguration at install time -- not when you run your first analysis. + +## Admin Console Overview + +The KOTS admin console is the day-two operations interface for the embedded cluster: + +- **Configuration management** -- All settings are managed through a form-based UI. Changes are applied without manual Kubernetes intervention. +- **Upgrades** -- New Pixee versions are delivered through the admin console. Upgrades are single-step operations with rollback support. +- **Health monitoring** -- Platform status, service health, and resource usage are visible from the console dashboard. +- **Diagnostics** -- Support bundle generation collects logs and configuration data for troubleshooting. Log size and age limits are configurable before generation. +- **Backup and restore** -- Data protection operations are managed from the admin console. + +The key message for infrastructure teams: you do not need to learn Kubernetes to operate Pixee. The admin console abstracts all cluster management into a familiar web interface. + +## Upgrading + +Pixee releases updates approximately every two weeks. Upgrades are delivered through the admin console: + +1. The admin console notifies you when a new version is available +2. Review the release notes in the console +3. Apply the upgrade as a single-step operation +4. The console displays upgrade progress and rolls back automatically if the upgrade fails + +The embedded cluster version tracks the Pixee Enterprise release cadence. Approximately 25 releases have shipped in the last 6 months -- the platform is actively maintained and improved. + +## Security Considerations + +The embedded cluster runs as a single-tenant deployment on your infrastructure: + +- **Data isolation.** All source code, scanner findings, and triage decisions stay on the VM. Only LLM inference and license validation generate outbound traffic. +- **Network control.** The VM requires port 443 (HTTPS for SCM webhooks and UI access) and port 30000 (admin console). No other inbound ports are needed. +- **Credential management.** SCM tokens and LLM API keys are stored in Kubernetes secrets within the cluster. External secret manager integration is supported. +- **TLS options.** Upload your own certificate, use a self-signed certificate for evaluation, or configure Let's Encrypt for automatic certificate management. + +For the full security review, see [Security Architecture](/enterprise/security-architecture). + +## When to Choose Helm Instead + +The embedded cluster is the right choice for most organizations without existing Kubernetes. Consider the [Helm / BYO Kubernetes](/enterprise/helm) deployment if: + +- You already have an EKS, GKE, AKS, or self-managed Kubernetes cluster +- You want to swap embedded components for your own services (BYO database, BYO object store, BYO observability) +- Your platform engineering team prefers Helm-managed deployments and wants to integrate Pixee into existing cluster operations + +Both deployment models deliver the same triage and remediation capabilities. The choice is about infrastructure preference, not product functionality. diff --git a/docs/enterprise/deployment/helm.md b/docs/enterprise/deployment/helm.md new file mode 100644 index 00000000..5acb3e3b --- /dev/null +++ b/docs/enterprise/deployment/helm.md @@ -0,0 +1,97 @@ +--- +title: Helm / BYO Kubernetes +slug: /enterprise/helm +track: leader +content_type: guide +seo_title: Helm / BYO Kubernetes - Deploy Pixee into EKS, GKE, AKS, or Self-Managed K8s +description: Deploy Pixee Enterprise via Helm chart into your existing Kubernetes cluster. Supports EKS, GKE, AKS, and self-managed K8s with BYO component options. +sidebar_position: 4 +--- + +The Helm deployment installs Pixee into your existing Kubernetes cluster using a standard Helm chart. It supports EKS, GKE, AKS, and self-managed Kubernetes. Conditional subcharts let you swap embedded components for your own services -- BYO database (PostgreSQL 15+), object store (S3, Azure Blob, GCS), observability stack, and identity provider. This is the deployment model for organizations with established platform engineering teams. + +## Who This Is For + +The Helm deployment serves organizations that already run Kubernetes and want Pixee to fit into their existing infrastructure: + +- **Platform engineering teams** comfortable with Helm-managed deployments and `values.yaml` configuration +- **Organizations with existing shared services** (databases, observability, identity providers) that prefer to use their own rather than embedded defaults +- **Multi-cloud enterprises** running EKS, GKE, AKS, or self-managed clusters + +Compared to legacy on-premises AppSec products that ship as VM images, a native Helm chart fits modern platform-engineering workflows. Compared to cloud-only SaaS tools, it keeps code inside your VPC and IAM boundary. + +## Prerequisites + +| Requirement | Specification | +| -------------- | ----------------------------------------------- | +| **Kubernetes** | EKS, GKE, AKS, or self-managed (current stable) | +| **CPU** | 8+ vCPU | +| **RAM** | 32+ GB | +| **Storage** | 100 GB+ SSD/NVMe | +| **Helm CLI** | Current stable version | +| **Network** | Port 443 (HTTPS) | + +**Namespace isolation.** Pixee runs in a dedicated namespace. The Helm chart does not require cluster-admin privileges for day-to-day operation. Installation requires namespace creation and secret management permissions. + +**Air-gapped variant.** If your Kubernetes cluster is in an air-gapped environment, see [Air-Gapped Deployment](/enterprise/air-gap) for additional configuration requirements including private LLM endpoints and container image pre-loading. + +## Installation + +The Helm deployment follows a standard pattern: add the chart repository, create a namespace with secrets, configure `values.yaml` for your environment (LLM provider, SCM integrations, authentication mode, and BYO component selections), and install. Preflight checks validate LLM provider connectivity and catch misconfiguration at install time. For current chart versions, values reference, and step-by-step instructions, see the [deployment guide](https://app.pixee.ai/docs/deploy). + +## BYO Components + +Conditional subcharts let you swap embedded defaults for your existing infrastructure. Disable any embedded component and provide your own. + +| Component | Embedded Default | BYO Option | +| ----------------- | ------------------------- | ------------------------------------------------ | +| **Object store** | SeaweedFS | AWS S3, Azure Blob, GCS, any S3-compatible store | +| **Database** | CloudNativePG | External PostgreSQL 15+ | +| **Observability** | VictoriaMetrics + Grafana | Customer's existing observability stack | +| **Auth** | Authentik OIDC | Google Workspace, Microsoft Entra ID, Okta | + +### Credential Management for BYO Components + +- **`existingSecret` support** -- All credential references support `existingSecret` for integration with external secret managers (Vault, External Secrets Operator, SOPS). No credentials need to be stored in Helm values. +- **Pod identity support** -- IRSA (AWS), Workload Identity (GCP), and Managed Identity (Azure) are supported for object store access, alongside static key configuration. +- **BYO database secrets** -- External PostgreSQL connection details can be provided as Kubernetes secrets with `existingSecret` references. + +Pod identity support (IRSA, Workload Identity, Managed Identity) eliminates static credentials for cloud-native deployments -- a strong signal for organizations that have adopted zero-trust infrastructure. + +## Cloud Provider Storage Classes + +Platform engineers: verify your storage class matches your cloud provider. + +| Cloud Provider | Storage Class | +| --------------- | -------------- | +| **EKS** | `gp2` / `gp3` | +| **GKE** | `standard-rwo` | +| **AKS** | `managed-csi` | +| **K3s / local** | default | + +## Multi-SCM Configuration + +A single Helm deployment supports all four SCM platforms simultaneously. Configure each platform independently: + +| SCM Platform | Auth Method | Self-Hosted Support | +| ---------------- | --------------------------------------------------- | ---------------------------------------- | +| **GitHub** | GitHub App (private key + webhook secret) | GitHub Enterprise Server (custom domain) | +| **GitLab** | Personal access token (service account recommended) | GitLab self-hosted (custom base URI) | +| **Azure DevOps** | PAT with webhook user/password | Azure DevOps Server | +| **Bitbucket** | API tokens | Bitbucket Cloud and Server | + +Enterprise controls include `member_projects_only` toggles (GitLab) to restrict Pixee to projects where the service account is an explicit member, and optional work-item linking (Azure DevOps) for organizations requiring linked work items on pull requests. + +For organizations with multiple SCM platforms -- for example, GitLab on-premises for core development and GitHub for open-source contributions -- a single Pixee deployment covers both with the same triage and remediation engine. + +## Upgrading + +Pixee releases updates approximately every two weeks. Standard Helm upgrade workflow applies: + +1. Review release notes for the new version +2. Run `helm upgrade` with your existing values file +3. Verify pods restart and the UI is accessible + +Approximately 25 releases have shipped in the last 6 months. The platform is actively maintained and improved on a rapid cadence. Review release notes before each upgrade to identify any breaking changes or new configuration options. + +Before upgrading, back up your current `values.yaml` file. If an upgrade introduces an issue, roll back to the previous Helm release using standard Helm rollback commands. diff --git a/docs/enterprise/enterprise-overview.md b/docs/enterprise/enterprise-overview.md new file mode 100644 index 00000000..5452a557 --- /dev/null +++ b/docs/enterprise/enterprise-overview.md @@ -0,0 +1,74 @@ +--- +title: Enterprise Overview +slug: /enterprise/overview +track: leader +content_type: conceptual +seo_title: Enterprise Overview - Self-Hosted Security Automation +description: Pixee Enterprise deployment models, compliance controls, identity management, and operational metrics. +sidebar_position: 1 +--- + +Pixee Enterprise deploys into your infrastructure -- Dedicated SaaS, turnkey embedded cluster, Helm into existing Kubernetes, or fully air-gapped with your own LLM. Every deployment model delivers the same triage and remediation engine, the same scanner integrations, and the same audit trail. This section covers deployment options, compliance, security architecture, and how to measure operational impact. + +## Enterprise Capabilities + +Enterprise adds infrastructure control, identity management, and compliance capabilities on top of the core triage and remediation engine. + +- **Self-hosted deployment** -- run Pixee on your infrastructure with your network policies +- **SSO and access control** -- Google Workspace, Microsoft Entra ID, Okta, or embedded OIDC +- **Bring Your Own Model (BYOM)** -- choose your LLM provider, own the keys, control the bill +- **Compliance controls** -- audit-ready triage records, exportable evidence, framework alignment +- **Bundled observability** -- metrics, logs, traces, and dashboards ship in the Helm chart +- **Enterprise support** -- dedicated solutions engineering + +Pixee ships approximately 25 releases every 6 months. Four deployment models, four LLM provider families, and four SCM integrations (GitHub, GitLab, Azure DevOps, Bitbucket) are available from a single deployment. + +A single Pixee Enterprise deployment supports multiple SCM platforms simultaneously. + +## Deployment Models at a Glance + +| Model | Best For | Infra Required | Time to Deploy | +| ------------------------- | ----------------------------------------------------- | ------------------------------------------ | -------------- | +| **Dedicated SaaS** | Teams wanting zero infrastructure management | None | Minutes | +| **Embedded Cluster** | Orgs without Kubernetes, regulated industries | Single Linux VM (8 vCPU, 32 GB RAM) | Under 1 hour | +| **Helm / BYO Kubernetes** | Orgs with existing EKS/GKE/AKS clusters | Customer Kubernetes cluster | Under 1 hour | +| **Air-Gapped** | Federal, financial services, healthcare (no internet) | Customer Kubernetes + private LLM endpoint | Hours | + +Every model delivers the same triage and remediation engine. The only difference is where the infrastructure runs and how data flows through your network. See [Deployment Options](/enterprise/deployment) for architecture diagrams, data flow tables, and infrastructure requirements. + +## Enterprise Capabilities Summary + +| Capability | Status | Detail Page | +| --------------------------------------------------------------------------- | ------ | ---------------------------------------------------------- | +| Self-hosted deployment (embedded cluster and Helm) | GA | [Deployment Options](/enterprise/deployment) | +| Air-gapped deployment with private LLM | GA | [Air-Gapped Deployment](/enterprise/air-gap) | +| SSO (Google Workspace, Microsoft Entra ID, Okta) | GA | [Security Architecture](/enterprise/security-architecture) | +| Bring Your Own Model (OpenAI, Azure AI Foundry, Anthropic) | GA | [Bring Your Own Model](/enterprise/byom) | +| Bundled observability (metrics, logs, traces, dashboards) | GA | [Observability](/enterprise/observability) | +| Compliance mapping (SOC 2, HIPAA, FedRAMP, PCI-DSS, NIST 800-53, ISO 27001) | GA | [Compliance](/enterprise/compliance) | +| Multi-SCM support (GitHub, GitLab, Azure DevOps, Bitbucket) | GA | [Getting Started](/) | +| Hierarchical LLM routing (7 named tiers) | GA | [Bring Your Own Model](/enterprise/byom) | +| Audit-ready triage records with LLM justification | GA | [Compliance](/enterprise/compliance) | +| Role-based access control | GA | [Security Architecture](/enterprise/security-architecture) | + +## Measuring Success + +Track these metrics from the Pixee reporting dashboard to evaluate operational impact: + +| Metric | What It Measures | Source | +| ------------------------------- | ----------------------------------------------------------------- | ------------------------------------- | +| **Merge rate** | Percentage of Pixee PRs merged by developers | Pixee dashboard: fix activity | +| **Triage reduction** | Percentage of findings automatically classified (TP/FP/won't-fix) | Pixee dashboard: triage summary | +| **MTTR** | Time from finding detection to merged fix | Pixee reporting: remediation velocity | +| **Compliance window adherence** | Critical/high findings remediated within required timeframes | Pixee reporting + compliance tool | +| **Finding volume trend** | Total open findings over time | Pixee dashboard: backlog view | + +See [Security & Trust](/platform/security) for production metrics on fix quality and validation. + +## What's Next + +**Evaluating deployment options?** Start with [Deployment Options](/enterprise/deployment) for architecture diagrams and data flow tables. + +**Planning the rollout?** The [Phased Rollout Guide](/enterprise/phased-rollout) covers the single-repo-to-enterprise adoption path with decision gates at each phase. + +**Reviewing compliance requirements?** The [Compliance](/enterprise/compliance) page maps Pixee capabilities to SOC 2, HIPAA, FedRAMP, PCI-DSS, NIST 800-53, and ISO 27001. diff --git a/docs/enterprise/observability.md b/docs/enterprise/observability.md new file mode 100644 index 00000000..323f31d8 --- /dev/null +++ b/docs/enterprise/observability.md @@ -0,0 +1,68 @@ +--- +title: Observability +slug: /enterprise/observability +track: leader +content_type: guide +seo_title: Observability - Metrics, Logs, Traces, and Dashboards for Pixee Enterprise +description: Monitor Pixee Enterprise with bundled VictoriaMetrics, Grafana dashboards, distributed tracing, and log aggregation. BYO observability supported. +sidebar_position: 9 +--- + +Pixee Enterprise ships a complete observability stack -- metrics, logs, traces, and dashboards -- bundled in the Helm chart. No separate purchase or manual setup required. SRE teams can use the bundled stack as-is, disable individual components, or route telemetry to their existing observability platform. This page covers what is included, how to integrate with your existing stack, and key metrics to monitor. + +## Bundled Observability Stack + +The Helm chart includes five observability components, each shipped as a conditional subchart that can be independently enabled or disabled: + +| Component | Purpose | Replaceable? | +| ----------------------------- | ------------------------------ | ---------------------------------------- | +| **VictoriaMetrics** | Metrics collection and storage | Yes -- BYO Prometheus or VictoriaMetrics | +| **Victoria-logs + collector** | Log aggregation | Yes -- BYO log pipeline | +| **Victoria-traces** | Distributed tracing | Yes -- BYO tracing solution | +| **Grafana k8s-monitoring** | Dashboards and visualization | Yes -- BYO Grafana | +| **Sentry** | Error reporting | Toggleable (opt-in / opt-out) | + +Pixee ships curated dashboards built specifically for the Pixee platform -- not just upstream chart defaults. These dashboards cover platform health, analysis throughput, LLM performance, and fix quality metrics. + +**Why this matters for enterprise evaluation:** Legacy on-premises scanners (Checkmarx, Veracode) predate Kubernetes-native observability and do not ship monitoring. SaaS scanners do not expose observability because the customer does not run the infrastructure. Pixee ships both the platform and the tools to monitor it. + +## Integrating with Your Existing Stack + +Most enterprise platform teams already run an observability stack. Pixee integrates rather than duplicating. + +**Disable embedded subcharts.** Turn off any embedded component (VictoriaMetrics, Victoria-logs, Victoria-traces, Grafana) and configure Pixee to emit telemetry to your existing platform. Each subchart is independently toggleable. + +**Grafana Cloud integration.** Grafana Cloud Private Data Connector support routes metrics from your self-hosted Pixee deployment to your Grafana Cloud tenant without exposing the cluster to inbound connections. + +**Standard pipelines.** Pixee's telemetry is compatible with standard Prometheus and OpenTelemetry pipelines. If your team already runs Prometheus, Datadog, or a similar platform, Pixee's metrics integrate without custom adapters. + +**Verification.** After configuring your integration, verify that metrics, logs, and traces are flowing to your platform. Pixee's admin console shows telemetry status for embedded components. + +## Key Metrics to Monitor + +For day-two operations teams, these are the metrics that indicate platform health and business value: + +| Metric Category | What to Watch | Why It Matters | +| ----------------------- | ----------------------------------------------------- | ------------------------------------------------------------------ | +| **Analysis throughput** | Tasks completed per hour, queue depth | Platform is processing findings at expected rate | +| **LLM latency** | Inference response time per tier | Performance tuning; identifies slow or rate-limited providers | +| **Fix quality** | Average safety, effectiveness, and cleanliness scores | Quality monitoring; trends indicate model or configuration changes | +| **Merge rate** | Percentage of PRs merged by developers | Adoption tracking; the primary business-value metric | +| **Error rate** | Failed analyses, retries, suppressed fixes | Operational health; spikes indicate configuration or LLM issues | + +**Business metrics vs. platform metrics:** Merge rate, triage volume, and remediation velocity are business metrics visible in Pixee's reporting dashboard. Analysis throughput, LLM latency, and error rates are platform metrics visible in the observability stack. Both matter for different audiences -- share business metrics with security leadership and platform metrics with SRE. + +For business-level reporting (merge rate trends, triage reduction, MTTR), see [Enterprise Overview > Measuring Success](/enterprise/overview#measuring-success). + +## Operational Controls + +Operational settings are configurable through the KOTS admin console (embedded cluster) or Helm values (BYO Kubernetes): + +| Control | Description | +| -------------------------------- | -------------------------------------------------------- | +| **Sentry toggle** | Enable or disable error reporting | +| **Custom metrics toggle** | Enable or disable custom Pixee metrics | +| **LLM debug mode** | Verbose logging for LLM request/response troubleshooting | +| **Support bundle configuration** | Log size and age limits for diagnostic bundle generation | + +For troubleshooting operational issues, see [Enterprise Troubleshooting](/enterprise/troubleshooting). diff --git a/docs/enterprise/phased-rollout.md b/docs/enterprise/phased-rollout.md new file mode 100644 index 00000000..ad9ceec4 --- /dev/null +++ b/docs/enterprise/phased-rollout.md @@ -0,0 +1,167 @@ +--- +title: Phased Rollout Guide +slug: /enterprise/phased-rollout +track: leader +content_type: guide +seo_title: Phased Rollout Guide - From Pilot to Enterprise-Wide Security Automation +description: Roll out Pixee from a single repository to your entire organization with decision gates, success criteria, and rollback plans at every phase. +sidebar_position: 10 +--- + +Pixee deploys in phases: single repository, team, org unit, enterprise. Each phase has defined success criteria, a decision gate, and a rollback path. This guide gives security leaders the planning framework and security engineers the execution checklist. Most teams complete Phase 1 (single-repo pilot) within one week and reach Phase 3 (org unit) within 30-45 days. + +## Overview + +Pixee deploys in phases to validate triage accuracy and fix quality on a controlled scope before expanding. Each phase generates metrics that inform the next expansion decision. Phase 1 data feeds the metrics tracked in [Enterprise Overview > Measuring Success](/enterprise/overview#measuring-success). + +## Phase Model Overview + +| Phase | Scope | Duration | Decision Gate | Who Leads | +| ----------------------- | ------------------------------------- | --------- | ------------------------------------------------------------ | ----------------------------- | +| **Phase 1: Pilot** | 1-3 repositories | 1-2 weeks | Merge rate above 50%, zero incidents | Security Engineer | +| **Phase 2: Team** | Single team (5-15 repos) | 2-4 weeks | Team merge rate stable, developer feedback positive | Security Engineer + Team Lead | +| **Phase 3: Org Unit** | Division or business unit (50+ repos) | 4-8 weeks | Consistent metrics across teams, support processes validated | Head of AppSec | +| **Phase 4: Enterprise** | All repositories | Ongoing | Executive sign-off, compliance requirements met | CISO / Head of AppSec | + +Timeline expectations are ranges, not commitments. Actual pace depends on your team size, internal approval processes, and compliance requirements. + +## Phase 1: Pilot + +Phase 1 is where most readers will start and where the most specific guidance matters. + +### Security Leader Planning Track + +**Selecting pilot repositories.** Choose repos that have active development, existing scanner findings, and engaged developers. Avoid dormant repositories or repos with no current security findings -- they produce no data. The best pilot candidates are repos where the security team already knows about unresolved findings. + +**Defining success criteria.** Set explicit thresholds before the pilot begins: merge rate above 50%, zero false fixes (no PR that introduces a bug or breaks tests), and at least one developer who voluntarily merges a Pixee PR without prompting. Write these down. + +**Internal communication.** Notify the development team that a pilot is starting on selected repositories. + +### Security Engineer Execution Track + +**Installation.** Connect Pixee to the pilot repositories. See [Connect Source Control](/getting-started/source-control) for a platform-by-platform quick-start guide. + +**Scanner connection.** Connect your existing scanners to Pixee so it can triage and remediate findings from your current tooling. Pixee works with natively integrated scanners and any SARIF-producing scanner. + +**First fix review.** Walk through the first Pixee PR with the development team. Explain what changed, why it changed, and the quality scores. + +**Metrics collection.** Track merge rate, triage volume, and developer response time from the Pixee dashboard. + +### Phase 1 Success Criteria + +| Criterion | Threshold | How to Measure | +| ------------------ | ------------------------------------------------- | ------------------------------- | +| Merge rate | Above 50% (first-week industry average) | Pixee dashboard: fix activity | +| False fixes | Zero (no PR that breaks tests or introduces bugs) | CI/CD results on Pixee PRs | +| Voluntary adoption | At least one developer merges without prompting | Observation / PR history | +| Triage value | Triage automation reduces manual review volume | Pixee dashboard: triage summary | + +## Phase 2: Team Expansion + +### Security Leader Planning Track + +Expand from champion repositories to team-wide deployment. Set team-level merge rate targets based on Phase 1 data. Establish fix review norms: who reviews Pixee PRs, what response time is expected. + +Use Phase 1 metrics to evaluate whether expansion is warranted. The metrics tracked in [Enterprise Overview > Measuring Success](/enterprise/overview#measuring-success) provide the data points for Phase 3 decision-making. + +### Security Engineer Execution Track + +Onboard additional repositories across the team. Configure team-level policies in PIXEE.yaml for consistent behavior. Train developers on the PR review workflow -- most questions in Phase 2 are about process, not product. + +Monitor for edge cases across different codebases. Languages, frameworks, and coding patterns vary within a team. Phase 2 surfaces these variations before org-wide deployment. + +### Decision Gate + +Stable merge rate across team repos, positive developer feedback (survey or informal), no unresolved incidents. If the gate is not met, diagnose the issue before expanding -- do not push forward on momentum alone. + +## Phase 3: Org Unit + +### Security Leader Planning Track + +Multi-team coordination is the primary challenge in Phase 3. Different teams may use different scanner stacks and languages. Align Pixee metrics with compliance reporting requirements. Define the support model: who handles developer questions and escalations. + +Build the executive reporting dashboard for Phase 4 approval. Present triage reduction, merge rate trends, MTTR improvement, and compliance acceleration across all enrolled teams. + +### Security Engineer Execution Track + +Scale repository configuration across teams using PIXEE.yaml. Verify language coverage across the org unit (see [Languages > Overview](/languages/overview)). Integrate Pixee reporting with existing CI/CD pipelines and dashboards. Set up observability (see [Observability](/enterprise/observability)) if running a self-hosted deployment. + +### Decision Gate + +Consistent metrics across all enrolled teams, compliance team sign-off on audit evidence, support processes validated and documented. + +## Phase 4: Enterprise Rollout + +### Security Leader Planning Track + +Executive sign-off requires presenting Phase 3 results with the metrics tracked in [Enterprise Overview > Measuring Success](/enterprise/overview#measuring-success): merge rate, triage reduction, MTTR, and compliance window adherence. + +Make enterprise deployment model decisions at this stage -- Dedicated SaaS, embedded cluster, Helm, or air-gapped based on compliance requirements. See [Deployment Options](/enterprise/deployment). + +### Security Engineer Execution Track + +Configure SSO and access control for enterprise-wide access. Set up reporting and dashboards for ongoing operations. Establish the maintenance cadence for upgrades (approximately every two weeks for Pixee Enterprise). + +## Rollback Plan + +Pixee is additive. If any phase does not meet success criteria, disabling Pixee is straightforward and carries zero risk to existing code. + +| Action | What Happens | +| -------------------------- | ------------------------------------------------------------------------------ | +| **Disable per-repository** | Pixee stops opening PRs for that repository. Existing code is unchanged. | +| **Disable per-team** | Team-level rollback without affecting other teams. | +| **Disable entirely** | All Pixee PRs stop. No existing code changes. No runtime dependency to remove. | +| **Data preservation** | All triage decisions and fix history persist even if Pixee is paused. | + +Disabling Pixee at any phase does not affect existing code. Previously merged fixes remain as standard code in your repositories. There is no runtime dependency on Pixee for code that has been merged. + +## Identifying Internal Champions + +A champion is a developer who actively uses Pixee PRs during the pilot phase and can support other teams during expansion. Typical indicators: merges Pixee PRs early, reviews PR descriptions and quality scores in detail, and asks about framework coverage. + +**Enablement:** Share the [Languages > Overview](/languages/overview) page (coverage matrix) and this rollout guide. Provide access to the metrics from [Enterprise Overview > Measuring Success](/enterprise/overview#measuring-success). + +## Multi-Business-Unit Rollout + +Organizations with multiple business units face a sequencing decision: which BU goes first? Starting with the most mature BU -- the one with the strongest security practices and most engaged developers -- typically produces the cleanest pilot data for evaluating expansion. + +**Different scanner stacks per BU are not a problem.** Pixee handles multiple scanners simultaneously. If one BU runs Checkmarx and another runs Veracode, each BU's scanner connects independently through the same triage and remediation pipeline. No configuration conflicts, no scanner migration required. + +**Per-BU configuration via PIXEE.yaml.** Each business unit can maintain its own PIXEE.yaml with different severity thresholds, excluded directories, and PR volume settings. A conservative BU can start with critical-only findings while a more mature BU runs full scope -- both within the same Pixee deployment. + +**Expansion timeline.** After the first BU completes Phase 1 and Phase 2, budget 2-4 weeks per additional business unit. Each subsequent BU benefits from the configuration playbook and PIXEE.yaml templates the first BU established. + +## PIXEE.yaml Configuration for Phased Rollout + +PIXEE.yaml controls the scope of triage and remediation per repository or business unit. Use these example configurations to match each rollout phase. + +**Conservative (Phase 1 pilot):** Critical findings only, exclude test directories. + +```yaml +# Conservative (Phase 1 pilot): Critical findings only, exclude tests +severity: + minimum: CRITICAL +exclude: + paths: + - "**/test/**" + - "**/tests/**" + - "**/*Test.java" +``` + +**Moderate (Phase 2 expansion):** Critical and high findings, all directories included. + +```yaml +# Moderate (Phase 2 expansion): Critical + High, all directories +severity: + minimum: HIGH +``` + +**Full scope (Phase 3+):** All severities, no exclusions. + +```yaml +# Full scope (Phase 3+): All severities +severity: + minimum: LOW +``` + +Each business unit or team can use a different configuration during rollout. As confidence builds, adjust the severity threshold downward and remove directory exclusions. See [PIXEE.yaml Reference](/configuration/pixee-yaml) for the complete configuration reference. diff --git a/docs/enterprise/security-architecture.md b/docs/enterprise/security-architecture.md new file mode 100644 index 00000000..1980512b --- /dev/null +++ b/docs/enterprise/security-architecture.md @@ -0,0 +1,169 @@ +--- +title: Security Architecture +slug: /enterprise/security-architecture +track: leader +content_type: conceptual +seo_title: Security Architecture - Data Flow, Access Control, and AI Governance +description: "Pixee security architecture: data flow controls, access management, AI governance, SSO integration, credential handling, and network security." +sidebar_position: 7 +--- + +Pixee's security architecture is built on three principles: minimize data exposure (send only relevant code snippets to LLM inference, never entire repositories), preserve human authority (PR-only workflow, never direct commits), and isolate analysis (stateless inference calls that cannot persist or affect other analyses). This page details data flow, access control, credential management, and AI governance for enterprise deployments. + +For Pixee's latest security certifications, audit reports, and data processing policies, visit the [Pixee Trust Center](https://trust.pixee.ai). + +Security teams evaluating Pixee should read this page alongside [Compliance](/enterprise/compliance). Together, they cover the technical architecture and the compliance mapping that enterprise reviews require. + +## Security Principles + +Five design decisions govern Pixee's security architecture: + +1. **Minimum data exposure.** Only security-relevant code context is sent to LLM inference. Not entire repositories. Not entire files (for large files). No absolute filesystem paths, repository URLs, git metadata, commit hashes, author information, or CI/CD details are included. + +2. **No full repository access by LLM.** File paths are relative to the project root. No git metadata or author information is sent. The LLM sees only what it needs to analyze the specific vulnerability. + +3. **Stateless inference.** Each analysis is an isolated inference call. A single analysis cannot modify the model, persist data across analyses, or affect other applications. This is fundamental to how the system operates. + +4. **PR-only workflow.** Every code change is delivered as a pull request. This is an architectural constraint, not an optional setting. There is no mode, configuration, or override that allows direct commits. + +5. **Human authority preserved.** Pixee adds validation layers before changes reach your existing review process. Developers and their teams always have final approval. Your branch protection rules, required reviewers, CI/CD pipelines, and SAST re-scanning all apply to Pixee changes exactly as they apply to human-written code. + +## Data Flow Architecture + +The following describes how data flows through a self-hosted Pixee deployment: + +1. **SCM events** (push, PR creation, scanner upload) arrive at the Pixee platform via webhook +2. **Pixee platform** extracts the relevant code context for the vulnerability being analyzed +3. **Code context** is sent to the customer's LLM provider (only vulnerability-relevant snippets) +4. **LLM response** is processed by the evaluation layer (independent inference call) +5. **Approved fixes** are delivered as pull requests back to the customer's SCM +6. **Triage decisions** are persisted with timestamp, classification, and LLM justification + +For Dedicated SaaS, steps 2-4 run on Pixee-managed infrastructure. For all self-hosted models, every step runs within the customer's network. + +### Data Classification Table + +This table is the single most important reference for security review. It specifies what data each component accesses. + +| Data Type | What Pixee Platform Sees | What LLM Sees | What Is Persisted | +| ----------------------- | ------------------------------ | -------------------------------------------- | ---------------------------------------------------------------- | +| **Source code** | Relevant vulnerability context | Relevant code snippets only (not full repos) | Triage outcome and fix content, not source code | +| **Scanner findings** | Full SARIF/finding data | Finding metadata only | Classification + justification | +| **Fix proposals** | Full proposed diff | Generated by LLM | PR content + quality scores (safety, effectiveness, cleanliness) | +| **Repository metadata** | Repo name, language, branch | Not sent | Analysis metadata | +| **Developer identity** | PR author for attribution | Never sent | Anonymized in telemetry (if telemetry is enabled) | +| **File paths** | Relative to project root | Relative to project root | Relative paths only | +| **Git metadata** | Not accessed | Not sent | Not persisted | + +### Data Flow by Deployment Model + +| Data Type | Dedicated SaaS (single-tenant) | Self-Hosted (Embedded/Helm) | Air-Gapped | +| -------------------- | ------------------------------ | --------------------------- | ---------------------------- | +| Source code snippets | Pixee cloud (dedicated) | Customer network | Customer network | +| Scanner findings | Pixee cloud (dedicated) | Customer network | Customer network | +| LLM inference | Pixee-managed | Customer's provider | Customer's private endpoint | +| Triage records | Pixee cloud (dedicated) | Customer network | Customer network | +| License validation | Pixee cloud | Pixee cloud (proxyable) | Pixee cloud (proxy required) | + +## Authentication and Access Control + +| Mechanism | Implementation | +| ---------------------- | ------------------------------------------------------------------------------------- | +| **SSO** | Google Workspace, Microsoft Entra ID, Okta (direct login), or embedded Authentik OIDC | +| **Role-based access** | Admin, Security Lead, Member roles via `pixee_roles` scope | +| **SCM authentication** | GitHub App (private key), GitLab PAT, Azure DevOps PAT, Bitbucket API tokens | +| **Credential storage** | Kubernetes secrets with `existingSecret` support for external secret managers | +| **Session management** | RP-Initiated Logout, token splitting, recovery flows | + +**Embedded Authentik OIDC** runs inside the customer cluster for self-hosted deployments -- no external IdP dependency for login availability. It federates to the customer's upstream corporate IdP (Google Workspace, Microsoft Entra ID, Okta, or any OIDC source) with auto-redirect and direct login. + +**Authentication modes** are selected at install time: evaluation mode (no auth), embedded OIDC, or direct corporate IdP login. Production deployments should use SSO. + +## Credential Management + +Pixee handles four categories of credentials. None are stored in Helm values -- all use Kubernetes secrets. + +| Credential Type | Storage | External Manager Support | +| ------------------------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------- | +| **SCM tokens** (GitHub App key, GitLab PAT, ADO PAT, Bitbucket API token) | Kubernetes secret | `existingSecret` (Vault, External Secrets Operator, SOPS) | +| **LLM API keys** | Kubernetes secret | `existingSecret` | +| **Database credentials** (if BYO PostgreSQL) | Kubernetes secret | `existingSecret` | +| **Object store credentials** (if BYO S3/Blob/GCS) | Kubernetes secret or pod identity | IRSA (AWS), Workload Identity (GCP), Managed Identity (Azure) | + +**Key points for security review:** + +- Customer owns all LLM API keys. Pixee never has access to customer LLM credentials. +- LLM traffic routes through the customer's account with the customer's billing. +- Pod identity support eliminates static credentials for cloud-native deployments. +- SCM tokens require minimum scopes -- documented per platform in the installation guide. + +## Network Security + +| Requirement | Detail | +| -------------------------- | --------------------------------------------------------------------------------------------------- | +| **Outbound connections** | License validation (proxyable). LLM provider (customer-controlled). Telemetry (opt-in, toggleable). | +| **Inbound connections** | SCM webhooks on port 443 only | +| **Proxy support** | `httpProxy`, `httpsProxy`, `noProxy` with per-provider endpoint overrides | +| **TLS options** | Upload certificate, self-signed, Let's Encrypt, cert-manager | +| **TLS-intercepting proxy** | CA cert injection supported for environments with SSL inspection | + +Self-hosted deployments require no inbound connections except SCM webhooks. All other communication is outbound and proxyable. + +## AI Governance + +For security leaders evaluating AI risk, Pixee's AI governance architecture addresses common concerns: + +**Input scope limitation.** Only vulnerability-relevant code is sent to the LLM. No customer proprietary patterns, business logic context, or secrets are included in prompts. + +**No training on customer data.** Customer code is used only for the specific analysis request. Azure OpenAI and equivalent providers offer contractual guarantees that customer data is not used for model training. Pixee does not retain customer code after analysis completion. + +**Provider-family-aware prompting.** Pixee uses provider-specific prompt structures (Anthropic gets Anthropic-optimized prompts, not a one-size-fits-all approach). This is a quality measure, not a security measure -- but it indicates the system is purpose-built for each provider, not a generic wrapper. + +**Independent evaluation.** The evaluator runs as a separate inference call from the generator. The generator cannot grade its own work. Fixes that fail evaluation are suppressed entirely. + +**Responsible AI documentation.** The architecture provides concrete, verifiable answers to governance committee questions. See [Security & Trust](/platform/security) for the full trust framework. + +## Adversarial Input Protection + +Code analyzed by an LLM-based system is itself a potential attack vector. Malicious code embedded in analyzed files could attempt to manipulate the LLM through prompt injection -- crafted comments or string literals designed to alter the model's behavior. Pixee addresses this risk through defense in depth across five layers: + +**Input scope limitation.** Only vulnerability-relevant code snippets are sent to the LLM, not full repositories or entire files. This limits the attacker's surface area for embedding adversarial payloads -- most of the codebase never reaches the model. + +**Output validation via independent evaluator.** The structurally independent evaluation layer (separate context window, separate system prompt, separate scoring rubric) acts as a second opinion on every generated fix. Malicious or anomalous outputs that deviate from expected security fix patterns are caught and suppressed by this independent check. + +**Narrow generation scope.** Fixes are constrained to known security patterns drawn from OWASP and SANS remediation guidance, not open-ended code generation. The model operates within a bounded solution space, making it harder for adversarial inputs to steer output toward arbitrary code execution or data exfiltration. + +**Deterministic-first routing.** The majority of fixes use zero-LLM deterministic codemods. Vulnerabilities handled by codemods never reach an LLM at all, eliminating prompt injection risk entirely for those fix types. This reduces the overall attack surface to only the subset of fixes that require AI generation. + +**PR-only delivery.** Even in the unlikely event that a manipulated fix passed evaluation, it would arrive as a pull request subject to developer review, CI/CD pipeline execution, and SAST re-scanning. No code reaches production without human approval. + +Defense in depth reduces the risk of adversarial input attacks. No system can guarantee zero adversarial success against a sufficiently motivated attacker -- but the combination of limited input scope, independent validation, constrained generation, deterministic routing, and human review creates multiple independent barriers that an adversarial payload would need to defeat simultaneously. + +## Network Architecture + +Pixee Enterprise runs as a set of Kubernetes pods with defined communication paths between components: + +- **Platform service** -- receives webhooks from the SCM, serves the dashboard UI, and coordinates analysis requests. This is the entry point for all external communication. +- **Analysis service** -- processes scanner findings, runs triage logic, and generates remediation patches. Operates on finding data passed internally from the platform service. +- **LLM proxy** -- routes inference requests to the configured model endpoint(s). Supports OpenAI, Azure AI Foundry, Anthropic, and Azure Anthropic providers. All LLM traffic passes through this proxy for consistent audit logging and provider abstraction. +- **Database** -- PostgreSQL for triage decisions, finding metadata, quality scores, and audit records. Stores the persistent state that powers the dashboard and compliance reporting. + +**Inter-pod communication** uses the internal cluster network only. No pod-to-pod traffic is exposed externally. Service discovery is handled through standard Kubernetes DNS. + +**Inbound traffic:** HTTPS on port 443 from SCM webhooks and dashboard users. No other inbound ports are required. + +**Outbound traffic:** HTTPS to the SCM API for PR creation and status updates. HTTPS to the configured LLM endpoint for inference requests. HTTPS to the Pixee license server for validation (can be routed through a corporate proxy). No other outbound connections are required. + +No component requires privileged Kubernetes access. All pods run with standard security contexts. Network policies can further restrict inter-pod communication to only the defined paths above. + +## Data Retention + +Pixee retains the following data categories, each with distinct lifecycle controls: + +**Triage decisions** are retained for the lifetime of the deployment. Retained artifacts include finding metadata, classification verdict, justification prose, and timestamp. These records support audit defensibility and compliance reporting. + +**Fix artifacts** include PR metadata and quality scores (Safety, Effectiveness, Cleanliness). Source code diffs are stored in Git history under customer control -- Pixee does not maintain a separate copy of fixed source code. + +**LLM interaction logs** (prompts and responses) are retained for audit and debugging purposes. Enterprise customers can configure the retention period to match their organization's data governance policies. + +**Data purge** follows standard Kubernetes PVC lifecycle. Customers control retention and deletion through their infrastructure configuration. For Dedicated SaaS deployments, data deletion requests are handled through standard support channels. diff --git a/docs/enterprise/troubleshooting.md b/docs/enterprise/troubleshooting.md new file mode 100644 index 00000000..85a4c0ca --- /dev/null +++ b/docs/enterprise/troubleshooting.md @@ -0,0 +1,85 @@ +--- +title: Enterprise Troubleshooting +slug: /enterprise/troubleshooting +track: leader +content_type: reference +seo_title: Enterprise Troubleshooting - Common Deployment and Operational Issues +description: "Troubleshoot common Pixee enterprise deployment issues: installation failures, scanner connectivity, LLM configuration, SSO, and performance." +sidebar_position: 11 +--- + +This page covers the most common issues encountered during Pixee Enterprise deployment and operation. Each entry describes the symptom, likely cause, and resolution steps. Issues are organized by deployment phase: installation, scanner connectivity, LLM configuration, authentication, and day-two operations. If your issue is not listed here, contact Pixee solutions engineering. + +## Installation Issues + +| Symptom | Likely Cause | Resolution | +| ------------------------------------------- | ------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Embedded cluster install hangs or times out | Insufficient system resources | Verify minimum requirements: 8 vCPU, 32 GB RAM, 100 GB+ SSD/NVMe with under 10 ms write latency. Check disk I/O performance. | +| Helm install fails with image pull errors | Container registry access not configured | Verify image pull secrets are created in the Pixee namespace and the cluster can reach the container registry. | +| Air-gapped install fails to start | Missing container images in local registry | Verify all required images have been transferred to the local registry and are tagged correctly. Compare against the image manifest. | +| KOTS admin console is inaccessible | Port forwarding or firewall rules | Verify port 30000 is accessible from your browser. Check firewall rules and any network policies that may block the admin console port. | +| Install completes but UI is unreachable | TLS configuration mismatch | Verify the domain and TLS configuration in the admin console matches your DNS and certificate setup. Self-signed certificates require browser trust or exception. | + +**Minimum Requirements Quick Check:** Before troubleshooting any installation issue, confirm: 8 vCPU, 32 GB RAM, 100 GB+ SSD/NVMe disk, ports 443 and 30000 open (embedded cluster) or port 443 open (Helm). Most installation failures trace back to insufficient resources or network access. + +For detailed setup procedures, see [Embedded Cluster](/enterprise/embedded-cluster), [Helm / BYO Kubernetes](/enterprise/helm), or [Air-Gapped Deployment](/enterprise/air-gap). + +## Scanner Connectivity + +| Symptom | Likely Cause | Resolution | +| --------------------------------------- | ------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- | +| Scanner findings not appearing in Pixee | SARIF file format mismatch or upload path error | Verify the scanner output conforms to the SARIF specification and the upload endpoint is correctly configured. | +| Partial findings ingestion | Scanner output exceeds size limits or contains unsupported rule IDs | Check the scanner output for unsupported finding types. Verify the scanner is producing complete SARIF output. | +| Duplicate findings after re-scan | Deduplication key mismatch between scan runs | Verify the scanner configuration produces consistent finding identifiers across runs. | +| Findings appear but no fixes generated | Scanner findings are in an unsupported language or CWE category | Check the [Languages Overview](/languages/overview) for supported language and finding type coverage. | + +For scanner-specific setup guides, see [Integrations Overview](/integrations/overview). For custom scanner configuration, see the [Universal SARIF](/integrations/sarif-universal) guide. + +## LLM Configuration + +| Symptom | Likely Cause | Resolution | +| ----------------------------------------- | ----------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Fixes not generating | LLM endpoint unreachable or credentials invalid | Verify the LLM endpoint URL is correct and the API key is valid. Run the preflight check from the admin console to test connectivity. | +| Slow fix generation | LLM provider rate limits or network latency | Check your provider's rate limit status. Verify the network path between the Pixee cluster and the LLM endpoint has acceptable latency. | +| Air-gapped LLM not responding | Private LLM endpoint misconfigured | Verify the endpoint is accessible from within the cluster network namespace. Check proxy configuration if the endpoint requires proxy access. | +| Triage decisions seem inaccurate | LLM model capability insufficient | The quality of triage and remediation depends on the model at the configured endpoint. Lower-capability models produce lower accuracy. Review the model assigned to the Reasoning tier. | +| Preflight check fails during installation | Endpoint URL, API key, or network path error | Read the preflight error message carefully -- it specifies whether the issue is authentication, connectivity, or configuration. | + +For LLM provider setup details, see [Bring Your Own Model](/enterprise/byom). + +## Authentication and Access + +| Symptom | Likely Cause | Resolution | +| -------------------------------------------- | --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| SSO login fails | OIDC configuration mismatch | Verify the issuer URL, client ID, and callback URL match between Pixee and your identity provider configuration. | +| Users can log in but cannot see repositories | SCM permissions not synced | Re-sync repository access from the SCM platform. Verify the service account or GitHub App has access to the expected repositories. | +| Role assignment not working | RBAC misconfiguration | Check user role assignments in the admin console. Verify the identity provider is sending the expected role claims. | +| SSO redirect loop | Callback URL mismatch | Verify the callback URL configured in Pixee matches the redirect URI registered with your identity provider exactly, including protocol and trailing slashes. | + +For SSO configuration details, see [Security Architecture](/enterprise/security-architecture). + +## Day-Two Operations + +| Symptom | Likely Cause | Resolution | +| ----------------------------------------- | -------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------ | +| High disk usage | Log retention or metrics storage growing unbounded | Adjust log retention settings in the admin console. Configure metric pruning intervals. Review support bundle log size limits. | +| Grafana dashboards not loading | Observability subchart disabled or misconfigured | Verify the Grafana subchart is enabled. If using BYO observability, verify telemetry is flowing to your platform. | +| Upgrade fails | Helm values conflict with new version | Review release notes for breaking changes before upgrading. Back up your values file before running the upgrade. | +| Support bundle is too large | Default log collection scope too broad | Configure support bundle log size and age limits before generating. Narrow the collection scope to the relevant time window. | +| Analysis queue growing without processing | LLM endpoint degraded or rate limited | Check LLM endpoint health and rate limit status. Review the error rate in the observability dashboard. | + +For monitoring configuration, see [Observability](/enterprise/observability). + +## Getting Help + +If your issue is not covered on this page: + +1. **Generate a support bundle** from the KOTS admin console (embedded cluster) or using the support bundle tool (Helm). Configure log size and age limits before generation to control bundle size. + +2. **Contact Pixee solutions engineering** with: + - Deployment model (embedded cluster, Helm, air-gapped) + - Pixee version (visible in admin console or Helm release) + - Symptom description and when it started + - Support bundle (attached) + +3. **For critical issues** affecting production analysis, escalate through your enterprise support channel for priority response. diff --git a/docs/faq/_category_.json b/docs/faq/_category_.json new file mode 100644 index 00000000..08b9f8b1 --- /dev/null +++ b/docs/faq/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "FAQ", + "position": 10, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "faq/faq" + } +} diff --git a/docs/faq/faq.md b/docs/faq/faq.md new file mode 100644 index 00000000..5c79e39b --- /dev/null +++ b/docs/faq/faq.md @@ -0,0 +1,191 @@ +--- +title: FAQ +slug: /faq/general +track: both +content_type: faq +seo_title: "Pixee FAQ | General, Enterprise, and Troubleshooting" +description: "Common questions about Pixee: how it works, safety, enterprise deployment, and troubleshooting." +sidebar_position: 1 +--- + +Frequently asked questions organized by topic. For detailed technical documentation, follow the links in each answer. + +## General + +### What is automated vulnerability remediation? + +Automated vulnerability remediation programmatically fixes security findings without requiring a developer to manually write the patch. Pixee generates fixes as pull requests that go through your existing review and CI/CD pipeline. Fixes come from two sources: deterministic codemods — rule-based transformations where the same input always produces the same output — and constrained AI generation for patterns where deterministic rules do not reach. Every fix passes a multi-layer validation pipeline before delivery. The typical fix changes 1-5 lines of code, applying established OWASP/SANS security patterns. + +### How does automated vulnerability triage work? + +Pixee's triage engine routes each finding through three progressive tiers: deterministic analyzers for known patterns (sub-second, zero cost), AI agents for ambiguous cases (dynamic codebase investigation), and automatic handling for novel and custom rule types — including proprietary scanners and custom rulesets — without manual configuration. Every verdict includes a structured justification — the specific code paths, security controls, or context that drove the decision. Up to 98% false positive reduction. See [Triage](/platform/triage) for the full architecture. + +### What is a codemod? + +A codemod is a deterministic code transformation rule that rewrites source code from a vulnerable pattern to a safe pattern. Same input, same output — no randomness, no variation between runs. Pixee's open-source codemod engines (codemodder-java, codemodder-python) are publicly inspectable. See [Codemodder](/open-source/codemodder) for the full catalog. + +### What scanners does Pixee work with? + +Pixee integrates natively with a growing list of scanners including CodeQL, Semgrep, Checkmarx, Veracode, Snyk Code, SonarQube, AppScan, Polaris, Fortify, Contrast, GitLab SAST, GitLab SCA, Trivy, Arnica, and Datadog SAST. Any scanner that produces SARIF output can also connect through the Universal SARIF integration — over 50 additional scanners validated. You do not need to change your detection stack. + +### Does Pixee replace my existing scanners? + +No. Pixee sits downstream of your existing SAST, SCA, and DAST tools. It consumes their findings, triages them to separate real threats from false positives, and produces validated fixes for confirmed vulnerabilities. + +### What programming languages does Pixee support? + +Java, Python, JavaScript/TypeScript, .NET/C#, Go, Ruby, PHP, Kotlin, Rust, Scala, Swift, plus IaC formats (Terraform, Dockerfile, K8s/Helm, CloudFormation). Deterministic codemod coverage is deepest for Java and Python. See [Language Support](/languages/overview) for the full coverage matrix. + +### Does Pixee support SCA (software composition analysis) remediation? + +Yes. SCA findings flow through the same triage and remediation pipeline as SAST findings. Pixee handles transitive dependency resolution, breaking change detection, and dependency upgrade coordination — delivering atomic PRs that include both the manifest version bump and downstream source-file changes. See [SCA](/platform/sca) for details. + +### What is the difference between Pixee and GitHub Copilot Autofix? + +Copilot Autofix is limited to GitHub Advanced Security (CodeQL) findings on GitHub. Pixee works with a growing list of natively integrated scanners across GitHub, GitLab, Azure DevOps, and Bitbucket. Pixee also provides triage automation, which Copilot Autofix does not offer. Pixee uses deterministic codemods alongside constrained AI, while Copilot Autofix relies on general-purpose AI code generation. Pixee also supports self-hosted and air-gapped deployment with Bring Your Own Model (BYOM). + +### How long does it take to set up Pixee? + +Dedicated SaaS setup: install the GitHub App, GitLab integration, Azure DevOps extension, or Bitbucket connector and Pixee begins analyzing repositories immediately — under 5 minutes. Self-hosted deployment (embedded cluster or Helm) typically completes in under one hour. Air-gapped deployment takes longer due to private LLM configuration and image transfer. + +### Does Pixee require code changes to install? + +No. Pixee installs as a platform integration and requires zero code changes, CLI installs, or configuration files to start. Developers interact with Pixee through standard pull requests in their existing platform. + +### How long does it take to see results? + +Most teams see their first automated fix within hours of connecting a scanner with existing findings. Triage results appear even faster — Pixee begins classifying findings as soon as scanner data is available. + +### Can I customize which vulnerabilities Pixee fixes? + +Yes. PIXEE.yaml configuration lets you control which finding types Pixee addresses, which repositories are active, and what approval workflows apply. You can exclude specific files, directories, or finding categories. See the [PIXEE.yaml Reference](/configuration/pixee-yaml) for configuration syntax. + +## Safety and Trust + +### Does automated remediation break existing code? + +Every fix goes through a multi-layer validation pipeline — constrained generation, independent evaluation by a separate model scoring Safety, Effectiveness, and Cleanliness, and your existing CI/CD pipeline and code review process. Fixes that do not pass validation are not delivered. See [Security & Trust](/platform/security). + +### What is the merge rate for Pixee-generated fixes? + +76% of Pixee-generated fixes are merged by development teams after human review on production deployments. This reflects developer trust after reviewing pre-validated fixes — not raw AI output. Fixes that cannot pass quality standards are suppressed before reaching a PR. + +### What happens if an automated fix introduces a bug? + +Every Pixee fix is delivered as a pull request, not a direct commit. Standard `git revert` applies if a merged change needs to be undone. There is no runtime dependency on Pixee for previously merged code. Closing an unmerged PR discards the proposed change with zero impact. + +### How does Pixee handle false positives from scanners? + +The triage engine reduces false positives by evaluating dataflow quality, detecting security controls between source and sink, classifying production vs. test code, and filtering intentionally-vulnerable projects. Each classification includes a structured justification. Security engineers can override any verdict. See [Triage](/platform/triage). + +### Is automated vulnerability remediation safe for production code? + +Yes. Pixee's fixes are narrow-scope security changes (1-5 lines) applying established OWASP/SANS patterns, not general-purpose code generation. They pass multi-layer validation before reaching a PR, and your existing CI/CD, SAST re-scanning, and code review gates all apply. The PR-only delivery model is an architectural constraint — there is no mode that allows direct commits. See [Security & Trust](/platform/security). + +## Enterprise + +### Does Pixee support self-hosted deployment? + +Yes. Three deployment models: embedded cluster (turnkey, no Kubernetes expertise required), Helm (for existing Kubernetes infrastructure), and air-gapped (fully disconnected with customer-hosted LLM). See [Deployment Options](/enterprise/deployment). + +### What are the infrastructure requirements for self-hosted Pixee? + +Minimum: 8 vCPU, 32 GB RAM, 100 GB SSD (single Linux VM for embedded cluster). See [Deployment Options](/enterprise/deployment) for sizing guidance per model. + +### Does Pixee support multiple SCM platforms simultaneously? + +Yes. A single Pixee Enterprise deployment supports GitHub, GitLab, Azure DevOps, and Bitbucket at the same time. Each SCM connection is configured independently. + +### Can Pixee run in an air-gapped environment? + +Yes. Pixee supports fully air-gapped deployment with a customer-hosted LLM. No code leaves your environment after installation. License validation requires a network path to Pixee servers (direct or via proxy). See [Air-Gapped Deployment](/enterprise/air-gap). + +### How does Pixee handle data residency requirements? + +Self-hosted deployments keep all data in your network. Air-gapped deployments have zero outbound data transmission. For Dedicated SaaS, each customer is provisioned into a dedicated, single-tenant environment — contact Pixee for full data handling details. See [Security Architecture](/enterprise/security-architecture) for the full data flow table by deployment model. + +### What data does Pixee send to LLM providers? + +Only code snippets relevant to the specific vulnerability — the vulnerable function and surrounding context — are sent to the configured LLM provider. No repository names, organizational metadata, or CI/CD configuration is sent. In self-hosted and air-gapped deployments, this traffic stays within your network. Bring Your Own Model (BYOM) means you control the provider, the model, and the endpoint. + +### Can I control which LLM provider Pixee uses? + +Yes. BYOM supports OpenAI, Azure AI Foundry, Anthropic, and Azure Anthropic. For air-gapped deployments, you host the model entirely within your network. See [BYOM Configuration](/enterprise/byom). + +### Does Pixee support SOC 2, FedRAMP, HIPAA, and other compliance frameworks? + +Pixee's architecture supports the controls required for major compliance frameworks. Contact Pixee for current SOC 2 Type II certification status and audit report availability. See [Compliance](/enterprise/compliance) for the full framework mapping table covering SOC 2, HIPAA, FedRAMP, PCI-DSS, NIST 800-53, and ISO 27001. + +### What audit trail does Pixee provide? + +Every Pixee fix creates a defensible audit record: typed triage verdict with code-level evidence, fix quality scores on every PR, full Git history showing what changed when and why, SAST re-scanning confirmation, and developer approval recorded in the merge event. Triage decisions export via CSV, JSON, and API. See [Compliance](/enterprise/compliance). + +### How does Pixee handle AI governance requirements? + +Every AI-generated fix passes through documented validation layers before delivery — constrained generation, independent evaluation by a separate model, and your existing code review process. The PR-based workflow ensures human-in-the-loop approval for every change. A significant portion of fixes use zero LLM involvement (deterministic codemods). All decisions are auditable with persisted reasoning. See [Security & Trust](/platform/security) for the Responsible AI governance Q&A. + +## Troubleshooting + +### Why is Pixee not analyzing my repository? + +Most likely cause: the repository has not been enabled in Pixee's settings after installing the SCM app. + +1. Verify the GitHub App, GitLab integration, Azure DevOps extension, or Bitbucket connector is installed on the correct organization. +2. Check that the specific repository is enabled in Pixee's repository management settings — installing the app does not automatically enable all repositories. +3. Verify Pixee has the required permissions: read code, read pull requests, write pull requests. +4. For GitLab, confirm the service account has the required scopes (`api`, `read_user`, `read_repository`, `read_api`, `write_repository`). +5. For Azure DevOps, verify the PAT is active and the webhook is configured. + +### Pixee installed but I do not see any activity. What is wrong? + +Most likely cause: no scanner findings exist for the connected repository. **Connecting a scanner is required** — Pixee needs scanner findings to generate fixes and triage results. + +1. Connect at least one scanner. See the [Integrations Overview](/integrations/overview) for setup instructions. +2. Verify the scanner has produced findings for the repository. +3. For custom or unsupported scanners, verify findings are in SARIF format and are being uploaded correctly. + +### Why are scanner findings not showing up in Pixee? + +Three common causes, in order of likelihood: + +1. **Integration not configured.** Each scanner requires its own integration configuration. +2. **Format mismatch.** Scanner output does not match the expected specification. Verify SARIF compliance for custom scanners. +3. **Upload path incorrect.** Scanner results are not being delivered to the correct endpoint. Check the integration documentation for the expected delivery method. + +### Scanner findings appear in Pixee but no fixes are generated. Why? + +Not all findings have available fixes. Pixee generates fixes when: a codemod or AI generation path exists for the vulnerability pattern, the code context is sufficient for safe fix generation, and the fix passes the multi-layer validation pipeline. Findings without available fixes still receive triage classification. Check [Language Support](/languages/overview) for coverage of your specific finding types. + +### Why is Pixee not opening PRs on my repository? + +Check in order: + +1. Repository enabled and Pixee has write PR permissions. +2. Scanner findings exist for the repository. +3. Fixes are available for the finding types present. +4. PIXEE.yaml is not excluding the relevant files, directories, or finding types. +5. Scheduling configuration has not deferred PR creation to a future window. + +If all five check out, contact Pixee support with your repository name and the finding types you expect fixes for. + +### A Pixee PR failed CI. What should I do? + +**If the failure is in Pixee's fix:** Close the PR. Pixee's fixes are validated before delivery, but they cannot account for every CI environment configuration. Closing a PR with zero impact is the intended workflow for fixes that do not fit your context. + +**If the failure is unrelated to Pixee's change:** Re-run CI. Check whether the CI failure also appears on other PRs to confirm it is not Pixee-specific. + +### Why does Pixee classify a finding as false positive when I think it is real? + +Review the structured justification provided with the classification — the specific code paths, security controls, or context signals that drove the decision. If you disagree after reviewing the evidence, override it. Overrides help calibrate triage accuracy for your codebase over time. + +### How do I prevent Pixee from fixing certain vulnerability types? + +Use [PIXEE.yaml](/configuration/pixee-yaml) to exclude specific finding types, files, or directories. You can also disable specific codemods by ID. + +### How do I export triage decisions for compliance reporting? + +Pixee exports triage decisions via CSV, JSON, and API. Each export includes timestamp, finding metadata, classification, structured justification, and any analyst overrides. See the [Reporting](/configuration/operations) page for export procedures. + +### Can I use Pixee with a private or internal GitHub Enterprise instance? + +Yes, with self-hosted deployment. Pixee Enterprise (embedded cluster, Helm, or air-gapped) runs within your network and connects to your internal SCM instance. See [Deployment Options](/enterprise/deployment). diff --git a/docs/faqs.md b/docs/faqs.md deleted file mode 100644 index d046c1ec..00000000 --- a/docs/faqs.md +++ /dev/null @@ -1,204 +0,0 @@ ---- -sidebar_position: 8 ---- - -# FAQs - -### What are Pixee's AI features? - -We utilize Large Language Models (LLMs) in some context-aware code fixes and to add code-specific comments, helping developers understand why a change is being recommended. Our triage features use LLMs to gather facts about the vulnerable code flow, wider technical context, in combination with deterministic analysis, to feed an expert recommendation system that produces our results. - -### What is Pixee's AI policy? - -At Pixee, we take your data privacy and security seriously. We want you to have peace of mind, knowing that your data will never be used to train AI models. - -### How does Pixee handle my data? - -Pixee is a platform focused on helping developers deliver higher quality code and places the utmost importance on our own security, including secure software development practices, IT practices, corporate controls and partner assessments. In case anyone asks, yes -- all data is encrypted in transit and at rest, and guaranteed to be destroyed. - -As an aside, many of us have been in security our whole careers, and we're quite passionate about it! We document all of this and more in our [Security and Trust Center](https://trust.pixee.ai/). - -### How will my information (i.e. code, projects, etc.) be used? - -Each party agrees to hold data and confidential information of the other party in confidence and not to disclose, retain, or distribute such information to third parties or to use such information for any purpose whatsoever. Please take a look at our full [Privacy Policy](https://www.pixee.ai/privacy) for more detail. - -### How do I know Pixee made changes? - -Pixee works directly with your repositories through pull/merge requests, so you decide when and if you want to accept changes suggested by Pixee. You can find suggestions made by Pixee in the [Pixee Dashboard](https://app.pixee.ai/) as well as your repository's GitHub.com pull requests page. Also, Pixee [cryptographically signs every commit](https://git-scm.com/book/en/v2/Git-Tools-Signing-Your-Work), which means changes suggested by Pixee are guaranteed to have come from Pixee, were not modified after the fact and are [verified by GitHub](https://docs.github.com/en/authentication/managing-commit-signature-verification/about-commit-signature-verification). - -### You said Pixee supports rule X for language Y, but I don't see a fix available. What gives? - -Some "shapes" of vulnerable code may not be fixable in a safe way, or recognized by our remediation logic. Please file a ticket if this happens and you think we should fix it! Providing an anonymized code sample and security finding will help us a lot. - -### Where can I learn more and discuss Pixee? - -Users can join the Pixee community [on Slack](https://join.slack.com/t/openpixee/shared_invite/zt-1pnk7jqdd-kfwilrfG7Ov4M8rorfOnUA). This channel can be used to engage with peers who are also interested in Pixee. Feel free to email us at help@pixee.ai with any questions or comments. - -### Why does pixee sometimes add new dependencies to my project? - -We always prefer to use existing controls built into a language, or a control from a well-known and trusted community dependency. When this is not an option, we add our own open source dependency to the project to ensure maximum readability and maintainability. All dependencies utilize permissive open-source licenses. - -Learn more about the [Java Security Toolkit (io.github.pixee.java-security-toolkit) on Maven Central](https://central.sonatype.com/artifact/io.github.pixee/java-security-toolkit/overview). - -Learn more about the [Python security package on PyPI](https://pypi.org/project/security/). - -### How do automatically assign GitHub PR reviewers? - -To automatically assign **reviewers** to Pixee PRs, consider [setting up a `CODEOWNERS` file](https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners). - -To automatically assign **users** to Pixee PRs, consider creating a GitHub action. Below is an example action that will assign all Pixee PRs to the user Octocat: - -```yaml -on: - pull_request: - types: [opened, reopened, ready_for_review] - -jobs: - auto-assign: - runs-on: ubuntu-latest - if: github.actor == 'pixeebot[bot]' - steps: - - name: Checkout - uses: actions/checkout@v4 - - - name: Assign PR to Collaborators - uses: actions/github-script@v7 - with: - script: | - const collaborators = ['octocat']; // Replace with actual GitHub usernames - github.rest.issues.addAssignees({ - owner: context.repo.owner, - repo: context.repo.repo, - issue_number: context.issue.number, - assignees: collaborators - }) -``` - -### Configuring Automatic Formatting - -Many projects enforce a consistent code style by using automatic code formatters. This section contains instructions for configuring GitHub Actions to automatically format PRs that are created by Pixee. - -#### Python - -The most popular Python code formatter is [Black](https://black.readthedocs.io/en/stable/). To automatically format PRs created by Pixee using Black, add the following GitHub action workflow to your repository: - -```yaml -name: Format Pixeebot PRs - -on: - pull_request: - types: [opened, synchronize] - -jobs: - apply-black: - if: github.event.pull_request.user.login == 'pixeebot[bot]' - runs-on: ubuntu-latest - permissions: - contents: write - - steps: - - name: Checkout - uses: actions/checkout@v4 - - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.12" - - - name: Install black - run: pip install black - - - name: Apply black formatting - run: black . - - - name: Commit and push changes - uses: stefanzweifel/git-auto-commit-action@v5 - with: - commit_message: ":art: Apply formatting" -``` - -This action can be added to your repository by creating a `.github/workflows/pixeebot-autoformat-black.yml` file with the above content. - -Note that it may be necessary to pin the version of Black to ensure that the formatting is consistent with your project's style. Depending on your project's configuration it may also be necessary to pass additional arguments to the `black` command to ensure that the correct settings are used. - -#### Java - -For Java projects it is common to use a tool such as [Spotless](https://github.com/diffplug/spotless) to enforce code formatting. To automatically format PRs created by Pixee using Gradle to apply Spotless, add the following GitHub action workflow to your repository: - -```yaml -name: Format Pixeebot PRs - -on: - pull_request: - types: [opened, synchronize] - -jobs: - spotless-apply: - if: github.event.pull_request.user.login == 'pixeebot[bot]' - runs-on: ubuntu-latest - permissions: - contents: write - - steps: - - uses: actions/checkout@v4 - - - name: "Setup JDK" - uses: actions/setup-java@v4 - with: - distribution: "temurin" - java-version: "17" - - - name: 🐘Setup Gradle - uses: gradle/actions/setup-gradle@v3 - - - name: 🎨 Run spotless via Gradle - run: ./gradlew spotlessApply - - - name: Commit and push changes - uses: stefanzweifel/git-auto-commit-action@v5 - with: - commit_message: ":art: Apply formatting" -``` - -### How do I configure Lockfile Updates? - -Some Pixee fixes add dependencies to your project. For package managers that rely on lockfiles, it is important to update the lockfile after adding dependencies. We recommend using a GitHub Action to automatically update lockfiles for Pixee PRs. - -#### Python: Poetry - -[Poetry](https://python-poetry.org/) is a popular Python package manager that uses a `pyproject.toml` file to manage dependencies. To automatically update the Poetry lockfile for Pixee PRs that add dependencies, add the following GitHub action workflow to your repository: - -```yaml -name: Update Poetry Lockfile - -on: - pull_request: - paths: - - "pyproject.toml" - -jobs: - update-lock-file: - if: github.event.pull_request.user.login == 'pixeebot[bot]' - runs-on: ubuntu-latest - steps: - - name: Check out repository - uses: actions/checkout@v3 - with: - fetch-depth: 0 - - - name: Set up Python - uses: actions/setup-python@v4 - with: - python-version: "3.11" # Specify your Python version here - - - name: Install Poetry - run: pip install poetry - - - name: Generate lock file - run: poetry update - - - name: Commit and push changes - uses: stefanzweifel/git-auto-commit-action@v5 - with: - commit_message: ":lock: Update Poetry lock file" -``` diff --git a/docs/getting-started/_category_.json b/docs/getting-started/_category_.json new file mode 100644 index 00000000..d60f115a --- /dev/null +++ b/docs/getting-started/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Getting Started", + "position": 1, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "getting-started/getting-started" + } +} diff --git a/docs/getting-started/first-fix.md b/docs/getting-started/first-fix.md new file mode 100644 index 00000000..08f5bf1b --- /dev/null +++ b/docs/getting-started/first-fix.md @@ -0,0 +1,99 @@ +--- +title: Your First Fix +slug: /getting-started/first-fix +track: dev +content_type: tutorial +seo_title: "Your First Pixee Fix | From Install to Merged PR" +description: "What a Pixee PR looks like, what the quality scores mean, and what to do with it." +sidebar_position: 6 +--- + +Your first Pixee fix arrives as a pull request in your existing code review tool. This page covers what to expect, how to evaluate the fix, and what the quality scores mean. + +## Anatomy of a Pixee Fix PR + +**PR Title:** Identifies the vulnerability type and affected file. Example: `Pixee fix: Parameterize SQL query in UserRepository.java` + +**PR Description — four parts:** + +1. **The vulnerability** — What was found, which scanner flagged it, severity, CWE, and OWASP category. +2. **The fix** — What Pixee changed and why this approach was chosen. +3. **Quality scores** — Safety, Effectiveness, and Cleanliness scores from the independent evaluation gate. +4. **References** — CWE definitions, OWASP documentation, scanner rule links. + +**The Diff:** Typically 1-5 lines in a single file. One vulnerability per PR — no bundled changes or surrounding refactors. + +## Understanding the Quality Scores + +Every Pixee PR includes three scores from an independent evaluation pass (a separate inference call from the fix generator): + +| Score | What It Checks | +| ----------------- | ----------------------------------------------------------------- | +| **Safety** | No breaking changes, no regressions, no unintended side effects | +| **Effectiveness** | The fix correctly resolves the vulnerability | +| **Cleanliness** | Proper formatting, no extraneous changes, preserves existing code | + +All three must pass before the fix reaches your PR queue. A fix cannot reach you on a high Cleanliness score if it fails Safety. + +## What to Do With the PR + +Review a Pixee PR the same way you review any other code change: + +1. Read the PR description — understand the vulnerability and the fix approach. +2. Review the diff — confirm the code change is correct for your application. +3. Check CI results — your existing tests, linters, and scanners run against the fix automatically. +4. Decide: + +| Action | When | +| ------------------- | ------------------------------------------------------------------------------------- | +| **Merge** | The fix is correct, tests pass, and the change resolves the vulnerability | +| **Request changes** | The fix is directionally correct but needs modification for your codebase conventions | +| **Close** | The fix is not appropriate for your codebase or the finding is acceptable risk | + +Pixee proposes. You decide. Your code review policies, CI/CD pipelines, and branch protection rules all apply. + +## Example Fixes + +**SQL injection — Java:** + +```java +// Before +String query = "SELECT * FROM users WHERE id = '" + userId + "'"; +Statement stmt = conn.createStatement(); +ResultSet rs = stmt.executeQuery(query); + +// After (Pixee fix) +String query = "SELECT * FROM users WHERE id = ?"; +PreparedStatement stmt = conn.prepareStatement(query); +stmt.setString(1, userId); +ResultSet rs = stmt.executeQuery(); +``` + +**Dependency upgrade (SCA fix):** Pixee bumps a vulnerable dependency to a patched version in your manifest file (`pom.xml`, `requirements.txt`, `package.json`) and includes any downstream source-file changes in the same PR. + +## After You Merge + +Once you merge, the vulnerability is resolved. Your scanner confirms remediation on its next run, and your backlog shrinks. No dashboard to update, no ticket to close. The merged PR is the record. + +Standard `git revert` applies if a merged change ever needs to be undone. There is no runtime dependency on Pixee for merged code. + +## If No Fix Arrives + +:::note +If you do not see a PR within an hour of installation, check these in order: + +1. **Verify the integration is connected.** Check that Pixee has access to the repositories you selected during setup. +2. **Confirm a scanner is connected.** Pixee needs scanner findings to act on. Connect CodeQL, Semgrep, SonarQube, or any SARIF-producing scanner via [CI/CD Integration](/integrations/ci-cd). +3. **Confirm supported languages are present.** Repositories in unsupported languages will not generate fixes. +4. **Check for fixable findings.** Your repositories may have findings that Pixee cannot currently remediate. Triage classifications will still appear. + ::: + +## From First Fix to Full Value + +Once the workflow is proven: + +- **Connect additional scanners** to expand coverage. Pixee works with natively integrated scanners and any SARIF-producing tool. +- **Roll out to more repositories** as confidence builds. +- **Track your merge rate** — see [Security & Trust](/platform/security) for merge rate data and context. + +For scaling to organization-wide deployment, see the [Phased Rollout Guide](/enterprise/phased-rollout). For technical depth on fix methodology, see [Remediation](/platform/remediation). diff --git a/docs/getting-started/getting-started.md b/docs/getting-started/getting-started.md new file mode 100644 index 00000000..4e32a952 --- /dev/null +++ b/docs/getting-started/getting-started.md @@ -0,0 +1,86 @@ +--- +title: Welcome to Pixee +slug: / +track: dev +content_type: tutorial +seo_title: "Get Started with Pixee | Automated Security Remediation" +description: Install Pixee and connect your scanners for automated vulnerability triage and remediation via pull requests. +sidebar_position: 1 +--- + +Pixee automates vulnerability triage and remediation directly inside your existing pull request workflow. Install the GitHub App, GitLab integration, Azure DevOps extension, or Bitbucket connector, connect your scanners, and Pixee starts delivering fixes as standard PRs your developers already know how to review and merge. Setup takes under five minutes, and most teams see their first automated fix within the hour. + +Pixee is not a scanner. It works downstream of your existing SAST, SCA, and DAST tools — ingesting their findings, triaging them for exploitability, and generating validated fixes. + +## What Pixee Does + +Pixee provides two co-equal capabilities: + +**Triage Automation** reduces false positives by up to 98%. Each scanner finding passes through exploitability analysis that determines whether the vulnerability is actually reachable and triggerable in your codebase — not just whether it matches a pattern. Every verdict includes a structured justification with the specific code evidence that drove the decision. + +**Remediation Automation** generates context-aware code fixes and delivers them as pull requests. Developers review and merge these PRs like any other code change. Across production deployments, 76% of Pixee-generated fixes are merged by development teams after human review. + +Both capabilities work together. Triage eliminates the noise. Remediation fixes what remains. + +| Capability | What It Does | Proof Point | +| ----------- | ----------------------------------------------------------- | ---------------------------------------- | +| Triage | Exploitability analysis across natively integrated scanners | Up to 98% false positive reduction | +| Remediation | Context-aware fixes as pull requests | 76% merge rate on production deployments | +| Delivery | Standard PRs in GitHub, GitLab, ADO, Bitbucket | Native platform integration | + +## Setup Flow + +Setting up Pixee takes three steps: + +| Step | Page | Time | +| --------------------------------------- | --------------------------------------------------------- | -------- | +| 1. Connect your source control platform | [Connect Source Control](/getting-started/source-control) | 3-5 min | +| 2. Connect your scanners | See below — required | 5-10 min | +| 3. Review and merge your first fix | [Your First Fix](/getting-started/first-fix) | 5 min | + +Total time to first merged fix: under 30 minutes for most teams. + +## Connecting Scanners (Required) + +:::warning[Scanners are required] +Pixee requires scanner findings to perform triage and generate fixes. Without at least one connected scanner, there is nothing for Pixee to act on. Installing Pixee without connecting a scanner will not produce any results. +::: + +**What "connecting a scanner" means:** + +- For scanners that write to your SCM's code-scanning surface (GitHub Code Scanning, GitLab Security Dashboard, etc.), Pixee ingests findings automatically through the SCM integration — no additional step required. +- For scanners that don't write to the SCM's code-scanning surface, upload SARIF results to the SCM's code-scanning API as a CI step. Pixee then ingests them through the SCM integration. +- For natively integrated scanners, configure the scanner connection directly in Pixee. Pixee pulls results automatically — no SARIF upload or CI step required. See [Integrations Overview](/integrations/overview) for the list of supported native integrations. + +Pixee integrates natively with a growing list of scanners including CodeQL, Semgrep, Checkmarx, Veracode, Snyk Code, SonarQube, AppScan, Polaris, Fortify, Contrast, GitLab SAST, GitLab SCA, and Trivy. Any SARIF-producing scanner also works. See [Scanner Integration](/platform/scanner-integration) for the full list and [CI/CD Integration](/integrations/ci-cd) for pipeline setup examples. + +## Choose Your Platform + +See [Connect Source Control](/getting-started/source-control) for a quick-start summary of all four platforms (GitHub, GitLab, Azure DevOps, Bitbucket) with connection requirements and step summaries. Full setup guides live under [Integrations → Source Control](/integrations/overview). + +Need enterprise deployment (self-hosted, air-gapped, BYOM)? Start with [Enterprise Deployment Options](/enterprise/deployment). + +## What Happens After Install + +1. Pixee connects to your repositories and ingests findings from your connected scanners. +2. The triage engine classifies each finding as true positive, false positive, or won't-fix — with a structured justification for every decision. +3. For confirmed vulnerabilities with available fixes, Pixee opens a pull request containing the fix, the vulnerability context, and quality scores. +4. Your developers review the PR in their normal workflow — same code review process, same CI/CD pipeline, same branch protection rules. +5. Developers merge, modify, or close the PR. No special tooling required. + +## Prerequisites + +- A GitHub, GitLab, Azure DevOps, or Bitbucket account with at least one repository +- At least one connected scanner — this is required for triage and remediation to work + +No agents to install. No CLI required for the standard workflow. No configuration files needed to start. + +## Large Backlogs (10,000+ Findings) + +Pixee handles large vulnerability backlogs without overwhelming your development team. Findings are prioritized by severity — Critical and High findings are processed first. + +PR creation is batched, not instantaneous. Expect a steady stream of fixes delivered over days, not a flood of hundreds of PRs at once. + +Use a [PIXEE.yaml](/configuration/pixee-yaml) file to scope initial remediation to specific severity levels, vulnerability types, or repository paths. + +For organizations managing hundreds of repositories or millions of findings, the [Phased Rollout Guide](/enterprise/phased-rollout) covers rollout strategy for large estates. diff --git a/docs/getting-started/source-control.md b/docs/getting-started/source-control.md new file mode 100644 index 00000000..cb2a9345 --- /dev/null +++ b/docs/getting-started/source-control.md @@ -0,0 +1,109 @@ +--- +title: Connect Source Control +slug: /getting-started/source-control +track: dev +content_type: tutorial +seo_title: "Connect Source Control to Pixee | GitHub, GitLab, Azure DevOps, Bitbucket" +description: Connect your source control platform to Pixee. Quick-start summary for GitHub, GitLab, Azure DevOps, and Bitbucket with links to full setup guides. +sidebar_position: 2 +--- + +Pixee delivers automated vulnerability fixes as pull requests (or merge requests) directly in your existing SCM workflow. Connect your SCM platform once, and Pixee starts triaging scanner findings and opening fix PRs. Setup takes under five minutes for most platforms. + +Choose your platform below for the connection summary, then follow the link to the full setup guide for detailed instructions, permissions tables, and troubleshooting. + +## GitHub + +| Item | Detail | +| ------------------------ | --------------------------------------------------------------------------------------------------------------------------- | +| **Integration type** | GitHub App (installed from GitHub Marketplace) | +| **Required permissions** | Repository contents, pull requests, code scanning alerts, checks, webhooks, metadata | +| **What you need** | Admin or owner permissions on target repositories or org | +| **Scanner ingestion** | Automatic via GitHub Code Scanning (GHAS API) — no extra step if you run CodeQL, Semgrep, or other SARIF-uploading scanners | + +**Quick steps:** + +1. Install the Pixee GitHub App from the GitHub Marketplace and select your organization. +2. Choose which repositories to connect (org-wide or specific repos). +3. Pixee ingests scanner findings and opens fix PRs — typically within the first hour. + +For public repositories without an existing scanner, see the [GitHub Setup guide](/integrations/scms/github) for a walkthrough using CodeQL (free for public repos). + +**Full setup guide:** [GitHub Integration →](/integrations/scms/github) + +--- + +## GitLab + +| Item | Detail | +| ----------------------- | ---------------------------------------------------------------------------------------------- | +| **Integration type** | Personal access token (service account recommended) | +| **Required scopes** | `api`, `read_user`, `read_repository`, `read_api`, `write_repository` | +| **What you need** | Maintainer or Owner role on target projects; Owner on parent group for group-level setup | +| **Instances supported** | GitLab SaaS (gitlab.com) and self-managed GitLab | +| **Scanner ingestion** | Automatic via GitLab Security Dashboard if you use GitLab SAST or other CI-integrated scanners | + +**Quick steps:** + +1. Create a GitLab personal access token for a dedicated service account with the required scopes. +2. Connect the token in Pixee's GitLab integration settings, providing your instance URL (for self-managed). +3. Choose which projects Pixee should analyze (all, member-only, or specific). + +**Full setup guide:** [GitLab Integration →](/integrations/scms/gitlab) + +--- + +## Azure DevOps + +| Item | Detail | +| ----------------------- | ---------------------------------------------------------------------------- | +| **Integration type** | Personal access token + optional webhook credentials | +| **Required scopes** | Full **Code** access (not "Full access") | +| **What you need** | Project Administrator or Project Collection Administrator on target projects | +| **Instances supported** | Azure DevOps Services (dev.azure.com) and Azure DevOps Server (on-premises) | +| **Scanner ingestion** | Via Azure Pipelines scanner integrations; SARIF upload supported | + +**Quick steps:** + +1. Create an Azure DevOps PAT for a dedicated service account with full Code access. +2. Connect the PAT and your organization name in Pixee's Azure DevOps integration settings. +3. Choose which projects and repositories to analyze. + +**Full setup guide:** [Azure DevOps Integration →](/integrations/scms/azure-devops) + +--- + +## Bitbucket + +| Item | Detail | +| ----------------------- | ------------------------------------------------------------------------------------------------------------- | +| **Integration type** | API token (Bitbucket Cloud) or repository access token | +| **Required scopes** | `read:user`, `read:workspace`, `read:repository`, `read:pullrequest`, `write:repository`, `write:pullrequest` | +| **What you need** | Admin on the target workspace (Cloud) or Project Admin (Server) | +| **Instances supported** | Bitbucket Cloud (bitbucket.org) and Bitbucket Data Center / Server | +| **Credentials** | Three values required: service account username, email address, and API token | +| **Scanner ingestion** | Via Bitbucket Pipelines scanner steps; SARIF upload supported | + +**Quick steps:** + +1. Create a Bitbucket Cloud API token for a dedicated service account. +2. Connect the token, username, and email address in Pixee's Bitbucket integration settings. +3. Choose which repositories in the workspace to analyze. + +**Full setup guide:** [Bitbucket Integration →](/integrations/scms/bitbucket) + +--- + +## After Connecting + +Once your SCM platform is connected: + +1. Pixee analyzes the default branch of each connected repository. +2. Scanner findings are ingested automatically (or via SARIF upload for scanners outside your SCM's native security surface). +3. Pixee opens fix pull requests for actionable findings — typically within the first hour. + +**Next step:** [Your First Fix →](/getting-started/first-fix) + +To customize behavior (branch targeting, severity filters, excluded paths), create a [PIXEE.yaml](/configuration/pixee-yaml) file in your repository root. + +Need enterprise deployment (self-hosted, air-gapped, BYOM)? See [Enterprise Deployment Options](/enterprise/deployment). diff --git a/docs/installing.md b/docs/installing.md deleted file mode 100644 index 2fade116..00000000 --- a/docs/installing.md +++ /dev/null @@ -1,48 +0,0 @@ ---- -sidebar_position: 2 ---- - -# Installing - -Pixee connects to your repositories and scanning tools through the [Pixee platform](https://app.pixee.ai). -Installation steps vary depending on the SCM and code scanning tools in use. - -## Self-Hosted - -Pixee Enterprise Server enables self-hosted deployment for organizations with additional security or compliance requirements. Documentation is available upon request. To learn more about self-hosted solutions, please [contact us](https://pixee.ai/demo-landing-page). - -## Tool connections - -Pixee fixes problems detected by [your existing code scanning tools and services](/code-scanning-tools/overview). - -If you use GitHub Advanced Security (GHAS), then installing the Pixeebot GitHub App is sufficient for connecting Pixee to your GHAS results. - -Otherwise, you will need to connect Pixee to your code scanning tools and services, before Pixee can send fixes. If your repository does not use any code scanning tools and services, but you still want to try Pixee, see our guide for [adding Semgrep CLI and Pixee to your GitHub repository.](https://docs.pixee.ai/code-scanning-tools/semgrep) - -## Repository access - -During installation, you’ll need to specify which of your repositories Pixee can access. This can be done in one of two ways: - -- **All repositories -** By selecting this option, Pixee will monitor all your existing and future repositories. -- **Select repositories -** Opting for this choice will present you with a list of your current repositories. From there, you can choose the specific repositories Pixee can access. - -## Updating repository access - -To update repository access for Pixee: - -**From Pixee Dashboard:** - -- To add a new repository, navigate to your Repositories page, and click the "+Connect new" button to choose a repository connection method. - -Demo of Connect New button in the Pixee platform - -**From GitHub:** - -- Go to your GitHub homepage. -- Navigate to Settings > Integrations > Applications. -- Select "pixeebot" from the list of applications. -- Click the configure button to access Pixee settings. - -Repository access selection can be managed at any time by adjusting settings through either of these paths. diff --git a/docs/integrations/_category_.json b/docs/integrations/_category_.json new file mode 100644 index 00000000..c4a7a059 --- /dev/null +++ b/docs/integrations/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Integrations", + "position": 4, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "integrations/integrations-overview" + } +} diff --git a/docs/integrations/ci-cd.md b/docs/integrations/ci-cd.md new file mode 100644 index 00000000..b2b80bfd --- /dev/null +++ b/docs/integrations/ci-cd.md @@ -0,0 +1,217 @@ +--- +title: CI/CD Integration +slug: /integrations/ci-cd +track: dev +content_type: tutorial +seo_title: "Pixee CI/CD Integration | Automated Security Fixes in Your Pipeline" +description: How Pixee fits into a CI/CD pipeline. Covers SCM-driven ingestion, SARIF upload patterns, and platform-specific examples. +sidebar_position: 7 +--- + +Pixee fits into your CI/CD pipeline without adding a runtime fix step. Scanners run as they always have; their findings are ingested by the Pixee platform via your SCM integration (or via a SARIF upload to the SCM's code-scanning API), and Pixee opens fix pull requests asynchronously. Your pipeline does not block on Pixee, and your existing scanner steps, build steps, and deployment gates are untouched. + +## How Pixee Fits in Your Pipeline + +``` +[Build] → [Scan (SAST/SCA)] → [Deploy gate] + ↓ + Findings ingested by Pixee (via SCM integration) + ↓ + Triage + Fix PR opened on the repository (async) +``` + +Your scanner runs as it always has. Findings flow to Pixee through one of two paths: + +- **SCM-native ingestion.** Pixee's GitHub App, GitLab integration, Azure DevOps integration, or Bitbucket connector reads scanner findings from the platform's code-scanning surface (GHAS Code Scanning, GitLab Security Dashboard, etc.). No additional CI step is required. +- **SARIF upload.** For scanners that don't write to the platform's code-scanning surface, upload SARIF to the SCM's code-scanning API as a CI step. Pixee then ingests it through the SCM integration like any other finding. + +Pixee processes findings on the platform, not in your pipeline. Fix generation runs asynchronously and arrives as pull requests. Your existing branch protection rules, code review process, and CI checks apply to every Pixee PR exactly as they do to any human-authored change. + +**Pipeline time impact:** Zero or one additional step. If your scanner already publishes to the SCM's code-scanning API, no Pixee-specific step is needed. If you upload SARIF as a separate CI step, that step typically runs in seconds. + +## What Data Leaves Your Network + +This is the question teams ask first, and the answer depends on your deployment model. + +| Data Type | SaaS (Cloud) | Self-Hosted (Embedded Cluster / Helm) | Air-Gapped | +| ----------------------- | --------------------------------------------------- | ---------------------------------------------------------- | ----------------------------------------- | +| Scanner results (SARIF) | Sent to Pixee's service for triage | Stays in your cluster | Stays in your network | +| Source code context | Accessed via SCM integration (read-only) | Stays in your cluster | Stays in your network | +| Generated fixes | Created on Pixee's infrastructure, delivered as PRs | Created and delivered within your cluster | Created and delivered within your network | +| LLM inference | Pixee-managed | Your chosen provider (OpenAI, Azure AI Foundry, Anthropic) | Customer-hosted LLM endpoint | +| Telemetry | Anonymized usage metrics (opt-out available) | Configurable | None | + +**SaaS deployment.** Pixee's service accesses your repositories through the SCM integration (GitHub App, GitLab PAT, etc.) with read-only code access and write access limited to creating PRs. Scanner results are transmitted for triage analysis. Source code is not stored after analysis completes. + +**Self-hosted and air-gapped.** All data stays within your infrastructure. You control the LLM provider, the network boundary, and the storage. See [Enterprise Deployment Options](/enterprise/deployment) for embedded cluster, Helm, and air-gapped setup guides. + +## Integration Comparison + +| Platform | Common Pattern | Setup Time | Prerequisites | +| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | ------------------------------------------------------------------------------------------------- | +| **GitHub Actions** | Scanner publishes SARIF to GitHub Code Scanning; GHAS-native scanners (CodeQL) need no extra step | ~5 min | Pixee GitHub App installed ([setup guide](/getting-started/source-control#github)) | +| **GitLab CI** | GitLab SAST + Dependency Scanning are ingested natively; external scanners upload SARIF to GitLab's vulnerability API | ~10 min | GitLab integration configured ([setup guide](/getting-started/source-control#gitlab)) | +| **Azure Pipelines** | Scanner runs in pipeline; SARIF is uploaded via Azure DevOps Code Scanning or directly to Pixee | ~10 min | Azure DevOps integration configured ([setup guide](/getting-started/source-control#azure-devops)) | +| **Bitbucket Pipelines** | Scanner runs in pipeline; SARIF is uploaded to Pixee | ~10 min | Bitbucket connector configured ([setup guide](/getting-started/source-control#bitbucket)) | +| **Jenkins / other CI** | Scanner runs anywhere; the SCM-native path still applies if your scanner publishes to GitHub Code Scanning, GitLab Security Dashboard, etc. | varies | One of the four SCM integrations configured | + +Setup times are wall-clock time from "I have a pipeline" to "Pixee is processing scanner results." This does not include scanner setup — that is your existing infrastructure. + +## GitHub Actions + +Most teams add no Pixee-specific step. Scanners that publish to GitHub Code Scanning (CodeQL, Semgrep with the GitHub uploader, third-party scanners with `github/codeql-action/upload-sarif`) are ingested by Pixee through the GitHub App. + +```yaml +name: Security Scan + +on: + push: + branches: [main] + pull_request: + +jobs: + scan: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + # Your existing scanner step. + - name: Run CodeQL + uses: github/codeql-action/analyze@v3 +``` + +CodeQL writes findings directly to GitHub Code Scanning. Pixee's GitHub App reads them through the GHAS API and opens fix PRs. + +For scanners that don't write to Code Scanning natively, upload the SARIF afterwards: + +```yaml +- name: Run my scanner + run: my-scanner --format sarif > results.sarif + +- name: Upload SARIF to GitHub Code Scanning + uses: github/codeql-action/upload-sarif@v3 + with: + sarif_file: results.sarif +``` + +**Prerequisites:** Install the Pixee GitHub App ([GitHub Setup](/getting-started/source-control#github)). + +## GitLab CI + +GitLab SAST and Dependency Scanning are ingested natively — Pixee reads findings from GitLab's vulnerability API, no extra CI step is required: + +```yaml +include: + - template: Security/SAST.gitlab-ci.yml + - template: Security/Dependency-Scanning.gitlab-ci.yml + +stages: + - build + - test + - scan +``` + +For external scanners, run them in CI and emit GitLab-compatible reports (or upload SARIF to GitLab's security dashboard via the security report artifacts). Pixee picks them up through the same GitLab integration. + +**Prerequisites:** Configure the GitLab integration with a service-account PAT ([GitLab Setup](/getting-started/source-control#gitlab)). + +**Self-hosted GitLab:** supported. Configure the custom base URI in the Pixee integration settings. + +## Azure Pipelines + +Run your scanner as a pipeline task and emit SARIF. The exact ingestion path depends on which scanner: scanners with Azure DevOps Code Scanning support publish there; others can upload SARIF directly to Pixee. + +```yaml +trigger: + - main + +pool: + vmImage: "ubuntu-latest" + +steps: + - task: UsePythonVersion@0 + inputs: + versionSpec: "3.11" + + # Your existing scanner step. + - script: | + pip install semgrep + semgrep --config auto --sarif -o $(Build.ArtifactStagingDirectory)/results.sarif . + displayName: "Run Scanner" +``` + +After the scanner publishes results to your repository's code-scanning surface (or to Pixee directly), the Pixee Azure DevOps integration ingests them and opens fix PRs. + +**Prerequisites:** Configure the Azure DevOps integration ([Azure DevOps Setup](/getting-started/source-control#azure-devops)). + +**Work-item linking:** If your organization requires linked work items on PRs, configure the work item ID in the Pixee integration settings. + +## Bitbucket Pipelines + +Run your scanner as a pipeline step and emit SARIF. Pixee's Bitbucket connector ingests SARIF results uploaded via the connector's reporting endpoint. + +```yaml +pipelines: + default: + - step: + name: Build and Test + script: + - npm install + - npm test + + - step: + name: Security Scan + script: + - pip install semgrep + - semgrep --config auto --sarif -o results.sarif . + artifacts: + - results.sarif +``` + +After the scan step, the SARIF file is available to the Pixee Bitbucket connector. Configuration of the upload step depends on your scanner — check the per-scanner integration page for specifics. + +**Prerequisites:** Configure the Bitbucket connector ([Bitbucket Setup](/getting-started/source-control#bitbucket)). Supports Bitbucket Cloud and Bitbucket Server. + +## Jenkins and Other CI Systems + +Pixee does not require a specific CI system. As long as the scanner can run _somewhere_ in your CI and findings reach the Pixee platform via one of the four SCM integrations, the rest of the pipeline is unchanged. + +Two common patterns: + +1. **Scanner writes to the SCM's code-scanning surface.** A Jenkins job runs the scanner, then uploads SARIF to GitHub Code Scanning / GitLab Security Dashboard / etc. via that platform's API. Pixee picks up the findings through the SCM integration. +2. **Scripted upload to Pixee.** A pipeline step uploads SARIF directly to the Pixee API. The [Pixee CLI](/api/cli)'s `pixee api` subcommand can POST a SARIF body, or you can use any HTTP client. + +```bash +# Example: upload SARIF directly to Pixee using the CLI in any CI environment. +brew tap pixee/pixee && brew install pixee # one-time, on a runner with brew +export PIXEE_TOKEN="$PIXEE_TOKEN" +export PIXEE_SERVER="https://pixee.example.com" + +pixee api /api/v1/scans \ + --method POST \ + --input results.sarif +``` + +Discover the exact upload endpoint for your deployment via HAL link traversal: `pixee api /api/v1` lists the available resources, and each resource's `_links` lead to its upload routes. + +**Prerequisites:** A Pixee API token (`PIXEE_TOKEN`) and the deployment URL (`PIXEE_SERVER`). For background on the CLI, see [Pixee CLI](/api/cli). + +## Scanner Result Ingestion + +Pixee accepts scanner results through three paths: + +1. **SCM-native APIs.** GitHub Code Scanning, GitLab vulnerability reports, Azure DevOps Code Scanning, Bitbucket reports. Pixee reads findings through the SCM integration. +2. **Direct SARIF upload to Pixee.** Use the [Pixee CLI](/api/cli) (`pixee api`) or an HTTP client. Useful when your CI system doesn't have a clean upload path to the SCM. +3. **Native scanner integrations.** For named scanners (CodeQL, Semgrep, Checkmarx, Veracode, Snyk Code, SonarQube, AppScan, Polaris, Fortify, Contrast, GitLab SAST, GitLab SCA, Trivy, and others) Pixee uses dedicated handlers that extract scanner-specific metadata for richer triage. See the per-scanner pages under [Integrations](/integrations/overview). + +**Universal SARIF.** Any SARIF-producing scanner works through the universal SARIF integration. See [Universal SARIF Integration](/integrations/sarif-universal). + +## Troubleshooting + +**Scanner findings not reaching Pixee.** Verify the SCM integration's read access to code-scanning results. For GitHub, confirm the App has `code_scanning_alerts: read`. For GitLab, confirm the PAT has `read_api`. For Azure DevOps and Bitbucket, confirm the credentials authorize reading the security/reports endpoints. + +**SARIF parsing errors.** Confirm the SARIF file is valid and conforms to the SARIF standard. Validate it is valid JSON. Most scanner export options include a SARIF format flag — check your scanner's documentation. + +**Fix PRs not appearing.** Check that the Pixee integration has write access to the target repository. For GitHub, the App needs `pull_requests: write`. Fix generation is asynchronous — allow a few minutes after findings are ingested. + +**`pixee api` returns exit code 2.** Authentication failed. Run `pixee auth status` to confirm the configured server and token, or reset both with `pixee auth login`. See [Pixee CLI](/api/cli) for credential resolution rules. diff --git a/docs/integrations/integrations-overview.md b/docs/integrations/integrations-overview.md new file mode 100644 index 00000000..e6bdd339 --- /dev/null +++ b/docs/integrations/integrations-overview.md @@ -0,0 +1,84 @@ +--- +title: "Integrations Overview & Coverage Matrix" +slug: /integrations/overview +track: both +content_type: guide +seo_title: "Pixee Integrations: Scanners, SCMs, and Universal SARIF" +description: Coverage matrix for Pixee integrations. Natively integrated scanners, 4 SCM platforms, and universal SARIF support. +sidebar_position: 1 +--- + +# Integrations Overview & Coverage Matrix + +Pixee integrations fall into two categories. **Scanning Tools** are the SAST, SCA, IAST, and aggregation platforms that produce findings — Pixee triages each finding and generates fixes. **Source Control** platforms are where Pixee delivers those fixes as pull requests or merge requests. Pixee does not replace your scanners or your SCM; it sits downstream of detection and inside your existing review workflow. + +One triage-and-remediation pipeline spans every scanner in your stack, regardless of vendor. Pixee adds the resolution layer; the rest of your stack stays as it is. + +## Source Control Coverage + +Pixee delivers remediation as pull requests (or merge requests) on the four major development platforms. All four support cloud and self-hosted/on-premises deployments via Pixee Enterprise Server. + +| Platform | PR/MR Delivery | Authentication | Setup Guide | +| ----------------------------------------------- | --------------------- | --------------------- | ----------------------------------------------------------- | +| [GitHub](/integrations/scms/github) | Native pull requests | GitHub App | [Get started](/getting-started/source-control#github) | +| [GitLab](/integrations/scms/gitlab) | Native merge requests | Personal access token | [Get started](/getting-started/source-control#gitlab) | +| [Azure DevOps](/integrations/scms/azure-devops) | Native pull requests | PAT + webhooks | [Get started](/getting-started/source-control#azure-devops) | +| [Bitbucket](/integrations/scms/bitbucket) | Native pull requests | API token | [Get started](/getting-started/source-control#bitbucket) | + +## Scanner Coverage Matrix + +Pixee provides a growing list of named scanner integrations plus universal SARIF support for any other tool. Every scanner's findings flow through the same triage and remediation pipeline; the only difference is the depth of metadata extraction. + +| Scanner | Integration Tier | Finding Types | Triage | Remediation | Input Method | +| --------------------------------------------------------------------- | ---------------- | -------------- | ------ | ----------- | ---------------- | +| [CodeQL](/integrations/scanners/codeql) | Deep | SAST | Yes | Yes | GHAS API / SARIF | +| [Semgrep](/integrations/scanners/semgrep) | Deep | SAST | Yes | Yes | SARIF | +| [Checkmarx](/integrations/scanners/checkmarx) | Deep | SAST | Yes | Yes | SARIF | +| [Veracode](/integrations/scanners/veracode) | Native | SAST | Yes | Yes | SARIF | +| [Snyk Code](/integrations/scanners/snyk-code) | Native | SAST | Yes | Yes | SARIF | +| [SonarQube / SonarCloud](/integrations/scanners/sonarqube) | Native | SAST | Yes | Yes | SARIF | +| [HCL AppScan](/integrations/scanners/appscan) | Native | SAST | Yes | Yes | SARIF | +| [Polaris / Black Duck (Coverity)](/integrations/scanners/polaris) | Native | SAST | Yes | Yes | SARIF | +| [Fortify](/integrations/scanners/fortify) | Native | SAST | Yes | Yes | SARIF | +| [Contrast Security](/integrations/scanners/contrast) | Native | IAST | Yes | Yes | SARIF | +| [GitLab SAST](/integrations/scanners/gitlab-sast) | Native | SAST | Yes | Yes | GitLab API | +| [GitLab SCA (Dependency Scanning)](/integrations/scanners/gitlab-sca) | Native | SCA | Yes | Yes | GitLab API | +| [Trivy](/integrations/scanners/trivy) | Native | SAST, SCA, IaC | Yes | Yes | SARIF | +| [Arnica](/integrations/scanners/arnica) | Native | SAST | Yes | Yes | SARIF | +| [Datadog SAST](/integrations/scanners/datadog-sast) | Native | SAST | Yes | Yes | SARIF | +| [DefectDojo](/integrations/scanners/defectdojo) | Aggregator | Aggregated | Yes | Yes | SARIF | +| [Any SARIF-producing scanner](/integrations/sarif-universal) | Universal | Varies | Yes | Yes | SARIF | + +**Integration tiers explained:** + +- **Deep:** Dedicated handler with scanner-specific metadata extraction. Extracts dataflow paths, rule descriptions, and scanner-specific context for higher triage accuracy. +- **Native:** Recognized scanner with tool identification and standard SARIF processing. Findings are fully triaged and remediated through the standard pipeline. +- **Aggregator:** Vulnerability management platforms that consolidate findings from many scanners. Pixee adds triage and remediation on top. +- **Universal SARIF:** Any tool that produces SARIF output works automatically. No pre-built integration required. + +All tiers feed into the same downstream triage and remediation pipeline. Deep integrations provide richer context; universal SARIF ensures no scanner is locked out. + +## How Scanner Integration Works + +Pixee's scanner integration follows a two-tier architecture that balances depth with breadth. + +**Tier 1 — Native Handlers.** For the most widely deployed scanners, Pixee has dedicated handlers that extract scanner-specific metadata. Each handler understands the idiosyncrasies of that tool's SARIF output — where rule descriptions live, whether dataflow traces (codeFlows) are available, and what metadata the scanner includes or omits. Better metadata extraction means higher triage accuracy. + +**Tier 2 — Universal SARIF.** For any scanner that produces SARIF (the OASIS standard for static analysis results), Pixee's universal SARIF engine ingests findings automatically. No pre-built integration required. The system dynamically adapts its handling strategy based on whatever metadata the SARIF contains. + +Both tiers feed into the same downstream pipeline: + +``` +Scanner runs > SARIF output > Pixee ingests > Triage pipeline > TP / FP / WONT_FIX > Remediation PRs +``` + +The result: one triage and remediation pipeline across every scanner in your stack, from CodeQL to your internal proprietary scanner — all through the same workflow. + +**Why SARIF matters.** SARIF (Static Analysis Results Interchange Format) is the OASIS open standard for static analysis results. Pixee supports the current SARIF standard. Most modern SAST, SCA, and secret-scanning tools produce SARIF output natively or via converters. By standardizing on SARIF as the ingestion format, Pixee ensures that any scanner — commercial, open source, or proprietary — can feed into the triage and remediation pipeline without custom integration work. + +**What this means in practice:** + +- Internal or proprietary scanners that output SARIF work on day one +- New commercial scanners are supported immediately if they produce SARIF +- You are never locked to a specific tool list +- Adding or removing a scanner from your stack does not require any Pixee configuration changes diff --git a/docs/integrations/sarif-universal.md b/docs/integrations/sarif-universal.md new file mode 100644 index 00000000..72e3eb94 --- /dev/null +++ b/docs/integrations/sarif-universal.md @@ -0,0 +1,94 @@ +--- +title: Universal SARIF Integration +slug: /integrations/sarif-universal +track: both +content_type: guide +seo_title: Universal SARIF Integration with Pixee +description: Connect any SARIF-producing scanner to Pixee for automated triage and remediation. Covers SARIF format requirements and upload methods. +sidebar_position: 2 +--- + +# Universal SARIF Integration + +Pixee's Universal SARIF integration accepts findings from any security scanner that produces SARIF output. This means you are not limited to Pixee's natively integrated scanners — if your tool can export SARIF, Pixee can triage and remediate its findings. Universal SARIF is how Pixee stays scanner-agnostic: your choice of detection tools is independent of your choice of resolution platform. + +This page covers the SARIF format requirements, upload methods, what metadata Pixee extracts, and the differences between Universal SARIF and native integrations. + +## When to Use Universal SARIF + +Use Universal SARIF when: + +- Your scanner is not in Pixee's [native integration list](/integrations/overview) +- You use a proprietary or custom-built scanner +- You aggregate findings from multiple tools through a central platform that exports SARIF +- You want to evaluate Pixee with a scanner before requesting a native integration + +Use a native integration when available — native integrations extract richer metadata and provide deeper triage context than Universal SARIF. + +## SARIF Requirements + +Pixee supports SARIF version 2.1.0. At minimum, each finding must include a `ruleId`, `message.text`, and a `physicalLocation` (file path and line number). Richer SARIF — particularly `codeFlows` with `threadFlows` — directly improves triage accuracy and fix quality. + +For the complete field reference, required vs. optional field breakdown, dataflow quality tiers, and validation guidance, see the [SARIF Reference](/api/sarif). + +## Upload Methods + +### CI/CD Pipeline Upload + +Upload SARIF as a step in your CI/CD pipeline after your scanner runs: + +```yaml +# Example: GitHub Actions +- name: Upload SARIF to Pixee + run: | + curl -X POST \ + -H "Authorization: Bearer $PIXEE_TOKEN" \ + -H "Content-Type: application/sarif+json" \ + -d @results.sarif \ + https://api.pixee.ai/v1/sarif/upload +``` + +### Platform-Native Upload + +If your scanner integrates with GitHub Code Scanning, GitLab Security Dashboard, or Azure DevOps, Pixee can ingest SARIF through the platform's native security findings API. + +### Manual Upload + +For evaluation or one-time use, upload SARIF files through the Pixee dashboard. + +## What Pixee Extracts from SARIF + +| SARIF Element | What Pixee Does With It | +| ---------------------------- | ---------------------------------------------------------- | +| `ruleId` | Maps to known vulnerability patterns for codemod selection | +| `message.text` | Provides context for AI-powered triage and fix generation | +| `physicalLocation` | Identifies the file and line to analyze and fix | +| `codeFlows` | Enables source-to-sink exploitability analysis | +| `level` (error/warning/note) | Informs triage prioritization | +| `rules[].help` | Provides vulnerability description for fix context | +| `properties` | Custom metadata (e.g., CWE, CVSS) for enriched triage | + +## Native vs. Universal SARIF + +| Dimension | Native Integration | Universal SARIF | +| ------------------- | ------------------------------------------------------- | ----------------------------------------------------- | +| Metadata extraction | Scanner-specific handler extracts maximum context | Relies on what SARIF contains | +| Triage depth | Full exploitability analysis with scanner-aware context | Exploitability analysis with available SARIF metadata | +| Fix coverage | Scanner-specific codemod dispatchers | Generic codemod matching by rule ID and CWE | +| Setup | One-click via platform integration | SARIF upload configuration required | +| Maintenance | Pixee maintains handler compatibility | You maintain SARIF export compatibility | + +**Recommendation:** Use native integrations when available. Use Universal SARIF for scanners without native support or for evaluation. + +## Supported SARIF Producers + +Any scanner producing valid SARIF output works with Universal SARIF. Scanners known to produce compatible output include: + +- ESLint (with SARIF formatter) +- Psalm +- PHPStan +- Bandit (Python) +- Gosec (Go) +- Brakeman (Ruby) +- Custom scanners with SARIF export +- Security platforms with SARIF aggregation (DefectDojo, GitHub Code Scanning, etc.) diff --git a/docs/integrations/scanners/_category_.json b/docs/integrations/scanners/_category_.json new file mode 100644 index 00000000..4179a4dd --- /dev/null +++ b/docs/integrations/scanners/_category_.json @@ -0,0 +1,9 @@ +{ + "label": "Scanning Tools", + "position": 4, + "collapsible": true, + "collapsed": false, + "link": { + "type": "generated-index" + } +} diff --git a/docs/integrations/scanners/appscan.md b/docs/integrations/scanners/appscan.md new file mode 100644 index 00000000..a73204d4 --- /dev/null +++ b/docs/integrations/scanners/appscan.md @@ -0,0 +1,119 @@ +--- +title: HCL AppScan Integration +slug: /integrations/scanners/appscan +track: both +content_type: guide +seo_title: HCL AppScan Integration with Pixee +description: Pixee integration with HCL AppScan for automated triage and remediation, with custom trace format handling. +sidebar_position: 1 +--- + +# HCL AppScan Integration + +Pixee integrates natively with HCL AppScan to triage SAST findings and deliver remediation as pull requests. The dedicated AppScan handler includes a custom code flow mapper that preserves AppScan's unique trace format for accurate triage decisions. + +## What AppScan Detects + +HCL AppScan (formerly IBM AppScan) is an enterprise application security testing suite widely deployed in financial services, insurance, and government. HCL acquired AppScan from IBM in 2019, and the product continues to serve organizations that have standardized on it for decades. + +AppScan detects: + +- **Static Application Security Testing (SAST)** -- source code analysis for injection flaws, cross-site scripting, authentication issues, and cryptographic weaknesses +- **Dynamic Application Security Testing (DAST)** -- runtime vulnerability scanning of web applications +- **Interactive Application Security Testing (IAST)** -- combined static and dynamic approaches +- **Software Composition Analysis (SCA)** -- open-source dependency vulnerabilities +- **API security testing** + +AppScan offers on-premises (AppScan Source, AppScan Enterprise) and cloud-hosted (AppScan on Cloud) deployment models. + +## How Pixee Enhances AppScan + +### Triage + +AppScan findings are processed through Pixee's triage pipeline with dedicated handling for AppScan's unique output format. + +**Custom code flow mapper.** AppScan structures its SARIF output differently from most scanners, particularly in how it represents code traces and data flows. Pixee's AppScan handler includes a custom code flow mapper that translates AppScan's SARIF structure into the format the triage engine expects, preserving trace information that would otherwise be lost. This trace preservation is what allows the triage engine to make accurate decisions about findings that involve multi-step data flows -- which is where most false positives originate. + +AppScan-specific severity levels are extracted and mapped appropriately, ensuring that the triage engine interprets each finding's risk in the context AppScan intended. + +### Remediation + +True positive findings receive automated code fixes delivered as pull requests. AppScan has dedicated tool-specific codemods in the remediation engine, meaning fixes are generated with awareness of the specific finding types and patterns AppScan reports. + +Fixes use deterministic codemods and AI-powered fixes. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Provision an AppScan API key** with permission to post comments on issues. The Key ID and Key Secret authorize Pixee to read findings and post triage comments back. +2. **Configure AppScan credentials** in Pixee. The fields are: AppScan Base URI (defaults to `https://cloud.appscan.com`), Key ID, Key Secret, and webhook authentication credentials. For Pixee Enterprise (Helm), values live under `platform.pixeebot.appscan.{apiKeyId, apiKeySecret, webhook.user, webhook.password}`. For embedded-cluster Enterprise, the admin console exposes these fields under **Config → Security Tool → AppScan**. +3. **Choose webhook authentication mode.** Two options: + - **Basic Auth (recommended)** — username and password for HTTP Basic auth on inbound webhook requests. Configure the username and password in Pixee, then use them when registering the webhooks in AppScan (see below). + - **Webhook secret (deprecated)** — a shared secret embedded in the webhook URL path. Supported but not recommended. +4. **Configure two webhooks in AppScan** (see [Webhook Configuration](#webhook-configuration) below) so AppScan notifies Pixee when scans complete and when patch requests are created. +5. **Connect your code repository** to Pixee (GitHub, GitLab, Azure DevOps, or Bitbucket — see [Source Control](/integrations/overview#source-control-coverage)). +6. **Pixee ingests AppScan findings** and processes them through the triage and remediation pipeline. +7. **Review and merge** Pixee-generated PRs in your normal development workflow. + +**Prerequisites:** HCL AppScan with SAST scan results, an API key with comment-posting permissions, Pixee account with connected repository. + +### Webhook Configuration + +AppScan needs two webhooks pointed at your Pixee instance: one for scan-completion events, one for patch-request events. Both are created via the AppScan Webhook API on your AppScan presence server. + +**Generate the Basic Auth header.** Encode the webhook user and password configured in Pixee: + +```bash +echo -n "username:password" | base64 +# -> dXNlcm5hbWU6cGFzc3dvcmQ= +``` + +Prepend `Basic ` to form the full header value (e.g., `Basic dXNlcm5hbWU6cGFzc3dvcmQ=`). + +**Webhook 1 — Scan Execution Completed.** Notifies Pixee when an AppScan scan finishes: + +```json +{ + "AuthorizationHeader": "Basic ", + "PresenceId": "", + "Uri": "https:///api/v1/integrations/appscan-default/webhooks/_/ScanExecutionCompleted/{SubjectId}", + "Global": true, + "AssetGroupId": "", + "Event": "ScanExecutionCompleted" +} +``` + +**Webhook 2 — New Patch Request.** Notifies Pixee when a patch is requested: + +```json +{ + "AuthorizationHeader": "Basic ", + "PresenceId": "", + "Uri": "https:///api/v1/integrations/appscan-default/webhooks/CreatePatch", + "Global": true, + "AssetGroupId": "", + "Event": "NewPatchRequest", + "RequestMethod": "POST", + "RequestBody": "{\"patch_id\": \"{SubjectId}\"}", + "ContentType": "application/json" +} +``` + +Replace the placeholders: + +- `` — the Base64 string from the encoding step above +- `` — your AppScan presence server ID +- `` — your Pixee Enterprise hostname +- `` — your AppScan asset group ID + +For details on AppScan's webhook API, see HCL's [AppScan Webhook API Documentation](https://cloud.appscan.com/swagger/index.html#/Webhooks/Webhooks_Create). + +## Common False Positive Patterns Pixee Eliminates + +- **Trace-based false positives:** AppScan's SAST traces flag data flows that are actually protected by intermediate sanitization or validation -- Pixee's custom code flow mapper preserves the full trace for accurate investigation +- **Severity inflation in low-risk contexts:** AppScan assigns high severity to findings in test code, internal APIs, and admin-only endpoints; Pixee adjusts classification based on code context +- **Framework-protected patterns:** Findings in code protected by application framework security controls that AppScan's static analysis cannot resolve +- **Duplicate findings across SAST and DAST:** When teams use both AppScan SAST and DAST, the same vulnerability may appear from both testing methods; Pixee's unified pipeline helps deduplicate + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/arnica.md b/docs/integrations/scanners/arnica.md new file mode 100644 index 00000000..cc655fe8 --- /dev/null +++ b/docs/integrations/scanners/arnica.md @@ -0,0 +1,37 @@ +--- +title: Arnica Integration +slug: /integrations/scanners/arnica +track: both +content_type: guide +seo_title: Arnica Integration with Pixee +description: Pixee integration with Arnica for automated triage and remediation of SAST findings. +sidebar_position: 15 +--- + +# Arnica Integration + +Pixee integrates with Arnica to triage SAST findings and deliver remediation as pull requests. Arnica's continuous security scanning surfaces code vulnerabilities across your repositories; Pixee adds the triage layer to separate exploitable findings from noise, and the remediation layer to deliver validated fixes. + +## How Pixee Enhances Arnica + +### Triage + +Arnica findings flow through Pixee's triage pipeline, which classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with code-level justification. The triage engine investigates the actual codebase — checking dataflow, security controls, and context — rather than relying on the rule match alone. + +Each classification includes a structured justification suitable for audit documentation. Security teams can review triage decisions, not just raw scanner output. + +### Remediation + +Confirmed vulnerabilities receive automated code fixes delivered as pull requests. Pixee generates fixes using deterministic codemods for known vulnerability patterns and AI-powered fixes for complex or codebase-specific cases. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Connect your code repository to Pixee** via the appropriate platform integration — see [Connect Source Control](/getting-started/source-control) for GitHub, GitLab, Azure DevOps, and Bitbucket. +2. **Configure Arnica to export findings in SARIF format** and deliver them to Pixee via the SARIF upload endpoint or CI/CD pipeline step. +3. **Review and merge** Pixee-generated PRs in your normal workflow. + +**Prerequisites:** Arnica configured for your repositories, Pixee connected to your SCM platform. + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/checkmarx.md b/docs/integrations/scanners/checkmarx.md new file mode 100644 index 00000000..aa865adc --- /dev/null +++ b/docs/integrations/scanners/checkmarx.md @@ -0,0 +1,68 @@ +--- +title: Checkmarx Integration +slug: /integrations/scanners/checkmarx +track: both +content_type: guide +seo_title: Checkmarx Integration with Pixee +description: Pixee integration with Checkmarx for automated triage and remediation, including adaptive handling for metadata-sparse SARIF. +sidebar_position: 2 +--- + +# Checkmarx Integration + +Pixee's Checkmarx integration triages CxSAST and CxOne findings and delivers remediation as pull requests -- even when Checkmarx SARIF exports contain minimal metadata. The dedicated Checkmarx handler compensates for sparse output by re-deriving context directly from the codebase, and includes Checkmarx-specific codemods for SQL and NoSQL injection. + +## What Checkmarx Detects + +Checkmarx (CxSAST and CxOne) is an enterprise SAST platform widely deployed in regulated industries including financial services, healthcare, and government. + +Checkmarx detects: + +- **SQL injection, XSS, path traversal, and authentication flaws** via deep static analysis +- **Broad CWE coverage** through commercial rule sets maintained by Checkmarx +- **Cross-language vulnerabilities** across many programming languages +- **Compliance-relevant findings** aligned with industry standards (OWASP, SANS, PCI DSS) + +Checkmarx is known for thorough analysis with broad CWE coverage. It is also known for high false positive rates that require extensive manual tuning -- a pain point that grows with codebase scale and scanner deployment breadth. + +## How Pixee Enhances Checkmarx + +### Triage + +Checkmarx findings are processed through Pixee's triage pipeline, which classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with code-level justification. + +The dedicated Checkmarx handler addresses a challenge unique to Checkmarx: metadata-sparse SARIF output. + +**Adaptive handling for metadata-poor SARIF.** This is the key technical differentiator of the Checkmarx integration. Checkmarx's SARIF exports are notably sparse compared to other scanners -- minimal rule descriptions, no codeFlows, limited context about what the finding means or why it was flagged. Most downstream tooling struggles with this because triage accuracy depends on understanding the finding, not just its location. + +Pixee's handler compensates. When Checkmarx SARIF provides minimal metadata, the adaptive triage pipeline re-derives context directly from the codebase. Rather than relying on the scanner to explain the finding, the system examines the actual code at the finding location, understands the surrounding context, and makes a triage decision based on what the code does -- not on what the scanner's sparse output says. + +The result: Pixee's triage accuracy does not degrade when the scanner provides minimal context. Teams get the same quality of triage decisions regardless of how much metadata Checkmarx includes in its SARIF export. + +### Remediation + +True positive findings receive automated code fixes delivered as pull requests. + +Pixee includes Checkmarx-specific remediation codemods alongside its general-purpose codemod library and AI-powered fixes. Fixes match your team's code conventions. Developers review and merge Pixee PRs through their standard workflow. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Export Checkmarx findings in SARIF format** from CxSAST or CxOne. +2. **Connect your code repository to Pixee** via the appropriate platform integration (GitHub, GitLab, Azure DevOps, or Bitbucket). +3. **Upload Checkmarx SARIF** to Pixee (via CI/CD pipeline or direct upload). +4. **Pixee ingests and processes findings** through the triage and remediation pipeline -- compensating for sparse metadata automatically. +5. **Review and merge** Pixee-generated PRs in your normal workflow. + +**Prerequisites:** Checkmarx CxSAST or CxOne license with SARIF export capability, Pixee connected to your SCM platform. + +## Common False Positive Patterns Pixee Eliminates + +- **SQL injection on parameterized code:** Findings flagged on code that already uses parameterized queries or ORM frameworks +- **XSS with framework-level encoding:** Findings where framework auto-escaping is present (React JSX, Django template engine, Angular sanitization) +- **Tuning-dependent suppressions:** Findings that would require manual Checkmarx tuning to suppress -- Pixee's triage handles this automatically with code-level justification +- **Test code at production severity:** Test fixtures and example files flagged alongside production code +- **Context-poor findings:** Findings where Checkmarx's sparse SARIF metadata makes manual review difficult -- Pixee re-derives context from the actual codebase + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/codeql.md b/docs/integrations/scanners/codeql.md new file mode 100644 index 00000000..e8b90b11 --- /dev/null +++ b/docs/integrations/scanners/codeql.md @@ -0,0 +1,72 @@ +--- +title: CodeQL Integration +slug: /integrations/scanners/codeql +track: both +content_type: guide +seo_title: CodeQL Integration with Pixee +description: Pixee integration with CodeQL for automated triage and remediation of GitHub Advanced Security findings. +sidebar_position: 3 +--- + +# CodeQL Integration + +Pixee's CodeQL integration ingests findings from GitHub Advanced Security, triages each one with code-level justification, and delivers remediation as pull requests. The dedicated CodeQL handler extracts dataflow paths (codeFlows), giving the triage engine full source-to-sink context -- not just the final finding location. + +## What CodeQL Detects + +CodeQL is GitHub's SAST engine, included with GitHub Advanced Security (GHAS). It performs deep semantic analysis to identify security vulnerabilities and code quality issues across your codebase. + +CodeQL detects: + +- **Dataflow vulnerabilities** -- SQL injection, cross-site scripting (XSS), path traversal, and other injection flaws with full source-to-sink traces +- **Security misconfigurations** -- insecure defaults, missing security headers, weak cryptographic settings +- **Code quality issues flagged as security-relevant** by CodeQL's query suites + +CodeQL supports JavaScript, TypeScript, Python, Java, C/C++, C#, Go, Ruby, and Swift. + +## How Pixee Enhances CodeQL + +### Triage + +CodeQL findings are processed through Pixee's triage pipeline, which classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with a detailed, code-level justification. + +The dedicated CodeQL handler provides deeper analysis than standard SARIF ingestion. Here is what it extracts and why it matters: + +**codeFlows extraction.** CodeQL's SARIF output includes multi-step dataflow traces showing how data moves from a source (user input, external data) through intermediate steps to a sink (database query, HTML output). Pixee's handler extracts these complete codeFlows paths and passes them to the triage engine. The result: the triage decision considers the full data journey, not just the line where CodeQL flagged the finding. This distinction matters because a finding at line 47 might look dangerous in isolation but is provably safe when you see the sanitization at line 23. + +**Non-standard SARIF handling.** CodeQL stores rule metadata on `tool.extensions` rather than `driver` -- a quirk that differs from how most other scanners structure their SARIF output. Pixee's handler accounts for this automatically, extracting `help.markdown` from rule metadata for rich vulnerability descriptions. Teams do not need to preprocess or normalize CodeQL SARIF before Pixee ingests it. + +**Graceful fallback.** Real-world CodeQL output varies across versions and configurations. The handler degrades gracefully when SARIF fields like `full_description` are absent, maintaining triage coverage without manual intervention. + +Each finding receives a classification with confidence score and audit-ready reasoning trail. Security teams review the triage output, not the raw scanner noise. + +### Remediation + +True positive findings receive automated code fixes delivered as pull requests. + +Pixee generates fixes using a combination of deterministic codemods and AI-powered fixes for complex, codebase-specific scenarios. Every fix goes through multi-layer validation before reaching a developer's review queue. + +- Pre-configured handlers cover common CodeQL rules +- Fixes match your team's code conventions -- naming patterns, preferred libraries, existing security utilities +- Developers review and merge Pixee PRs through the standard GitHub workflow + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Enable CodeQL scanning** in your GitHub repository via GitHub Advanced Security. +2. **Install the Pixee GitHub App** on your organization or selected repositories. +3. **Pixee automatically ingests CodeQL findings** via the GHAS API or SARIF upload -- no manual export required. +4. **Configure triage preferences** in `PIXEE.yaml` (optional) to tune classification behavior. +5. **Review and merge** Pixee-generated PRs in your normal GitHub workflow. + +**Prerequisites:** GitHub Advanced Security license, Pixee GitHub App installed. + +## Common False Positive Patterns Pixee Eliminates + +- **Sanitized sinks:** Dataflow traces that terminate in sinks protected by framework-level sanitization (CodeQL cannot always resolve sanitization applied by middleware or security libraries) +- **Informational findings:** Security-relevant code quality findings that are informational, not exploitable in the actual runtime environment +- **Test code at production severity:** Findings in test fixtures, example code, and documentation snippets flagged at production severity levels +- **Low-precision rules in specific contexts:** Rules with high recall but low precision in certain language or framework configurations + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/contrast.md b/docs/integrations/scanners/contrast.md new file mode 100644 index 00000000..d2626a85 --- /dev/null +++ b/docs/integrations/scanners/contrast.md @@ -0,0 +1,74 @@ +--- +title: Contrast Security Integration +slug: /integrations/scanners/contrast +track: both +content_type: guide +seo_title: Contrast Security (IAST) Integration with Pixee +description: Pixee integration with Contrast Security IAST for automated triage and remediation of runtime-detected vulnerabilities. +sidebar_position: 4 +--- + +# Contrast Security Integration + +Pixee ingests Contrast Security findings, triages each one, and delivers remediation as pull requests. Contrast's runtime instrumentation produces a different signal than purely static scanners, and Pixee processes those findings through the same triage and remediation pipeline used for SAST tools. + +## What Contrast Detects + +Contrast Security uses Interactive Application Security Testing (IAST) -- runtime instrumentation that observes application behavior to identify vulnerabilities as code executes. Contrast Assess runs as an agent inside the application, watching real requests and the data flows they trigger. + +Contrast detects: + +- **Injection flaws** -- SQL injection, command injection, LDAP injection, NoSQL injection, observed against live traffic +- **Cross-site scripting (XSS)** -- reflected, stored, and DOM-based variants +- **Authentication and session weaknesses** -- including weak randomness, insecure cookies, and missing security headers +- **Insecure deserialization** +- **Path traversal** +- **Cryptographic weaknesses** -- weak algorithms, hardcoded keys, insecure modes +- **Vulnerable open-source dependencies** (via Contrast SCA) + +Because Contrast observes runtime behavior, it tends to surface findings with higher confidence than static scanners and can confirm exploitability for some classes of vulnerabilities. Contrast typically deploys in dev, QA, or staging environments where instrumentation overhead is acceptable. + +## How Pixee Enhances Contrast + +### Triage + +Contrast findings are processed through Pixee's triage pipeline alongside findings from SAST scanners. Each finding receives a classification with code-level justification. + +Runtime-confirmed findings carry a higher prior toward true-positive classification than equivalent static findings, but Pixee still validates each one in code context. Triage focuses on whether the runtime-observed vulnerability: + +- Is actually reachable in the deployed code paths (not just present) +- Lacks effective remediation upstream of the sink +- Maps to source code the team controls (versus a dependency that requires a different remediation strategy) + +The result: security teams can act on Contrast findings with the same confidence they get from Pixee's other scanner integrations. + +### Remediation + +True-positive findings receive automated code fixes delivered as pull requests, generated by Pixee's deterministic codemods and AI-powered fixes. Fixes match the team's code conventions and existing security utilities. + +Developers review and merge Pixee PRs through the standard development workflow. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +Pixee ingests Contrast findings via the [pixee/upload-tool-results-action](https://github.com/pixee/upload-tool-results-action) GitHub Action, which synchronizes Contrast results with Pixee. + +1. **Run Contrast** in your CI pipeline or runtime environment so findings are available. +2. **Export Contrast findings** to a Contrast-supported format (SARIF or Contrast's native JSON). +3. **Add the upload action** to your CI workflow: + - Configure with the path to your exported findings file + - Provide your Pixee API token as a secret +4. **Pixee ingests the upload** and processes each finding through the triage and remediation pipeline. +5. **Review and merge** Pixee-generated PRs in your normal development workflow. + +**Prerequisites:** Contrast Assess deployed and producing findings, Pixee account with connected repository, GitHub/GitLab/ADO/Bitbucket integration enabled. + +## Common False Positive Patterns Pixee Eliminates + +- **Test-environment-only findings:** Vulnerabilities observed in staging or QA that do not exist in code paths reachable in production +- **Findings in third-party code:** Issues that map to dependencies rather than the team's source code -- routed to SCA-style remediation rather than direct code fixes +- **Sanitized sinks:** Runtime-observed flows that terminate in sinks with framework-level sanitization Contrast does not always resolve +- **Severity inflation:** Findings flagged at high severity that are gated behind authentication, internal APIs, or otherwise reduced-impact contexts + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/datadog-sast.md b/docs/integrations/scanners/datadog-sast.md new file mode 100644 index 00000000..532dafe5 --- /dev/null +++ b/docs/integrations/scanners/datadog-sast.md @@ -0,0 +1,37 @@ +--- +title: Datadog SAST Integration +slug: /integrations/scanners/datadog-sast +track: both +content_type: guide +seo_title: Datadog SAST Integration with Pixee +description: Pixee integration with Datadog Static Analysis for automated triage and remediation of SAST findings. +sidebar_position: 16 +--- + +# Datadog SAST Integration + +Pixee integrates with Datadog Static Analysis to triage findings and deliver remediation as pull requests. Datadog's SAST scanning surfaces code-level security issues alongside your observability data; Pixee adds triage to separate exploitable vulnerabilities from noise and remediation to deliver validated fixes as PRs. + +## How Pixee Enhances Datadog SAST + +### Triage + +Datadog Static Analysis findings flow through Pixee's triage pipeline, which classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with code-level justification. The triage engine investigates the actual codebase — evaluating dataflow, security controls, and surrounding context — rather than relying on the rule match alone. + +Teams running Datadog for observability and security in a unified platform can use Pixee to close the loop from finding detection to validated fix — without leaving the pull request workflow. + +### Remediation + +Confirmed vulnerabilities receive automated code fixes delivered as pull requests. Pixee generates fixes using deterministic codemods for known vulnerability patterns and AI-powered fixes for complex or codebase-specific cases. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Connect your code repository to Pixee** via the appropriate platform integration — see [Connect Source Control](/getting-started/source-control) for GitHub, GitLab, Azure DevOps, and Bitbucket. +2. **Configure Datadog Static Analysis to export SARIF output** and deliver it to Pixee via the SARIF upload endpoint or CI/CD pipeline step. +3. **Review and merge** Pixee-generated PRs in your normal workflow. + +**Prerequisites:** Datadog Static Analysis configured for your repositories, Pixee connected to your SCM platform. + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/defectdojo.md b/docs/integrations/scanners/defectdojo.md new file mode 100644 index 00000000..a6f48839 --- /dev/null +++ b/docs/integrations/scanners/defectdojo.md @@ -0,0 +1,46 @@ +--- +title: DefectDojo Integration +slug: /integrations/scanners/defectdojo +track: both +content_type: guide +seo_title: DefectDojo Integration with Pixee +description: Pixee integration with DefectDojo for automated triage and remediation of aggregated findings from multiple scanners. +sidebar_position: 5 +--- + +# DefectDojo Integration + +Pixee integrates with DefectDojo to triage aggregated findings and deliver remediation as pull requests. DefectDojo serves as the management layer — organizing and tracking findings — but does not triage for exploitability or generate code fixes. Pixee adds those two capabilities. Your DefectDojo instance continues operating as your centralized vulnerability tracker; Pixee acts on what DefectDojo organizes. + +DefectDojo is an open-source application vulnerability management platform that consolidates findings from multiple scanners. + +## What DefectDojo Does + +- **Aggregates findings** from multiple security scanners into a single view +- **Deduplicates findings** across tools and scan runs +- **Tracks vulnerability lifecycle** (open, verified, mitigated, closed) +- **Provides vulnerability metrics** and reporting +- **Supports import from 150+ scanner formats** + +## How Pixee Enhances DefectDojo + +### Triage + +DefectDojo aggregates findings from multiple scanners, but triaging is still manual — security teams review each finding to determine whether it is a real threat. Pixee automates this step with exploitability analysis, classifying each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with structured evidence. + +### Remediation + +DefectDojo tracks vulnerability status but does not generate code fixes. Pixee delivers fixes as pull requests for confirmed vulnerabilities, moving findings from "open" to "mitigated" with actual code changes. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Install Pixee** for your platform. +2. **Configure DefectDojo export** — export findings in SARIF format from DefectDojo. +3. **Connect to Pixee** — upload SARIF findings via Pixee's integration endpoint or configure automated export. +4. **Review and merge** — Pixee triages findings and opens PRs for remediable issues. + +**Prerequisites:** DefectDojo instance with findings imported, Pixee platform integration configured. + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/fortify.md b/docs/integrations/scanners/fortify.md new file mode 100644 index 00000000..2f3611a4 --- /dev/null +++ b/docs/integrations/scanners/fortify.md @@ -0,0 +1,51 @@ +--- +title: Fortify Integration +slug: /integrations/scanners/fortify +track: both +content_type: guide +seo_title: Fortify (OpenText / Micro Focus) Integration with Pixee +description: Pixee integration with Fortify SAST for automated triage and remediation. Reduces backlog burden in regulated and government environments. +sidebar_position: 6 +--- + +# Fortify Integration + +Pixee integrates with Fortify to triage SAST findings and deliver remediation as pull requests. Fortify is widely deployed in government, defense, and regulated industries where long-standing contracts make it the entrenched SAST tool — and where finding backlogs frequently accumulate faster than manual triage can keep pace. Pixee classifies findings by exploitability and generates the code fixes Fortify does not produce. Your Fortify scans continue running as configured. + +> Fortify has changed corporate hands over the years (HP → HPE → Micro Focus → OpenText). Pixee works with Fortify regardless of which logo is on your license agreement. + +## What Fortify Detects + +- OWASP Top 10 and CWE categories across 25+ programming languages +- Dataflow vulnerabilities with source-to-sink taint analysis +- Security misconfigurations +- Quality and reliability issues flagged as security-relevant +- Custom rule support for organization-specific patterns + +Fortify produces SARIF output via its FPR-to-SARIF conversion tools, enabling integration with downstream platforms. + +## How Pixee Enhances Fortify + +### Triage + +Fortify findings in government and financial services environments often accumulate into large backlogs because manual triage cannot keep pace with scan volume. Pixee's triage pipeline classifies each finding by exploitability, reducing the manual review burden. + +Fortify's rich dataflow analysis provides source-to-sink traces that Pixee's triage engine can leverage for more accurate exploitability assessment. When the SARIF output includes those traces, the triage decision considers the full data journey, not just the line where Fortify flagged the finding. + +### Remediation + +Fortify identifies vulnerabilities but does not generate automated code fixes. Pixee delivers remediation as pull requests, applying deterministic codemods for known vulnerability patterns and AI-powered generation for complex scenarios. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Install Pixee** for your platform. +2. **Export Fortify findings as SARIF** — use Fortify's FPR-to-SARIF conversion or export from Fortify Software Security Center (SSC). +3. **Upload SARIF to Pixee** via CI pipeline integration or the Pixee API endpoint. +4. **Pixee triages findings** and opens PRs for remediable issues. +5. **Review and merge.** + +**Prerequisites:** Fortify SCA or SSC with findings, SARIF export capability, Pixee platform integration configured. + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/gitlab-sast.md b/docs/integrations/scanners/gitlab-sast.md new file mode 100644 index 00000000..2c90015f --- /dev/null +++ b/docs/integrations/scanners/gitlab-sast.md @@ -0,0 +1,54 @@ +--- +title: GitLab SAST Integration +slug: /integrations/scanners/gitlab-sast +track: both +content_type: guide +seo_title: GitLab SAST Integration with Pixee +description: Pixee integration with GitLab SAST for automated triage and remediation of findings from multiple analyzers. +sidebar_position: 7 +--- + +# GitLab SAST Integration + +Pixee integrates with GitLab SAST to triage findings from GitLab's built-in static analysis and deliver remediation as merge requests. GitLab SAST uses multiple underlying analyzers (Semgrep, SpotBugs, Gosec, Bandit, and others), each with different false positive rates and metadata quality. Pixee normalizes these heterogeneous findings into a single triage workflow and generates fixes that GitLab SAST does not provide. Your GitLab SAST configuration continues running exactly as it does today. + +## What GitLab SAST Detects + +GitLab SAST is the built-in SAST capability in GitLab Ultimate. It runs as part of CI/CD pipelines using a collection of open-source analyzers orchestrated by GitLab's framework: + +- OWASP Top 10 and common injection flaws via Semgrep (multi-language) +- Java vulnerabilities via SpotBugs +- Go vulnerabilities via Gosec +- Python vulnerabilities via Bandit +- Ruby vulnerabilities via Brakeman +- JavaScript/TypeScript vulnerabilities via NodeJsScan +- Security misconfigurations across frameworks + +## How Pixee Enhances GitLab SAST + +### Triage + +GitLab SAST aggregates findings from multiple analyzers, each with different severity scales, rule naming conventions, and false positive rates. Pixee's triage pipeline normalizes these findings into consistent classifications with structured justifications. + +This solves a specific problem: teams using GitLab SAST receive findings from 5+ different analyzers with inconsistent metadata quality. Pixee applies the same exploitability analysis regardless of which underlying analyzer produced the finding, providing a unified view of what is real and what is noise. + +Each finding is classified as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with code-level evidence. + +### Remediation + +GitLab shows SAST findings in the merge request security widget and vulnerability management dashboard but does not generate automated code fixes. Pixee closes this gap by delivering fixes as merge requests directly in GitLab. + +GitLab SAST findings often lack the contextual detail needed for efficient manual remediation. Pixee's fix generation adds the missing context — vulnerability explanation, fix rationale, and quality scores — directly in the MR. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Connect GitLab to Pixee** — follow the [GitLab quick-start](/getting-started/source-control#gitlab) guide to install the Pixee integration +2. **Ensure GitLab SAST is enabled** — GitLab SAST runs via CI/CD pipeline templates. Verify your `.gitlab-ci.yml` includes the SAST template +3. **Pixee ingests findings automatically** — when GitLab SAST runs in your pipeline, Pixee receives the findings via the GitLab API +4. **Review triage results and merge fixes** — Pixee opens MRs for remediable findings in your existing GitLab workflow + +**Prerequisites:** GitLab Ultimate license (for SAST), Pixee GitLab integration installed + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/gitlab-sca.md b/docs/integrations/scanners/gitlab-sca.md new file mode 100644 index 00000000..8718bdf0 --- /dev/null +++ b/docs/integrations/scanners/gitlab-sca.md @@ -0,0 +1,60 @@ +--- +title: GitLab SCA Integration +slug: /integrations/scanners/gitlab-sca +track: both +content_type: guide +seo_title: GitLab Dependency Scanning (SCA) Integration with Pixee +description: Pixee integration with GitLab Dependency Scanning for automated triage and remediation of open-source dependency vulnerabilities. +sidebar_position: 8 +--- + +# GitLab SCA Integration + +Pixee integrates with GitLab Dependency Scanning (GitLab's built-in SCA) to triage findings and deliver remediation as merge requests. GitLab Dependency Scanning identifies known vulnerabilities in your project's open-source dependencies via the Gemnasium analyzer; Pixee classifies each finding by exploitability and opens MRs that bump dependency versions to fixed releases. Your GitLab Dependency Scanning configuration continues running exactly as it does today. + +> "Dependency Scanning" is GitLab's name for SCA. The terms are interchangeable — `gemnasium-dependency_scanning` is the analyzer that produces the findings. + +## What GitLab Dependency Scanning Detects + +GitLab Dependency Scanning runs as part of CI/CD pipelines and surfaces known vulnerabilities (CVEs) in your project's direct and transitive dependencies. Coverage spans the major package ecosystems: + +- **Java / JVM** — Maven, Gradle (`pom.xml`, `build.gradle`) +- **Python** — pip, Poetry, Pipenv (`requirements.txt`, `Pipfile.lock`, `poetry.lock`) +- **JavaScript / TypeScript** — npm, Yarn, pnpm (`package-lock.json`, `yarn.lock`, `pnpm-lock.yaml`) +- **.NET** — NuGet (`packages.lock.json`) +- **Go** — Go modules (`go.sum`) +- **Ruby** — Bundler (`Gemfile.lock`) +- **PHP** — Composer (`composer.lock`) +- **Rust** — Cargo (`Cargo.lock`) +- **Conan** — C/C++ Conan packages + +Findings are reported with CVE identifiers, severity, affected version ranges, and (where available) the version that fixes the vulnerability. + +## How Pixee Enhances GitLab Dependency Scanning + +### Triage + +GitLab Dependency Scanning surfaces every CVE in every dependency — direct and transitive — without distinguishing whether the vulnerable code path is actually reachable in your project. The result is high finding volume, much of it not exploitable in context. Pixee's triage pipeline classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX based on whether the vulnerable function is actually called and reachable in your codebase. + +This is the core SCA-noise problem: a CVE in a transitive dependency is only meaningful if your code (directly or via the dependency tree) actually exercises the vulnerable code path. Pixee's reachability analysis is what separates the small set of dependency CVEs that matter from the large set that do not. + +Each finding is classified with code-level evidence — what calls the vulnerable function, what does not, and why. + +### Remediation + +GitLab shows dependency findings in the merge request security widget and vulnerability management dashboard but does not automatically open MRs to bump versions. Pixee closes this gap by delivering version-bump merge requests directly in GitLab for findings that are reachable and have a fixed version available. + +Pixee's SCA remediation is deterministic: for each TRUE_POSITIVE with a fix available, Pixee opens an MR that updates the dependency to the lowest version in the fixed range, runs lockfile updates, and includes the CVE rationale in the MR description. Multi-vulnerability fixes can be batched per dependency to minimize MR churn. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Connect GitLab to Pixee** — follow the [GitLab quick-start](/getting-started/source-control#gitlab) guide to install the Pixee integration. +2. **Ensure Dependency Scanning is enabled** — verify your `.gitlab-ci.yml` includes the `Dependency-Scanning.gitlab-ci.yml` template (or your own equivalent that runs `gemnasium-dependency_scanning`). +3. **Pixee ingests findings automatically** — when Dependency Scanning runs in your pipeline, Pixee receives the findings via the GitLab API. +4. **Review triage results and merge fixes** — Pixee opens MRs for remediable findings in your existing GitLab workflow. + +**Prerequisites:** GitLab Ultimate license (Dependency Scanning is part of GitLab's Secure category, which requires Ultimate), Pixee GitLab integration installed. + +See the [SCA](/platform/sca) page for details on how Pixee handles dependency findings end-to-end. See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/polaris.md b/docs/integrations/scanners/polaris.md new file mode 100644 index 00000000..f43624e0 --- /dev/null +++ b/docs/integrations/scanners/polaris.md @@ -0,0 +1,54 @@ +--- +title: Polaris Integration +slug: /integrations/scanners/polaris +track: both +content_type: guide +seo_title: Polaris (Synopsys / Black Duck Coverity) Integration with Pixee +description: Pixee integration with Polaris (Synopsys / Black Duck Coverity) for automated triage and remediation of dataflow and code-quality findings. +sidebar_position: 9 +--- + +# Polaris Integration + +Pixee integrates with Polaris to triage findings from the Coverity SAST engine and deliver remediation as pull requests. Polaris's strength is thorough, conservative dataflow analysis; that thoroughness produces high finding volumes that mix security vulnerabilities, code quality, and lower-severity patterns. Pixee classifies each finding by exploitability and generates code fixes Polaris does not produce. Your Polaris scans continue running as configured. + +> Polaris is the unified application security platform from Synopsys / Black Duck. Note: Synopsys divested its Software Integrity Group, which now operates under the Black Duck Software brand. Polaris remains the unified platform name; Coverity remains the SAST engine name. Pixee works with Polaris regardless of the branding on your license. + +## What Polaris Detects + +- **SAST via the Coverity engine** — deep dataflow analysis, buffer overflows, injection flaws, concurrency issues, and taint tracking across multiple languages +- **SCA via Black Duck** — open-source license compliance and vulnerability detection +- **Rapid Scan** — lightweight SAST designed for CI/CD integration (faster analysis with narrower rule coverage than full Coverity) +- **API security issues** +- **Infrastructure misconfigurations** + +## How Pixee Enhances Polaris + +### Triage + +The Coverity engine is known for thorough, conservative analysis. This thoroughness produces high volumes of findings that mix security vulnerabilities, code quality issues, and lower-severity patterns. Pixee's triage pipeline classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with a code-level justification, accounting for framework protections, sanitization logic, and deployment context that Coverity's conservative analysis may not resolve. + +### Remediation + +Polaris provides findings and remediation guidance but does not generate automated code fixes or pull requests. Pixee closes this gap. True positive findings are automatically fixed using deterministic codemods and AI-powered fixes. Fixes are delivered as pull requests matching the team's code conventions. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Run Polaris** on your repository (via Polaris CLI or CI/CD integration). +2. **Export results in SARIF format** from Polaris. +3. **Upload SARIF to Pixee** via API, UI, or CI integration. +4. **Pixee processes findings** through the triage and remediation pipeline. +5. **Review and merge** Pixee-generated PRs. + +**Prerequisites:** Polaris account with Coverity SAST scan results, Pixee account with connected repository. + +## Common False Positive Patterns Pixee Eliminates + +- **Conservative analysis flagging unlikely conditions:** Coverity flags potential issues even when exploitation requires multiple unlikely conditions to align +- **Code quality findings mixed with security:** Polaris reports reliability bugs, code quality issues, and security vulnerabilities in the same output; Pixee separates security from non-security +- **Buffer overflow false positives in managed languages:** Coverity rules designed for C/C++ may produce findings in managed-language code (Java, C#) where memory management is handled by the runtime +- **Test and example code at production severity:** Findings in non-production code flagged at production severity levels + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/semgrep.md b/docs/integrations/scanners/semgrep.md new file mode 100644 index 00000000..4ad01322 --- /dev/null +++ b/docs/integrations/scanners/semgrep.md @@ -0,0 +1,74 @@ +--- +title: Semgrep Integration +slug: /integrations/scanners/semgrep +track: both +content_type: guide +seo_title: Semgrep Integration with Pixee +description: Pixee integration with Semgrep for automated triage and remediation of OSS and Pro rule findings. +sidebar_position: 11 +--- + +# Semgrep Integration + +Pixee's Semgrep integration processes findings from both Semgrep OSS and Semgrep Pro through automated triage and remediation. The dedicated Semgrep handler extracts rule metadata for accurate classification, then delivers fixes as pull requests. + +## What Semgrep Detects + +Semgrep is a lightweight, fast SAST scanner with a large and growing rule library. Teams adopt it for its speed, pattern-based rule syntax, and developer-friendly workflow. + +Semgrep detects: + +- **OWASP Top 10 vulnerabilities** -- injection, broken authentication, XSS, insecure deserialization, and more +- **Language-specific security rules** from both OSS and Pro rule sets +- **Custom organizational rules** written in Semgrep's pattern syntax for team-specific security policies +- **Code quality issues with security implications** -- hardcoded secrets, weak cryptographic usage, deprecated API calls + +Semgrep supports Python, JavaScript/TypeScript, Java, Go, Ruby, C#, PHP, Kotlin, Swift, and more. Rules run via Semgrep CLI (open source) or Semgrep Code (cloud platform). + +## How Pixee Enhances Semgrep + +### Triage + +Semgrep findings are processed through Pixee's triage pipeline, which classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with code-level justification and a confidence score. + +The dedicated Semgrep handler provides scanner-specific metadata extraction: + +**Rule metadata extraction.** Pixee's handler extracts `fullDescription.text` rule metadata from Semgrep's SARIF output, giving the triage engine the rule explanation alongside the finding. This context helps the triage pipeline distinguish between high-severity exploitable findings and informational warnings that share the same rule ID. + +**OSS and Pro rule support.** The handler processes findings from both Semgrep OSS and Semgrep Pro rule sets. Whether your team uses the community rules, the commercial Pro rules, or a mix, findings flow through the same triage pipeline. + +**Custom rule support.** Custom Semgrep rules that produce SARIF output work with Pixee automatically. Your organization's custom security policies are triaged and remediated through the same pipeline as standard rules -- no additional configuration required. + +Each finding receives a classification with reasoning trail suitable for audit documentation. Security teams can review the triage decisions, not just the raw output. + +### Remediation + +True positive findings receive automated code fixes delivered as pull requests. + +Pixee generates fixes using deterministic codemods and AI-powered fixes. The deterministic codemods handle standard security patterns with zero LLM dependency. AI-powered fixes address complex, codebase-specific scenarios where the fix requires understanding your application's architecture and conventions. + +- Fixes match your team's code conventions -- Pixee generates fixes that use your existing libraries and follow your patterns +- Semgrep identifies what is wrong; Pixee delivers the fix as a PR +- Developers review Pixee PRs through the same workflow they use for all code changes + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Run Semgrep** on your repository via Semgrep CLI, CI/CD integration, or Semgrep Code (cloud). +2. **Export results in SARIF format** using `semgrep --sarif` (CLI) or configure SARIF export in Semgrep Code. +3. **Connect your code repository to Pixee** via the appropriate platform integration (GitHub, GitLab, Azure DevOps, or Bitbucket). +4. **Pixee ingests Semgrep SARIF** and processes findings through the triage and remediation pipeline. +5. **Review and merge** Pixee-generated PRs in your normal workflow. + +**Prerequisites:** Semgrep installed or Semgrep Code account, Pixee connected to your SCM platform. + +## Common False Positive Patterns Pixee Eliminates + +- **Low-severity OSS rules on common patterns:** Rules that fire on widespread coding patterns without evaluating whether the specific instance is exploitable +- **Per-file duplication noise:** The same rule firing on multiple locations across files without prioritization or deduplication +- **Framework-mitigated findings:** Code protected by middleware, security libraries, or framework-level controls that Semgrep's pattern matching cannot resolve +- **Test code flagged at production severity:** Test fixtures, example code, and mock data triggering rules intended for production code +- **Stale API warnings:** Generic rules that lack language-version awareness, flagging deprecated API usage on code that has already been migrated + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/snyk-code.md b/docs/integrations/scanners/snyk-code.md new file mode 100644 index 00000000..a96ccbd2 --- /dev/null +++ b/docs/integrations/scanners/snyk-code.md @@ -0,0 +1,64 @@ +--- +title: Snyk Code Integration +slug: /integrations/scanners/snyk-code +track: both +content_type: guide +seo_title: Snyk Code Integration with Pixee +description: Pixee integration with Snyk Code for automated triage and remediation of SAST findings. +sidebar_position: 12 +--- + +# Snyk Code Integration + +Pixee integrates with Snyk Code to triage SAST findings and deliver remediation as pull requests. Snyk Code continues scanning as it does today -- Pixee sits downstream, providing independent triage verification and automated fixes. More importantly, Pixee triages Snyk Code findings alongside findings from every other scanner in your portfolio through one pipeline, eliminating per-tool review silos. + +## What Snyk Code Detects + +Snyk Code is the SAST component of the Snyk platform, built on the DeepCode acquisition. It provides real-time static analysis designed for developer workflows, with IDE integrations, CLI scanning, and CI/CD pipeline support. Snyk Code is known for speed and lower false positive rates compared to traditional SAST tools, with strong adoption among cloud-native engineering teams. + +Snyk Code detects: + +- **Injection flaws** -- SQL injection, cross-site scripting, command injection, and other injection-class vulnerabilities +- **Authentication and cryptographic weaknesses** -- broken authentication, insecure cryptographic usage +- **Code quality issues with security implications** -- patterns that could lead to security vulnerabilities +- **Hardcoded secrets and credentials** +- **Data flow taint tracking** -- tracing untrusted data from sources to sinks + +Language coverage includes JavaScript/TypeScript, Python, Java, Go, Ruby, C#, PHP, Swift, and Kotlin. + +## How Pixee Enhances Snyk Code + +### Triage + +Snyk Code already produces lower false positive rates than traditional SAST tools. Pixee's value for Snyk Code users centers on two areas: + +**Independent verification.** Each Snyk Code finding is processed through Pixee's triage pipeline, which classifies it as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with a detailed justification and confidence score. The classification provides audit-ready evidence for compliance workflows. + +**Cross-scanner unification.** Most teams run Snyk Code alongside other scanners -- SCA tools, container scanners, infrastructure-as-code analyzers. Pixee triages findings from all of them through one pipeline with consistent classification logic. No more switching between the Snyk dashboard, the GHAS dashboard, and the SonarQube portal to review findings from each tool in isolation. + +### Remediation + +Snyk's "DeepCode AI Fix" provides remediation suggestions within the Snyk UI. Pixee delivers a different outcome: complete, context-aware fixes as pull requests that developers review and merge through their standard code review workflow. + +Fixes are generated using deterministic codemods and AI-powered fixes for complex scenarios. Every fix matches the team's code conventions -- naming patterns, preferred libraries, and existing security utilities. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Run Snyk Code scan** on your repository (via Snyk CLI, CI/CD integration, or Snyk UI). +2. **Export results in SARIF format** from Snyk Code. +3. **Upload SARIF to Pixee** via API, UI, or CI integration. +4. **Pixee processes findings** through the triage and remediation pipeline. +5. **Review and merge** Pixee-generated PRs in your normal development workflow. + +**Prerequisites:** Snyk account with Snyk Code enabled, Pixee account with connected repository. + +## Common False Positive Patterns Pixee Eliminates + +- **Framework-protected endpoints:** Snyk Code flags injection risks in code protected by middleware-level input validation or framework security features +- **Sanitized data in multi-file flows:** Data flows where sanitization occurs upstream in a different file, beyond Snyk Code's analysis scope +- **Test code at production severity:** Intentionally vulnerable test fixtures, mock data, or example code flagged as production security issues +- **Context-dependent findings:** Findings that depend on runtime configuration or deployment context that static analysis cannot determine + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/sonarqube.md b/docs/integrations/scanners/sonarqube.md new file mode 100644 index 00000000..eef65d5f --- /dev/null +++ b/docs/integrations/scanners/sonarqube.md @@ -0,0 +1,70 @@ +--- +title: SonarQube Integration +slug: /integrations/scanners/sonarqube +track: both +content_type: guide +seo_title: SonarQube Integration with Pixee +description: Pixee integration with SonarQube and SonarCloud for automated triage and remediation, including security hotspot classification. +sidebar_position: 13 +--- + +# SonarQube Integration + +Pixee integrates natively with SonarQube and SonarCloud to triage findings and deliver remediation as pull requests. SonarQube's security hotspots require manual review -- Pixee automates that review with code-level justification and generates fixes for confirmed vulnerabilities. + +## What SonarQube Detects + +SonarQube (self-hosted) and SonarCloud (SaaS) are the most widely deployed code quality and security analysis platforms in the industry. Often the first analysis tool adopted by engineering teams, SonarQube combines SAST with code quality, technical debt, and coverage analysis across 30+ languages. + +SonarQube detects: + +- **Static Application Security Testing (SAST)** -- OWASP Top 10, CWE coverage, injection flaws, cross-site scripting, authentication issues +- **Security hotspots** -- code patterns that require manual security review before being classified as safe or vulnerable +- **Code quality issues** -- bugs, code smells, and technical debt +- **Code coverage analysis** -- test coverage tracking +- **Duplication detection** -- identifying copy-paste patterns across the codebase + +## How Pixee Enhances SonarQube + +### Triage + +SonarQube's security hotspot system explicitly requires manual review -- a developer or security engineer must investigate each hotspot and classify it as safe or vulnerable. For teams with hundreds or thousands of hotspots, this manual process creates a permanent backlog. + +Pixee automates that review. Each SonarQube finding -- including security hotspots -- is processed through Pixee's triage pipeline, which classifies it as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with a code-level justification. The triage engine investigates the actual codebase to determine whether a hotspot represents a genuine risk. + +For teams managing SonarQube's high-volume output, where security findings mix with code quality findings and hotspots in a single dashboard, Pixee separates what matters from what does not. + +### Remediation + +SonarQube shows what is wrong but does not generate fixes. Pixee fills this gap by delivering remediation as pull requests. True positive findings from SonarQube are automatically fixed using deterministic codemods and AI-powered fixes for complex scenarios. Dedicated prompt builders in the remediation engine handle SonarQube-specific finding formats. + +Fixes match your team's code conventions. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Supported Languages + +Pixee remediates SonarQube findings across Java, Python, JavaScript/TypeScript, .NET, and PHP. Java and Python have the deepest deterministic codemod coverage; other languages rely on AI-powered fixes. For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +### Prerequisites + +- SonarQube 9.x or later (self-hosted) or SonarCloud (SaaS) with existing scan results +- A Pixee account with at least one repository connected ([Getting Started](/)) +- A SonarQube user token with **Browse** and **Administer** project permissions (not a global analysis token) + +Connect SonarQube by providing your instance URL and a user token with Browse and Administer project permissions. Pixee queries SonarQube directly via API -- no SARIF export needed. SonarQube projects are mapped to code repositories using the project key; if your project keys match your repository names, mapping is automatic. For enterprise self-hosted deployments, configure SonarQube credentials in your Helm values. For step-by-step configuration, see the [installation guide](https://app.pixee.ai/docs/setup). + +### What Happens with Large Backlogs + +If your SonarQube instance has thousands of findings, Pixee does not open thousands of PRs simultaneously. Findings are prioritized by severity (Critical and High first), and PR creation is controlled by your configured batch settings. See [Operations](/configuration/operations) for PR volume controls. + +## Common False Positive Patterns Pixee Eliminates + +- **Security hotspots that are actually safe:** Pixee's triage engine investigates the actual code context and determines whether the flagged pattern is exploitable -- automating the manual review SonarQube requires +- **Code quality findings conflated with security:** SonarQube mixes code smells, bugs, and security findings in one dashboard; Pixee distinguishes genuine security issues from code quality noise +- **Framework-mitigated injection patterns:** Findings where the application framework provides protection (parameterized queries via ORM, CSRF tokens via framework middleware) +- **Test code at production severity:** SonarQube scans test directories by default; Pixee adjusts classification for non-production code + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/trivy.md b/docs/integrations/scanners/trivy.md new file mode 100644 index 00000000..2371e211 --- /dev/null +++ b/docs/integrations/scanners/trivy.md @@ -0,0 +1,49 @@ +--- +title: Trivy Integration +slug: /integrations/scanners/trivy +track: both +content_type: guide +seo_title: Trivy Integration with Pixee +description: Pixee integration with Aqua Trivy for automated triage and remediation across container, dependency, IaC, and secret findings. +sidebar_position: 14 +--- + +# Trivy Integration + +Pixee integrates with Trivy to triage findings and deliver remediation as pull requests. Trivy's breadth — container images, dependencies, IaC, secrets — produces high-volume output. A single container base image can have hundreds of known CVEs, most of which are not exploitable in your application's context. Pixee's exploitability analysis classifies each finding so teams can focus on what is actually reachable and fixable. Trivy continues scanning as configured; Pixee adds the triage and fix layer it does not provide. + +Trivy is Aqua Security's open-source scanner, widely adopted in cloud-native and DevSecOps environments. + +## What Trivy Detects + +- **Container image vulnerabilities** — OS packages and application dependencies +- **SCA** — open-source dependency vulnerabilities +- **Infrastructure as Code (IaC) misconfigurations** — Terraform, CloudFormation, Kubernetes manifests, Dockerfiles +- **Secret detection** — hardcoded credentials, API keys +- **License compliance issues** +- **SBOM generation** — CycloneDX and SPDX formats + +Trivy produces SARIF output natively, making it highly interoperable with downstream tools. + +## How Pixee Enhances Trivy + +### Triage + +Trivy's breadth is its strength and its challenge. Container image scans can surface hundreds of CVEs in OS packages, most of which are not exploitable in the application's context. Pixee's triage pipeline classifies each finding by exploitability and actionability, separating real threats from noise. For code-level findings and IaC misconfigurations, the triage engine investigates the actual codebase to determine whether the finding represents a real risk. For dependency vulnerabilities found in container image scans, Pixee can generate dependency update fixes where the dependency is managed in your source code. + +### Remediation + +Trivy identifies vulnerabilities but does not generate code fixes. Pixee delivers fixes as pull requests — updating dependency versions, fixing IaC misconfigurations, and remediating code-level findings using both deterministic codemods and AI-powered generation. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Install Pixee** for your platform — see [Connect Source Control](/getting-started/source-control) for GitHub, GitLab, Azure DevOps, and Bitbucket. +2. **Configure Trivy to output SARIF** — add `--format sarif` to your Trivy command or CI pipeline step. +3. **Upload SARIF to Pixee** — configure SARIF upload in your CI pipeline or use the Pixee integration endpoint. +4. **Review and merge** — Pixee triages findings and opens PRs for remediable issues. + +**Prerequisites:** Trivy installed in your CI pipeline or locally, Pixee platform integration configured. + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scanners/veracode.md b/docs/integrations/scanners/veracode.md new file mode 100644 index 00000000..ff58b2d9 --- /dev/null +++ b/docs/integrations/scanners/veracode.md @@ -0,0 +1,62 @@ +--- +title: Veracode Integration +slug: /integrations/scanners/veracode +track: both +content_type: guide +seo_title: Veracode Integration with Pixee +description: Pixee integration with Veracode for automated triage and remediation of SAST findings. +sidebar_position: 15 +--- + +# Veracode Integration + +Pixee integrates natively with Veracode to triage SAST findings and deliver remediation as pull requests. Pixee sits downstream, classifying each finding as true positive, false positive, or won't-fix with code-level justification, then generating fixes for confirmed vulnerabilities. + +## What Veracode Detects + +Veracode is a leading cloud-native application security platform widely deployed in regulated industries including financial services, healthcare, and government. Its centralized cloud scanning model -- code is uploaded to Veracode's cloud for analysis -- provides broad coverage without requiring local scanning infrastructure. + +Veracode detects: + +- **Static Application Security Testing (SAST)** -- broad coverage of OWASP Top 10 and CWE categories including injection flaws, cross-site scripting, authentication weaknesses, and insecure cryptography +- **Software Composition Analysis (SCA)** -- open-source dependency vulnerabilities and license risk +- **Dynamic Application Security Testing (DAST)** -- runtime vulnerability detection against deployed applications +- **Secrets detection** -- hardcoded credentials and API keys +- **Infrastructure as Code (IaC) misconfigurations** + +## How Pixee Enhances Veracode + +### Triage + +Veracode findings are processed through Pixee's triage pipeline, which classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX with a detailed justification and confidence score. + +The dedicated Veracode handler extracts scanner-specific metadata from Veracode's SARIF output, providing the triage engine with the context it needs for accurate classification. This reduces the manual triage burden on AppSec teams who currently review Veracode results in the Veracode portal -- a process that consumes hours of analyst time per scan cycle. + +Each classified finding includes an audit-ready justification trail explaining the reasoning behind the triage decision. + +### Remediation + +True positive findings receive automated code fixes delivered as pull requests. Pixee generates fixes using deterministic codemods and AI-powered fixes for complex, codebase-specific scenarios. + +Veracode's own "Veracode Fix" provides AI-assisted remediation suggestions, but it does not deliver merged pull requests at scale. Pixee closes that gap: findings move from classification to fix to developer review in one pipeline. Developers review and merge Pixee PRs through their standard workflow. + +For the full list of vulnerability types Pixee triages and fixes, see [What Pixee Fixes](/platform/what-pixee-fixes). + +## Setup + +1. **Connect Veracode credentials** in Pixee settings (Helm values for Enterprise Server, or SaaS configuration). +2. **Configure Veracode SARIF export** or use Pixee's native Veracode integration to ingest findings directly. +3. **Connect your code repository** (GitHub, GitLab, Azure DevOps, or Bitbucket). +4. **Pixee processes findings** automatically through the triage and remediation pipeline. +5. **Review and merge** Pixee-generated PRs in your normal development workflow. + +**Prerequisites:** Veracode account with SAST scan results, Pixee account with connected repository. + +## Common False Positive Patterns Pixee Eliminates + +- **Parameterized query false positives:** Veracode flags SQL injection on code that already uses parameterized APIs or ORMs -- Pixee's triage verifies the actual query construction +- **Sanitized input in complex flows:** Veracode's static analysis cannot always trace sanitization through complex control flow; Pixee investigates security controls in the actual codebase +- **Test code at production severity:** Pixee distinguishes test fixtures, example code, and documentation snippets from production code +- **Framework-mitigated findings:** Code protected by framework-level security controls (Spring Security, Django middleware) that Veracode's static analysis cannot resolve + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. diff --git a/docs/integrations/scms/_category_.json b/docs/integrations/scms/_category_.json new file mode 100644 index 00000000..56f8e9e3 --- /dev/null +++ b/docs/integrations/scms/_category_.json @@ -0,0 +1,9 @@ +{ + "label": "Source Control", + "position": 3, + "collapsible": true, + "collapsed": false, + "link": { + "type": "generated-index" + } +} diff --git a/docs/integrations/scms/azure-devops.md b/docs/integrations/scms/azure-devops.md new file mode 100644 index 00000000..cc7e4068 --- /dev/null +++ b/docs/integrations/scms/azure-devops.md @@ -0,0 +1,55 @@ +--- +title: Azure DevOps Integration +slug: /integrations/scms/azure-devops +track: both +content_type: guide +seo_title: Azure DevOps Integration with Pixee +description: Pixee integration with Azure DevOps via personal access token and webhook configuration. Optional work-item linking for branch-policy compliance. +sidebar_position: 1 +--- + +# Azure DevOps Integration + +Pixee integrates with Azure DevOps through a personal access token and webhook configuration, delivering automated security triage and remediation as pull requests. Developers review and merge Pixee fixes exactly like any other PR — zero new tools, zero new interfaces. Optional work-item linking supports organizations that enforce "Require linked work item" branch policies. Works with Azure DevOps Services (cloud) and Azure DevOps Server (on-premises). + +## How Pixee Works with Azure DevOps + +Pixee connects to Azure DevOps using your organization name plus a personal access token (PAT) for API access. Optional webhook credentials authenticate inbound webhook requests from Azure DevOps to Pixee for real-time event delivery. + +**PAT-based authentication.** A PAT with full _Code_ access handles repository reads, branch operations, and pull-request management. Use a custom scope rather than "Full access" so the token grants only what the integration needs. + +**Pull request delivery.** Every remediation Pixee generates arrives as a standard Azure DevOps PR. PR descriptions include the finding context, fix explanation, triage justification, and confidence score. + +**Webhook integration (optional).** Azure DevOps can deliver repository and PR events to Pixee for low-latency response to scanner output. Configure a webhook user and password in Pixee, then point Azure DevOps webhook deliveries at the Pixee endpoint with HTTP Basic auth using those credentials. + +## Authentication + +| Credential | Purpose | +| ---------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- | +| Organization name | Identifies your Azure DevOps organization to Pixee | +| Personal access token | A PAT with **full _Code_ access** (custom scope, not "Full access"). Authorizes repository reads, branch operations, and PR management. | +| Webhook user / password (optional) | HTTP Basic credentials Pixee uses to authenticate inbound webhook requests from Azure DevOps | + +For Pixee Enterprise (Helm), these values live under `platform.scm.azure.{organization, token, webhook.user, webhook.password}`. For SaaS, use the settings UI. For embedded-cluster Enterprise, the admin console exposes these fields under **Config → Development Platforms → Azure DevOps**. + +## Scanner Integration + +Pixee works with any scanner that produces SARIF output run from Azure Pipelines or any external CI system. No modification to existing pipeline YAML is required. Scanner findings are uploaded to Pixee via SARIF; Pixee then triages and remediates them, delivering fix PRs into the same Azure DevOps repository where the code lives. + +## Setup + +1. **Create a personal access token** in Azure DevOps with a custom scope that includes full _Code_ access. +2. **(Optional) Choose webhook credentials** — a username and password that Pixee will use to authenticate inbound webhook requests from Azure DevOps. +3. **Configure Pixee** with your organization name, the PAT, and (optionally) the webhook credentials. See [Authentication](#authentication) above for the values map. +4. **(Optional) Set up Azure DevOps webhooks** to deliver repository and PR events to your Pixee endpoint, using HTTP Basic auth with the credentials from step 2. +5. **Pixee begins monitoring** for scanner findings and generating remediation PRs. + +For the quick-start walkthrough, see [Connect Source Control → Azure DevOps](/getting-started/source-control#azure-devops). + +## Azure DevOps Server (On-Premises) + +Pixee Enterprise Server supports both Azure DevOps Services (cloud) and Azure DevOps Server (on-premises) with the same capabilities. The same PAT and webhook integration model applies. + +For on-premises configuration, see the [enterprise deployment documentation](/enterprise/deployment). + +See [Integrations Overview](/integrations/overview) for the full integration coverage matrix. diff --git a/docs/integrations/scms/bitbucket.md b/docs/integrations/scms/bitbucket.md new file mode 100644 index 00000000..64914b83 --- /dev/null +++ b/docs/integrations/scms/bitbucket.md @@ -0,0 +1,65 @@ +--- +title: Bitbucket Integration +slug: /integrations/scms/bitbucket +track: both +content_type: guide +seo_title: Bitbucket Integration with Pixee +description: Pixee integration with Bitbucket via API token. Native pull request delivery and SARIF upload from Bitbucket Pipelines or any external CI system. +sidebar_position: 2 +--- + +# Bitbucket Integration + +Pixee integrates with Bitbucket Cloud through an API token, delivering automated security triage and remediation as pull requests. Developers review and merge Pixee fixes exactly like any other PR — zero new tools, zero new interfaces. + +## How Pixee Works with Bitbucket + +Pixee connects to Bitbucket Cloud using a workspace-scoped API token. API tokens are the current authentication method, replacing app passwords (deprecated by Atlassian). + +**Pull request delivery.** Every remediation Pixee generates arrives as a standard Bitbucket PR. PR descriptions include the finding context, fix explanation, triage justification, and confidence score. + +**Username plus email.** Bitbucket API tokens require both your account's **email address** (used for API authentication) and your **username** (used for Git operations). Configure both in Pixee — using just one will not work. We recommend using a dedicated service-account user rather than a personal user, so the integration survives team-member departures. + +## Authentication + +| Credential | Purpose | +| ------------- | --------------------------------------------------------------------- | +| Username | Git operations against the workspace's repositories | +| Email address | API authentication (Bitbucket API tokens require email, not username) | +| API token | Authorizes the workspace operations defined by the scopes below | + +**Required API token scopes:** + +| Scope | Purpose | +| ----------------------------- | ------------------------------------------------- | +| `read:user:bitbucket` | Identify the authenticated user | +| `read:workspace:bitbucket` | Discover repositories in the workspace | +| `read:repository:bitbucket` | Read code for analysis | +| `read:pullrequest:bitbucket` | Read PR state for ingestion and event correlation | +| `write:repository:bitbucket` | Push fix branches | +| `write:pullrequest:bitbucket` | Create and manage remediation PRs | + +For instructions on creating an API token, see Atlassian's [Bitbucket Cloud documentation](https://support.atlassian.com/bitbucket-cloud/docs/create-a-repository-access-token/). + +## Scanner Integration + +Bitbucket Pipelines is one option for running scanners, but many teams use Jenkins, CircleCI, GitHub Actions, or other CI systems with Bitbucket-hosted repositories. Pixee works with all of them: + +- **SARIF upload from Bitbucket Pipelines** — scanner steps in `bitbucket-pipelines.yml` can produce SARIF and upload it to Pixee. +- **SARIF upload from external CI** — Jenkins, CircleCI, GitHub Actions, or any CI system that produces SARIF can upload findings to Pixee. +- **All named scanner integrations** and the universal SARIF connector work with Bitbucket-hosted repositories. + +## Setup + +1. **Create a service-account user** in your Bitbucket workspace. +2. **Generate an API token** for the service account with the six scopes listed above. +3. **Configure Pixee** with the username, email address, and API token. For Pixee Enterprise (Helm), the values live under `platform.scm.bitbucket.{username, emailAddress, apiToken}`. For SaaS, use the settings UI. For embedded-cluster Enterprise, the admin console exposes these fields under **Config → Development Platforms → BitBucket**. +4. **Pixee begins monitoring** for scanner findings and generating remediation PRs. + +For the quick-start walkthrough, see [Connect Source Control → Bitbucket](/getting-started/source-control#bitbucket). + +## Bitbucket Server / Data Center + +Bitbucket Server (formerly Data Center) is a separate Atlassian product from Bitbucket Cloud. The integration mechanics — credentials, scopes, and configuration paths — differ. For Bitbucket Server deployments running on Pixee Enterprise, see the [enterprise deployment documentation](/enterprise/deployment) for the supported connection model and current configuration details. + +See [Integrations Overview](/integrations/overview) for the full integration coverage matrix. diff --git a/docs/integrations/scms/github.md b/docs/integrations/scms/github.md new file mode 100644 index 00000000..9d67e502 --- /dev/null +++ b/docs/integrations/scms/github.md @@ -0,0 +1,140 @@ +--- +title: GitHub Integration +slug: /integrations/scms/github +track: both +content_type: guide +seo_title: GitHub Platform Integration with Pixee +description: Pixee integration with GitHub via native GitHub App. Automated triage and remediation delivered as pull requests. +sidebar_position: 3 +--- + +# GitHub Integration + +Pixee integrates with GitHub through a native GitHub App that delivers automated security triage and remediation as pull requests. Developers review and merge Pixee fixes exactly like any other PR -- zero new tools, zero new interfaces. The GitHub App handles repository access, webhook events, and PR creation automatically. Works with GitHub.com and GitHub Enterprise Server. + +> This page covers GitHub as a development platform. For CodeQL and GitHub Advanced Security scanner integration, see [CodeQL Integration](/integrations/scanners/codeql). + +## How Pixee Works with GitHub + +Pixee connects to GitHub through a first-class GitHub App -- the same integration model used by production-grade developer tools across the GitHub ecosystem. + +**GitHub App integration.** A single GitHub App installation gives Pixee access to your organization's repositories. The app handles authentication, webhook events, and PR creation through GitHub's native API. Credentials are managed through the GitHub App's private key, with support for external secret managers (Vault, External Secrets Operator, SOPS) via `existingSecret` configuration. + +**Pull request delivery.** Every remediation Pixee generates arrives as a standard GitHub pull request. PR descriptions include the finding context, fix explanation, triage justification, and confidence score. Developers see Pixee PRs in their PR queue alongside all other pull requests -- no separate dashboard, no new tool to learn. + +**Webhook integration.** Pixee receives real-time events from your repositories via GitHub webhooks. Repository changes, PR actions, and scanner output trigger Pixee's triage and remediation pipeline automatically. + +**Repository management.** Install the GitHub App on all repositories or select specific ones. Organization-level or repository-level installation gives administrators control over which repositories Pixee monitors. + +## What Developers See + +Fixes arrive as standard GitHub pull requests — no new tools, no new dashboards. Existing branch protection rules, required reviewers, and CI checks apply to Pixee PRs exactly as they would to any other PR. See [Connect Source Control → GitHub](/getting-started/source-control#github) for the quick-start steps, or [Your First Fix](/getting-started/first-fix) for what a Pixee PR looks like. + +## Scanner Integration via GitHub + +GitHub serves as both the development platform and a scanner delivery mechanism: + +- **CodeQL findings via GHAS API:** Pixee's deep integration ingests CodeQL findings directly from GitHub Advanced Security. See [CodeQL Integration](/integrations/scanners/codeql) for details. +- **SARIF upload via GitHub Code Scanning:** Any scanner that uploads SARIF to GitHub's Code Scanning API makes those findings available to Pixee. +- **Direct SARIF upload from GitHub Actions:** Scanner results from Actions workflow jobs can be sent to Pixee directly. +- **All scanner findings** -- regardless of source -- are processed through the same triage and remediation pipeline. + +## GitHub Actions Integration + +Pixee works alongside your existing GitHub Actions workflows without requiring modifications. + +Scanner results from Actions jobs are available to Pixee. If your CodeQL Action, Semgrep Action, or any SARIF-producing scanner runs in a GitHub Actions workflow, the output feeds into Pixee's pipeline automatically or via SARIF upload. + +There is no need to modify existing `.github/workflows/` files. Pixee operates alongside your CI/CD pipeline, not inside it. + +## Setup + +1. **Install the Pixee GitHub App** on your organization or selected repositories. +2. **Authorize repository access** -- choose all repositories or select specific ones. +3. **Pixee begins monitoring** for scanner findings and generating remediation PRs. +4. **Configure preferences** in `PIXEE.yaml` (optional) to tune triage behavior and fix scope. +5. **Review and merge** your first Pixee PR. + +For a quick-start walkthrough, see [Connect Source Control → GitHub](/getting-started/source-control#github). + +### Required Permissions + +The Pixee GitHub App requests the following permissions during installation. Pixee Enterprise customers register a custom GitHub App and configure the same permissions; SaaS customers install the published Pixee App which carries these permissions pre-configured. + +**Repository permissions:** + +| Permission | Access | Purpose | +| -------------------- | -------------- | ------------------------------------------------------------- | +| Checks | Read and write | Report triage and fix-validation status on PRs | +| Code scanning alerts | Read and write | Ingest CodeQL and SARIF findings; report fix status | +| Commit statuses | Read and write | Reflect fix-pipeline state on commits | +| Contents | Read and write | Read code for analysis; create fix branches | +| Dependabot alerts | Read and write | Ingest SCA findings from Dependabot | +| Issues | Read and write | Read referenced issues; comment with triage context | +| Metadata | Read-only | Repository metadata for configuration | +| Pull Requests | Read and write | Create and manage remediation PRs | +| Workflows | Read and write | Inspect Actions workflow state for scanner-result correlation | + +**Organization permissions:** + +| Permission | Access | Purpose | +| ---------- | --------- | ---------------------------------------- | +| Members | Read-only | Resolve PR-author identities for scoping | + +**Account permissions:** + +| Permission | Access | Purpose | +| --------------- | --------- | --------------------------------------------- | +| Email addresses | Read-only | Author attribution on Pixee-generated commits | + +**Webhook events the App subscribes to:** Code scanning alert, Check run, Create, Dependabot alert, Issue comment, Issues, Pull request, Pull request review, Pull request review comment, Pull request review thread, Push, Repository. + +See [Integrations Overview](/integrations/overview) for the full scanner coverage matrix. + +## GitHub Enterprise Server + +GHES (and Pixee Enterprise on github.com) is supported by registering a **custom GitHub App** on your GitHub host. Pixee Enterprise then connects using that App's credentials. The mechanics are the same as a standard GitHub App; the install path differs because you control the App registration end-to-end. + +### Registering the Custom GitHub App + +In your GitHub host (github.com or your GHES instance), go to **Settings → Developer settings → GitHub Apps → New GitHub App**, then: + +1. **GitHub App name.** Choose something unique to your org (e.g., `AcmePixeebotApp`). Save the name — Pixee Enterprise needs it. +2. **Homepage URL.** Anything works (e.g., `https://pixee.ai`). You can change this later. +3. **Callback URL.** Set to `https:///api/auth/login`. +4. **Request user authorization (OAuth) during installation.** Check this box. +5. **Webhook → Active.** Check this box. +6. **Webhook URL.** Set to `https:///github-event`. +7. **Webhook secret.** Set to a randomly generated value. Save it — Pixee Enterprise needs it. +8. **Permissions.** Configure the repository, organization, and account permissions exactly as listed in [Required Permissions](#required-permissions) above. +9. **Subscribe to events.** Check the events listed in [Required Permissions](#required-permissions) above. +10. **Where can this GitHub App be installed?** Start with **Only on this account**; you can broaden later. +11. **Create GitHub App.** Save the generated **App ID**. +12. **Generate a private key** from the App's settings page. Download the `.pem` file. + +### Configuring Pixee Enterprise + +Provide the App's credentials to your Pixee Enterprise installation: + +- **Embedded cluster.** Admin console → **Config → Development Platforms → GitHub** → enter the App name, App ID, and upload the private key. For GHES, select **Custom domain** for the **GitHub domain** setting and enter your GHES hostname. +- **Helm.** Set the values under `platform.github`: + ```yaml + platform: + github: + appName: "" + appId: "" + appWebhookSecret: "" + appPrivateKey: | + -----BEGIN RSA PRIVATE KEY----- + ... + -----END RSA PRIVATE KEY----- + # For GHES on a custom domain, set the URL: + # url: "https://github.your-company.com" + ``` + +### Network and Verification + +- **Bidirectional reachability** is required between your GitHub host and the Pixee Enterprise deployment. GitHub sends webhook events to Pixee; Pixee makes API calls back to GitHub. For air-gapped environments, see [Enterprise Deployment Options](/enterprise/deployment). +- **Verify connectivity** by checking the App's event log under **Settings → Developer settings → GitHub Apps → Advanced**. Successful deliveries to the Pixee webhook URL confirm the integration is reachable end-to-end. + +For deployment-model details (embedded cluster, Helm, air-gapped), see [Enterprise Deployment Options](/enterprise/deployment). diff --git a/docs/integrations/scms/gitlab.md b/docs/integrations/scms/gitlab.md new file mode 100644 index 00000000..27abbc8a --- /dev/null +++ b/docs/integrations/scms/gitlab.md @@ -0,0 +1,83 @@ +--- +title: GitLab Integration +slug: /integrations/scms/gitlab +track: both +content_type: guide +seo_title: GitLab Integration with Pixee +description: Pixee integration with GitLab via service-account personal access token. Native merge request delivery with optional project-membership scoping. +sidebar_position: 4 +--- + +# GitLab Integration + +Pixee integrates with GitLab through a service-account personal access token, delivering automated security triage and remediation as merge requests. Developers review and merge Pixee fixes exactly like any other MR — zero new tools, zero new interfaces. The integration handles repository access, webhook events, and MR creation automatically. Works with GitLab.com and self-hosted GitLab. + +> This page covers GitLab as a development platform. For GitLab SAST scanner integration, see [GitLab SAST](/integrations/scanners/gitlab-sast). For GitLab Dependency Scanning (SCA), see [GitLab SCA](/integrations/scanners/gitlab-sca). + +## How Pixee Works with GitLab + +Pixee connects to GitLab through a service-account personal access token (PAT) with the scopes required to read repositories, manage merge requests, and create fix branches. + +**PAT-based authentication.** A single service-account PAT gives Pixee scoped access to your GitLab projects. The token's scopes are limited to what Pixee needs — full API access for MR management, repository read/write, and user-attribution metadata. + +**Merge request delivery.** Every remediation Pixee generates arrives as a standard GitLab MR. MR descriptions include the finding context, fix explanation, triage justification, and confidence score. Developers see Pixee MRs in their MR queue alongside all other merge requests. + +**Webhook events.** Pixee receives real-time events from your projects via GitLab webhooks. Repository changes, MR actions, and scanner output trigger Pixee's triage and remediation pipeline automatically. + +**Project access control.** The `member_projects_only` toggle restricts Pixee to projects where the service account is an explicit member — a security control useful in large GitLab instances where you want Pixee scoped to a known subset of projects rather than every project the token can technically access. + +## Authentication + +The PAT requires the following scopes: + +| Scope | Purpose | +| ----------------------- | -------------------------------------------------------------- | +| `api` | Full API access for MR creation and management | +| `read_user` | Read user information for attribution | +| `read_repository` | Read repository contents for analysis | +| `read_api` | Read-only API access for discovery | +| `write_repository` | Create fix branches and commit changes | +| `ai_features` | Drive GitLab Duo / AI features used by the integration | +| `read_registry` | Read the project's container registry for image-based analyses | +| `read_virtual_registry` | Read GitLab's virtual dependency registry for SCA correlation | + +## Scanner Integration via GitLab + +GitLab serves as both the development platform and a scanner delivery mechanism: + +- **GitLab SAST findings** are ingested natively. See [GitLab SAST](/integrations/scanners/gitlab-sast). +- **GitLab Dependency Scanning** for SCA is ingested as well. See [GitLab SCA](/integrations/scanners/gitlab-sca). +- **Any SARIF scanner output** can be uploaded to Pixee from GitLab CI jobs. +- **Fortify + GitLab** is a documented enterprise deployment pattern. See [Fortify](/integrations/scanners/fortify). + +## GitLab CI + +Pixee works alongside existing GitLab CI/CD pipelines without requiring modifications. No changes to `.gitlab-ci.yml` are needed. Pixee is compatible with GitLab's security dashboard and vulnerability management features. + +## Setup + +1. **Create a service-account user** in GitLab with appropriate project membership. (Service accounts are recommended over personal accounts so the integration survives team-member departures.) +2. **Generate a personal access token** for the service account with the scopes listed above. +3. **Configure Pixee** with the PAT. For Pixee Enterprise (Helm), values live under `platform.scm.gitlab.{token, baseUri, webhookSecret}`. For SaaS, use the settings UI. For embedded-cluster Enterprise, the admin console exposes these fields under **Config → Development Platforms → GitLab**. +4. **Configure repository access** — either grant the service account access to all relevant projects, or use `member_projects_only` for explicit per-project membership. +5. **Pixee begins monitoring** projects, ingesting scanner findings, and generating remediation MRs. + +For the quick-start walkthrough, see [Connect Source Control → GitLab](/getting-started/source-control#gitlab). + +### Webhook Configuration + +For real-time event delivery from GitLab, configure a webhook on your project (or group) pointing at: + +``` +https:///api/v1/integrations/gitlab-default/webhooks +``` + +The webhook secret you set in GitLab must match the `webhookSecret` configured in Pixee Enterprise. For setup instructions, see [GitLab's webhook documentation](https://docs.gitlab.com/user/project/integrations/webhooks/). Webhooks are optional — Pixee can still ingest findings via API polling — but recommended for low-latency response to scanner output. + +## Self-Hosted GitLab + +Pixee Enterprise Server connects to self-hosted GitLab via the same PAT integration used for GitLab.com. Capabilities are identical: MR delivery, webhook events, scanner ingestion, and project management all work the same way. + +For self-hosted GitLab configuration, see the [enterprise deployment documentation](/enterprise/deployment). + +See [Integrations Overview](/integrations/overview) for the full integration coverage matrix. diff --git a/docs/intro.md b/docs/intro.md deleted file mode 100644 index 7cf6e4b4..00000000 --- a/docs/intro.md +++ /dev/null @@ -1,47 +0,0 @@ ---- -sidebar_position: 1 ---- - -# Introducing Pixee 👋 - -Pixee is your automated product security engineer. - -Pixee triages and fixes issues detected by your [code scanning tools](/code-scanning-tools/overview). To make the fixes, we send you pull requests, just like your other team members. - -### How does Pixee help me? - -1. 🗃️ **Continuous Improvement:** works down your backlog of issues and keeps your codebase secure. -2. :seedling: **PR Improvement:** checks each new pull request (PR) and recommends improvements. -3. 🔎 **Triage**: identifies false positives and prioritizes issues that need fixing. - -### What types of issues can Pixee triage and fix? - -Pixee can triage and fix a wide range of security issues detected by code scanning tools. Many of these issues are common across tools and languages, such as: - -- SQL Injection -- Cross-Site Scripting (XSS) -- Insecure Deserialization -- Insecure Randomness -- XML External Entities (XXE) -- Insecure Cookie Handling -- Command Injection -- JNDI Injection -- Reflection Injection -- Insecure Configuration -- ... and many more! - -### How can I test Pixee? - -Pixee is most easily tried as a GitHub App. Reach out to us [here](https://pixee.ai/demo-landing-page) and we'll help you get setup. We provide a free tier on our cloud offering that can be installed on any public or private repository. After adding Pixee, you need to get some code scanning results to show the breadth of fixes available. To do that, try adding [SonarCloud](https://www.sonarsource.com/products/sonarcloud/) to it. This is a great way to get started with Pixee and see how it can help to harden and secure your code, and triage your code scanner alerts. - -If you need a repository to test with, we recommend trying Pixee out with a deliberately insecure application. Template repositories containing Java and Python test applications are available in PixeeSandbox: [https://github.com/PixeeSandbox](https://github.com/PixeeSandbox). - -Testing with these deliberately insecure applications can give you an idea of how Pixee works, before installing it directly on your personal or professional repositories. - -For additional details, see the [Installation](/installing) page. - -Pixee also supports self-hosted deployments for organizations that require additional security or compliance measures. To learn more about Pixee self-hosted solutions, please [contact us](https://pixee.ai/demo-landing-page). - -### What does Pixee cost? - -Please see https://www.pixee.ai/pricing. diff --git a/docs/languages.md b/docs/languages.md deleted file mode 100644 index 4c69b2e0..00000000 --- a/docs/languages.md +++ /dev/null @@ -1,43 +0,0 @@ ---- -sidebar_position: 3 ---- - -# Language support - -Pixee has evolved to a language-agnostic platform that can triage and fix security issues across most critical programming languages. Our agentic capabilities are designed to understand and work with diverse codebases, regardless of the underlying language or framework. - -## Currently supported languages - -When triaging and fixing issues detected by code scanning tools, Pixee provides robust support for: - -### Programming Languages - -- Java -- Python -- C#/.NET -- JavaScript -- TypeScript -- Node.js -- Ruby -- Go -- PHP -- Kotlin -- Rust -- Scala -- Swift -- Objective-C - -### Infrastructure as Code - -- Terraform/HCL -- Dockerfile/Containerfile -- Kubernetes/Helm -- CloudFormation -- Ansible -- Docker Compose - -## Expanding language coverage - -Our language-agnostic architecture means we're continuously expanding support to cover more languages and frameworks. If you're working with a language not explicitly listed here, Pixee may still be able to help with security issue triage and remediation. - -For questions about specific language support or to request coverage for additional languages, please [contact us](https://pixee.ai/demo-landing-page). diff --git a/docs/languages/_category_.json b/docs/languages/_category_.json new file mode 100644 index 00000000..6d7b5d40 --- /dev/null +++ b/docs/languages/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Language Support", + "position": 7, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "languages/languages-overview" + } +} diff --git a/docs/languages/languages-overview.md b/docs/languages/languages-overview.md new file mode 100644 index 00000000..18f636cf --- /dev/null +++ b/docs/languages/languages-overview.md @@ -0,0 +1,44 @@ +--- +title: Language Support +slug: /languages/overview +track: both +content_type: guide +seo_title: Language Support -- Pixee Docs +description: Programming languages and IaC formats supported by Pixee for security triage and remediation. +sidebar_position: 1 +--- + +Pixee supports a broad and growing set of languages and IaC formats. Coverage expands continuously as the platform evolves. + +## Programming Languages + +| Language | Common Frameworks (examples) | Common Package Managers (examples) | +| ------------------------------------- | ---------------------------------- | -------------------------------------- | +| **Java** | Spring Boot, Jakarta EE, Micronaut | Maven, Gradle | +| **Python** | Django, Flask, FastAPI | pip, Poetry, Pipenv, conda, setuptools | +| **JavaScript / TypeScript / Node.js** | Express, React, Next.js, Nest.js | npm, yarn, pnpm | +| **C# / .NET** | ASP.NET Core, Blazor | NuGet | +| **Go** | Standard library, Gin, Echo | Go modules | +| **Ruby** | Rails, Sinatra | Bundler (Gemfile) | +| **PHP** | Laravel, Symfony | Composer | +| **Kotlin** | Spring Boot, Android | Maven, Gradle | +| **Rust** | | Cargo | +| **Scala** | Play, Akka | sbt, Maven | +| **Swift** | iOS/macOS | Swift Package Manager | +| **Objective-C** | iOS/macOS | CocoaPods, Carthage | +| **Groovy** | Gradle, Spring, Jenkins | Maven, Gradle | +| **Shell / Bash** | | — | +| **PowerShell** | | — | + +## Infrastructure as Code + +| Format | Notes | +| ------------------------------ | -------------------------------------------------------------------------------- | +| **Terraform / HCL** | Security misconfigurations, IAM policies, storage encryption, network exposure | +| **Dockerfile / Containerfile** | Running as root, insecure base images, exposed secrets in build layers | +| **Kubernetes / Helm** | Pod security contexts, RBAC misconfigurations, exposed secrets, network policies | +| **CloudFormation** | AWS resource misconfigurations, IAM, S3, security groups | +| **Ansible** | Playbook security patterns | +| **Docker Compose** | Service configuration security | + +For what Pixee triages and fixes across these languages and formats, see [What Pixee Fixes](/platform/what-pixee-fixes). Pixee's architecture is designed to work across languages — if yours isn't listed, [contact the team](https://pixee.ai/demo). diff --git a/docs/open-pixee.md b/docs/open-pixee.md deleted file mode 100644 index 98cf848c..00000000 --- a/docs/open-pixee.md +++ /dev/null @@ -1,25 +0,0 @@ ---- -sidebar_position: 5 -title: Open source ---- - -# Open Source - -Pixee believes in open source! We leverage tools from the community and strive to give back when possible. - -## Codemodder - -The fixes we make in Pixee are powered by our open source (and open format!) project called [Codemodder](https://codemodder.io) -- check it out! - -## Contributions - -We've made contributions to the following OSS projects, either directly, or as part of being Pixee free tier users: - -- [JavaParser](https://github.com/javaparser/javaparser) (we're a sponsor as well!) -- [LibCST](https://github.com/Instagram/LibCST/) -- [Quarkus](https://github.com/quarkusio/quarkus) -- [GitHub4j](https://github.com/hub4j/github-api) -- [JUnit](https://github.com/junit-team) -- [Spring Framework](https://github.com/spring-projects/spring-framework) -- [StirlingPDF](https://github.com/Stirling-Tools/Stirling-PDF) -- ... and more! diff --git a/docs/open-source/_category_.json b/docs/open-source/_category_.json new file mode 100644 index 00000000..58b02d3d --- /dev/null +++ b/docs/open-source/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Open Source", + "position": 9, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "open-source/codemodder" + } +} diff --git a/docs/open-source/codemodder.md b/docs/open-source/codemodder.md new file mode 100644 index 00000000..8aec4a4f --- /dev/null +++ b/docs/open-source/codemodder.md @@ -0,0 +1,159 @@ +--- +title: Codemodder Framework +slug: /open-source/codemodder +track: dev +content_type: guide +seo_title: Codemodder Framework -- Pixee Docs +description: Codemodder open source framework for building security-focused code transformations. Supports Java and Python. +sidebar_position: 1 +--- + +# Codemodder Framework + +Codemodder is an open source framework created by Pixee for building language-specific, security-focused code transformations called codemods. Each codemod encodes a specific security remediation pattern — SQL injection parameterization, insecure deserialization hardening, cryptography upgrades — as a deterministic, testable rule. Codemodder currently supports Java via [codemodder-java](https://github.com/pixee/codemodder-java) and Python via [codemodder-python](https://github.com/pixee/codemodder-python), with every codemod publicly inspectable on GitHub. + +Automated code changes demand trust. Open source engines provide that transparency in a way that proprietary black-box tools cannot — security teams and auditors can inspect the exact transformation rules before trusting automated remediation in their codebase. + +All projects are licensed under **Apache 2.0**. + +## Projects + +| Project | Language | Description | +| ---------------------------------------------------------------- | -------------- | ------------------------------------------------------------------------------- | +| [codemodder-java](https://github.com/pixee/codemodder-java) | Java | Java codemod engine with AST transformations via ParseAndGo | +| [codemodder-python](https://github.com/pixee/codemodder-python) | Python | Python codemod engine with LibCST, regex, and XML transformers | +| [Codemodder framework](https://github.com/pixee/codemodder-spec) | Multi-language | Core specification and framework for building language-specific codemod engines | + +## What Codemods Are + +A security codemod is a deterministic rule that transforms insecure code into secure code. "Deterministic" means same input produces the same output every time — no LLM, no variance, no hallucination. Codemods encode decades of OWASP and SANS best practices into testable, repeatable rules. + +For example, a codemod detects raw SQL string concatenation and transforms it into parameterized queries. The fix is the same whether you run it today or a year from now. That predictability is what makes codemods suitable for automated remediation in production codebases. + +## Architecture + +Codemodder has three layers: + +**Framework layer.** Core abstractions for codemod registration, file discovery, transformation execution, and output generation. This layer defines how codemods are built, configured, and run regardless of target language. + +**Language engines.** Language-specific implementations that plug into the framework: + +- **codemodder-java** uses ParseAndGo-based AST transformations. Codemods register into a default codemod set and operate on Java abstract syntax trees. +- **codemodder-python** supports three transformer strategies: LibCST for AST-level transformations, regex for pattern-based changes, and XML for configuration files. A single Python codemod can target source files, config files, or dependency manifests. + +**Output format.** All engines produce a structured JSON report describing every change made — including what was modified, where, and the security rationale — designed to integrate into CI/CD pipelines or review workflows. + +## How Codemods Work + +The transformation pipeline follows a consistent flow from scanner finding to structured output: + +1. **Scanner produces a finding.** A SAST or SCA tool flags a vulnerability and emits a SARIF report identifying the file, line, and rule that triggered. +2. **Codemodder matches a codemod rule.** The engine checks whether a registered codemod handles the finding type (e.g., CWE-89 for SQL injection maps to the SQL parameterization codemod). +3. **The codemod analyzes the vulnerable code.** Using AST parsing (ParseAndGo for Java, LibCST for Python), regex matching, or XML parsing, the codemod identifies the exact code pattern that needs to change. +4. **The transformation applies the security fix.** The codemod rewrites the code deterministically. +5. **The engine writes a structured report.** A JSON document describes what changed and why — both human-readable and machine-parseable. +6. **Developer reviews the change.** In the Pixee platform, the fix becomes a pull request. With the standalone engine, you review the structured report and the modified files directly. + +## codemodder-java + +The Java engine provides a library of deterministic codemods using ParseAndGo-based AST transformations. + +**Fix categories covered:** + +- SQL injection parameterization +- SSRF prevention +- Insecure deserialization hardening +- Weak cryptography replacement (secure random, algorithm upgrades) +- Insecure temp file handling +- SSL/TLS protocol upgrades +- Security hardening patterns from OWASP/SANS + +**Running codemodder-java:** + +```bash +# Clone and build +git clone https://github.com/pixee/codemodder-java.git +cd codemodder-java +./gradlew build + +# Run against a target project +./gradlew run --args="--source /path/to/project --output results.json" + +# Run specific codemods only +./gradlew run --args="--source /path/to/project --codemod-include pixee:java/sql-parameterizer --output results.json" +``` + +## codemodder-python + +The Python engine provides a library of deterministic codemods with three distinct transformer strategies. + +**Transformer strategies:** + +| Strategy | Target | Use Case | +| -------- | ---------------------------- | ---------------------------------------------------------------------- | +| LibCST | Python source files | AST-level transformations (function calls, imports, class definitions) | +| Regex | Config and source files | Pattern-based replacements where AST parsing is unnecessary | +| XML | Dependency manifests, config | XML configuration files and dependency declarations | + +A single codemod can combine strategies. For example, a PyYAML hardening codemod might use LibCST to change `yaml.load()` calls to `yaml.safe_load()` in source files while also updating a requirements file via regex. + +**Fix categories covered:** + +- SQL injection parameterization +- SSRF prevention +- PyYAML safe loading +- Defused XML parsing +- Weak cryptography replacement (secure random, JWT decode verification) +- Security hardening patterns from OWASP/SANS + +**Running codemodder-python:** + +```bash +# Install +pip install codemodder + +# Run against a target project +codemodder /path/to/project --output results.json + +# Run specific codemods only +codemodder /path/to/project --codemod-include pixee:python/secure-random --output results.json + +# Exclude directories +codemodder /path/to/project --path-exclude tests/ vendor/ --output results.json +``` + +## Open Source vs. Pixee Platform + +The open source engines and the commercial Pixee platform serve different needs. + +**Open source engines** provide deterministic codemods only. No AI, no triage, no scanner integration, no PR workflow. You run them locally or in CI/CD and get structured output describing every change. + +**The Pixee platform** builds on the open source engines and adds: + +- **AI-powered fixes** for vulnerability patterns that deterministic rules cannot reach (custom frameworks, multi-file dataflows, context-dependent sanitization) +- **Triage Automation** with false positive reduction via exploitability analysis +- **Native scanner integrations** — see [Integrations](/integrations/overview) for the full list +- **Pull request delivery** so developers review fixes through their existing code review process +- **Enterprise deployment** options including embedded cluster, Helm, and air-gapped environments + +The open source layer is the deterministic foundation. The platform adds intelligence, automation, and enterprise workflow on top. + +## Custom Codemods + +You can build custom codemods on the Codemodder framework for your organization's internal security patterns — internal framework wrappers, custom query builders, organization-specific coding standards. See the [Custom Codemods](/open-source/custom-codemods) tutorial for step-by-step instructions. + +## Contributing + +Contributions are welcome across all Codemodder repositories. New codemods have the highest impact — each one expands the number of vulnerability patterns the community can fix automatically. + +**How to contribute:** + +1. Browse [`good first issue`](https://github.com/pixee/codemodder-java/labels/good%20first%20issue) tags in [codemodder-java](https://github.com/pixee/codemodder-java/issues) or [codemodder-python](https://github.com/pixee/codemodder-python/issues) +2. Open an issue describing your proposed codemod before writing code — this ensures alignment on approach +3. Fork, branch (`feat/codemod-name`), implement, and add before/after test fixtures +4. Run the full test suite (`./gradlew test` for Java, `pytest` for Python) and verify output against a sample repository +5. Submit a pull request referencing the issue, with sample before/after code + +**Quality standards:** Before/after test fixtures are required for every codemod. Codemods must be deterministic — no external API calls, no network dependencies, no randomness. One codemod per PR. + +All contributions are submitted under Apache 2.0. Contributors are credited in release notes. See the CONTRIBUTING.md in each repository for the full workflow. diff --git a/docs/open-source/custom-codemods.md b/docs/open-source/custom-codemods.md new file mode 100644 index 00000000..09a3b17e --- /dev/null +++ b/docs/open-source/custom-codemods.md @@ -0,0 +1,222 @@ +--- +title: Custom Codemods +slug: /open-source/custom-codemods +track: dev +content_type: tutorial +seo_title: Custom Codemods -- Pixee Docs +description: Build custom security codemods using the Codemodder framework. Step-by-step tutorial for Java and Python. +sidebar_position: 3 +--- + +# Custom Codemods + +You can build custom codemods using Pixee's open source [Codemodder](/open-source/codemodder) framework to automate security fixes specific to your organization's codebase patterns. Custom codemods are deterministic transformation rules -- same input, same output, every time. This tutorial walks through building a custom codemod from scratch: defining the detection pattern, writing the transformation, testing it, and deploying it. + +## When to Build Custom Codemods + +The built-in codemods cover common vulnerability patterns from OWASP and SANS (see [Codemodder](/open-source/codemodder) for the full catalog). Custom codemods make sense when: + +- **Your organization has internal security patterns.** You enforce coding standards that go beyond public vulnerability databases. Maybe your team requires all HTTP clients to use an internal `SecureHttpClient` wrapper, or all database access to go through a custom query builder. +- **You use internal frameworks.** Your codebase has framework-specific utilities (e.g., a custom `SafeQueryBuilder` or `AuthenticatedRequestFactory`) that the built-in codemods do not know about. +- **You want auditable, repeatable fixes.** Rather than manually fixing the same pattern across hundreds of files, a codemod applies the same transformation everywhere, consistently and testably. +- **You want to contribute back.** If the pattern is general enough, you can submit your codemod to the open source repositories for the community. + +## Prerequisites + +**For Java codemods:** + +- JDK 17 or later +- Gradle (the codemodder-java build system) +- Familiarity with Java AST concepts (abstract syntax trees) + +**For Python codemods:** + +- Python 3.10 or later +- pip for dependency management +- Familiarity with LibCST or basic regex patterns + +**For both:** + +- A working understanding of the [Codemodder](/open-source/codemodder) architecture +- The vulnerability pattern you want to detect and the fix you want to apply + +## Tutorial: Build a Custom Java Codemod + +This example builds a codemod that detects direct `Statement.execute()` calls with user-controlled input and transforms them into parameterized `PreparedStatement` queries. + +### Step 1: Set Up the Development Environment + +```bash +# Clone the repository +git clone https://github.com/pixee/codemodder-java.git +cd codemodder-java +``` + +Review the project structure. Codemods live in the `core-codemods/` directory. Each codemod is a single class that extends the framework's base codemod class and registers itself for a specific vulnerability pattern. + +### Step 2: Define the Detection Pattern + +Before writing code, define clearly what the codemod detects and what it produces. + +**Vulnerable input (before):** + +```java +String query = "SELECT * FROM users WHERE id = " + userId; +Statement stmt = connection.createStatement(); +stmt.execute(query); +``` + +**Secure output (after):** + +```java +String query = "SELECT * FROM users WHERE id = ?"; +PreparedStatement stmt = connection.prepareStatement(query); +stmt.setString(1, userId); +stmt.execute(); +``` + +The codemod needs to: + +1. Find `Statement.execute()` calls where the query string is built via concatenation +2. Replace the `Statement` with `PreparedStatement` +3. Extract concatenated variables into parameterized placeholders +4. Add the corresponding `setParameter()` calls + +### Step 3: Write the Transformation + +Implement the codemod class by extending the framework's base class. The class declares which CWE or rule ID it handles, and the `visit` method contains the transformation logic. + +The transformation uses ParseAndGo to walk the Java AST, identify `Statement.execute()` nodes, and rewrite them. The framework handles file discovery, change tracking, and structured-report generation. + +Refer to the [codemodder-java CONTRIBUTING guide](https://github.com/pixee/codemodder-java/blob/main/CONTRIBUTING.md) for the current base class interfaces and registration patterns. + +### Step 4: Add Tests + +Every codemod requires before/after test fixtures: + +**Test fixture: `before/SqlInjection.java`** + +```java +// Contains the vulnerable code pattern +String query = "SELECT * FROM users WHERE id = " + userId; +Statement stmt = connection.createStatement(); +stmt.execute(query); +``` + +**Test fixture: `after/SqlInjection.java`** + +```java +// Contains the expected secure code after transformation +String query = "SELECT * FROM users WHERE id = ?"; +PreparedStatement stmt = connection.prepareStatement(query); +stmt.setString(1, userId); +stmt.execute(); +``` + +The test framework automatically runs the codemod against the `before` fixture and asserts the output matches the `after` fixture. Add multiple test cases covering: + +- The primary pattern (direct string concatenation) +- Variations in code style (different variable names, multi-line queries) +- Edge cases (multiple concatenated variables, nested expressions) +- Cases where the codemod should NOT transform (already parameterized queries) + +### Step 5: Register the Codemod + +Add the codemod to the registration system so the engine discovers it at runtime. Registration maps the codemod to its CWE identifier and assigns it a unique codemod ID (e.g., `pixee:java/sql-parameterizer`). + +### Step 6: Run and Validate + +```bash +# Build the project with the new codemod +./gradlew build + +# Run against a test repository +./gradlew run --args="--source /path/to/test-repo --codemod-include pixee:java/sql-parameterizer --output results.json" +``` + +Review the report in `results.json` to verify the changes are correct. The output describes each file modified, the lines changed, and the security rationale. + +## Tutorial: Build a Custom Python Codemod + +Python codemods follow the same pattern with different tooling. This example builds a codemod that detects `yaml.load()` without a safe loader and transforms it to `yaml.safe_load()`. + +### Step 1: Set Up the Development Environment + +```bash +# Clone the repository +git clone https://github.com/pixee/codemodder-python.git +cd codemodder-python +pip install -e ".[dev]" +``` + +### Step 2: Define the Detection Pattern + +**Vulnerable input (before):** + +```python +import yaml + +with open("config.yml") as f: + config = yaml.load(f) +``` + +**Secure output (after):** + +```python +import yaml + +with open("config.yml") as f: + config = yaml.safe_load(f) +``` + +### Step 3: Choose a Transformer Strategy + +Python codemods support three transformer strategies: + +| Strategy | When to Use | This Example | +| ---------- | ---------------------------------------------------------------------------- | ---------------------------------------------------- | +| **LibCST** | Transforming Python source code (function calls, imports, class definitions) | Yes -- rewriting `yaml.load()` to `yaml.safe_load()` | +| **Regex** | Simple pattern replacements in config files or source | Not for this example | +| **XML** | Modifying XML configuration or manifest files | Not for this example | + +For this codemod, LibCST is the right choice because we are transforming a Python function call. + +### Step 4: Write the Transformation + +The codemod class extends the Python framework's base class and uses LibCST to locate `yaml.load()` calls and replace them with `yaml.safe_load()`. The framework handles file traversal, change tracking, and output generation. + +Refer to the [codemodder-python CONTRIBUTING guide](https://github.com/pixee/codemodder-python/blob/main/CONTRIBUTING.md) for the current base class interfaces and visitor patterns. + +### Step 5: Add Tests and Register + +Create before/after test fixtures following the same pattern as Java. Register the codemod with a unique ID (e.g., `pixee:python/safe-yaml-load`). + +### Step 6: Run and Validate + +```bash +# Run against a test repository +codemodder /path/to/test-repo --codemod-include pixee:python/safe-yaml-load --output results.json +``` + +## Testing Best Practices + +Reliable codemods require thorough testing: + +- **Before/after fixtures are mandatory.** Every codemod must have at least one fixture pair demonstrating the transformation. +- **Cover style variations.** Real codebases are messy. Test with different indentation, variable naming, multi-line expressions, and comment placement. +- **Test negative cases.** Include fixtures where the codemod should NOT transform code. A codemod that triggers false positives erodes trust. +- **Edge cases matter.** What happens with nested function calls? What about files with multiple instances of the pattern? What about partial matches? +- **Run against real repositories.** After unit tests pass, run the codemod against an actual codebase to validate behavior at scale. + +## Deploying Custom Codemods + +**Local and CI/CD.** Custom codemods run anywhere Codemodder runs. Add them to your CI/CD pipeline to enforce organization-specific security patterns on every commit: + +```bash +# Example CI/CD step +codemodder $WORKSPACE --codemod-include pixee:python/safe-yaml-load --output results.json +``` + +**Sharing across teams.** Package custom codemods as a separate module that depends on the Codemodder framework. Teams can pull your codemod package alongside the core engine. + +**Contributing upstream.** If your codemod addresses a general vulnerability pattern, consider [contributing it back](/open-source/codemodder#contributing) to the open source repositories so the broader community benefits. diff --git a/docs/platform/_category_.json b/docs/platform/_category_.json new file mode 100644 index 00000000..482998f3 --- /dev/null +++ b/docs/platform/_category_.json @@ -0,0 +1,10 @@ +{ + "label": "Platform", + "position": 2, + "collapsible": true, + "collapsed": false, + "link": { + "type": "doc", + "id": "platform/what-is-agentic-security-engineering" + } +} diff --git a/docs/platform/architecture.md b/docs/platform/architecture.md new file mode 100644 index 00000000..13f43c81 --- /dev/null +++ b/docs/platform/architecture.md @@ -0,0 +1,116 @@ +--- +title: Platform Architecture +slug: /platform/architecture +track: leader +content_type: conceptual +seo_title: "Pixee Platform Architecture | How It All Fits" +description: Three-component architecture with progressive triage, hybrid remediation, and native PR delivery. End-to-end processing flow from scanner finding to merged fix. +sidebar_position: 2 +--- + +Pixee's Agentic Security Engineering Platform uses a three-component architecture — a backend platform, an analysis service, and a user interface — to process vulnerability findings from any scanner through unified triage and remediation pipelines. Findings arrive via webhook or API, pass through a progressive triage engine, and exit as validated pull requests. The system handles everything from sub-second deterministic triage to multi-agent AI fix planning without requiring you to replace any existing tools. + +This page walks through the end-to-end processing flow, from scanner finding to merged fix. + +## End-to-End Processing Flow + +Every vulnerability finding follows the same path through Pixee, regardless of which scanner produced it or which language the code is written in: + +| Stage | What Happens | Output | +| ----------------------- | ---------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | +| **1. Scan Ingestion** | Finding arrives via webhook or API; normalized into a common internal format | Standardized finding with maximum available metadata | +| **2. Triage** | Three-tier progressive analysis determines exploitability | Typed verdict (true positive, false positive, won't fix) with structured evidence | +| **3. Remediation** | Hybrid engine generates a validated fix for confirmed vulnerabilities | Code change that passed independent quality evaluation | +| **4. PR Delivery** | Fix shipped as a native pull request on your platform | Reviewable diff with vulnerability context, quality scores, and description | +| **5. Developer Review** | Your team reviews, tests, and merges through existing workflow | Merged fix or feedback | + +SAST and SCA findings both flow through this same pipeline. There is no separate workflow for dependency vulnerabilities versus first-party code findings. + +## Scan Ingestion + +Findings arrive from natively integrated scanners or any SARIF-producing tool: + +**Native integrations with dedicated handlers:** CodeQL (GitHub Advanced Security), SonarQube/SonarCloud, Checkmarx, Veracode, Snyk Code, Semgrep, AppScan, Polaris, Fortify, Contrast, GitLab SAST, GitLab SCA, Trivy, Arnica, and Datadog SAST. + +Each native integration has a tool-specific handler that extracts maximum metadata from the scanner's output format. CodeQL findings include codeFlows and help documentation. Semgrep findings carry full rule descriptions. Metadata-poor tools like Checkmarx use rule-ID-based strategies to compensate for sparse SARIF output. + +**Universal SARIF fallback:** Any scanner that produces SARIF output works through tool-agnostic processing. Over 50 scanner tools have been validated via this path. No scanner is locked out of the pipeline. + +All findings are normalized into a common internal format before downstream processing. This normalization is what makes the triage and remediation engines scanner-agnostic -- they operate on standardized findings, not raw scanner output. + +## Triage Engine + +The triage engine classifies every finding through a three-tier progressive architecture. Each tier represents a different analysis strategy, and the system routes each finding to the cheapest sufficient tier automatically. + +| Tier | Strategy | Speed | LLM Cost | Best For | +| ---------------------- | -------------------------------------------------------------------------------------------- | ------------------------- | ----------- | ---------------------------------------------------------------------- | +| **Tier 1: Structured** | 15+ deterministic analyzers | Sub-second | Zero | Known patterns (SQL injection, XSS, command injection, path traversal) | +| **Tier 2: Agentic** | AI agents dynamically search the codebase | Seconds | Per-finding | Ambiguous findings, novel frameworks, custom security controls | +| **Tier 3: Adaptive** | Handles novel rule types automatically, expanding coverage as new rule types are encountered | Minutes (first encounter) | Per-finding | Novel rule types, proprietary scanners, custom rulesets | + +**Progressive fallback:** The system attempts Tier 1 first. If the deterministic analyzer cannot reach a high-confidence verdict, the finding escalates to Tier 2. If the agentic investigation cannot resolve it, Tier 3 handles it automatically and coverage expands for future findings of the same type. Most findings resolve at Tier 1. + +A shared context-aware intelligence layer enriches every tier with codebase signals: dataflow quality, production versus test classification, security control detection, and intentionally-vulnerable project filtering. Every verdict includes a typed status, adjusted severity, justification with code snippets, and a confidence score. + +For false positive reduction data, see [Triage Capabilities](/platform/triage). + +For full triage details, see [Triage](/platform/triage). + +## Remediation Engine + +The remediation engine uses a hybrid-intelligence model: deterministic codemods handle known vulnerability patterns, and AI-powered fixes handle everything else. + +**Deterministic codemods:** Pre-built, rule-based transformations for known OWASP/SANS security patterns. Same input, same output, every time. Zero LLM involvement. Zero hallucination risk. Open-source engines (codemodder-java, codemodder-python) are publicly inspectable. See [Remediation](/platform/remediation) for the full codemod library. + +**AI-powered fixes:** Handle custom frameworks, multi-file dataflow vulnerabilities, and novel patterns where deterministic rules cannot reach. Pixee extracts maximum metadata from each scanner's native output format, normalizing findings so the AI receives the right context regardless of source scanner. + +**Multi-agent fix planning:** Complex fixes that span dependency manifests, source files, and configuration changes are planned before execution. Specialized agents handle version decisions, source file identification, and manifest updates independently. Plans are evaluated for quality before code changes begin. + +**Independent fix evaluation:** Every generated fix passes through a separate quality gate scoring Safety (no breaking changes), Effectiveness (resolves the vulnerability), and Cleanliness (code quality). The evaluator runs as a separate inference call -- the generator does not grade its own work. Fixes that fail evaluation are retried with structured feedback or suppressed entirely. + +For merge rate data and trust details, see [Security & Trust](/platform/security). + +For full remediation details, see [Remediation](/platform/remediation). + +## PR Delivery + +Validated fixes are delivered as native pull requests on GitHub, GitLab, Azure DevOps, or Bitbucket. PR-only delivery is a non-negotiable architectural constraint -- there is no mode, setting, or override that allows direct commits. + +Every PR includes: + +- **Full diff** showing exactly what changed +- **Vulnerability context** explaining what the scanner found and why the fix addresses it +- **Quality scores** from the independent fix evaluation +- **Detailed description** with remediation rationale + +Your existing code review policies, CI/CD pipelines, SAST re-scanning, and branch protection rules all apply to Pixee changes exactly as they apply to human-written code. The same SAST tools that found the original vulnerability also scan the proposed fix. + +Standard `git revert` applies if any merged change needs to be undone. There is no runtime dependency on Pixee for merged code -- removing Pixee leaves all previously merged fixes intact as standard code. + +## LLM Orchestration + +Pixee uses hierarchical model routing to assign the right AI capability to each task. Fast triage queries use lightweight models. Deep reasoning tasks use more capable models. Code generation uses models optimized for that purpose. + +The platform supports multiple LLM provider families: + +| Provider Family | Deployment Context | +| ------------------------------- | -------------------------------------- | +| OpenAI | Cloud deployments | +| Azure OpenAI / Azure AI Foundry | Enterprise cloud with Azure compliance | +| Anthropic Claude | Cloud deployments | +| Azure Anthropic | Enterprise cloud with Azure compliance | +| Any OpenAI-compatible endpoint | Custom or self-hosted LLM deployments | + +Customers choose providers based on compliance requirements, cost preferences, or performance needs. Bring Your Own Model (BYOM) support means enterprises deploy the LLM provider that satisfies their AI governance policies. + +For air-gapped deployments, a customer-hosted LLM is required. No code leaves the customer's environment. The only outbound connection is license validation, which can be proxied. + +## Three-Component Stack + +| Component | Responsibility | +| -------------------- | -------------------------------------------------------------------------------------------- | +| **Backend Platform** | Platform orchestration, scan ingestion, PR authoring, API layer, webhook processing | +| **Analysis Service** | Triage analysis, remediation generation, fix evaluation, SCA processing, code transformation | +| **User Interface** | Dashboard, findings management, configuration, reporting | + +The Analysis Service handles the computationally intensive work -- triage decisions, fix generation, and quality evaluation. The Backend Platform manages the integration surface: scanner webhooks, SCM platform APIs, and PR lifecycle. The User Interface provides visibility into triage outcomes, remediation activity, and configuration. diff --git a/docs/platform/context-memory.md b/docs/platform/context-memory.md new file mode 100644 index 00000000..01ef680e --- /dev/null +++ b/docs/platform/context-memory.md @@ -0,0 +1,78 @@ +--- +title: "Context, Memory & Preferences" +slug: /platform/context-memory +track: both +content_type: conceptual +seo_title: "Context, Memory & Preferences | How Pixee Learns Your Codebase" +description: How Pixee reads your codebase, adapts to team conventions, and improves from feedback signals to deliver context-aware fixes. +sidebar_position: 4 +--- + +Pixee is not a generic code scanner that applies one-size-fits-all patches. It reads your repository, learns your team's conventions and frameworks, and improves from the feedback your team provides when it reviews and merges fixes. This page explains how that context is gathered, stored, and used. + +## Codebase Context + +Before Pixee generates a fix, it analyzes the repository for the patterns, frameworks, and security controls already in use. This context shapes every fix Pixee produces. + +**What Pixee reads:** + +- **Existing patterns and conventions** — naming conventions, preferred utility classes, error handling patterns, code style. If your team wraps SQL calls in a `DatabaseHelper`, Pixee generates fixes that use `DatabaseHelper`, not a raw JDBC pattern. +- **Frameworks and libraries in use** — Spring Boot, Django, Express, ASP.NET Core, and others each have idiomatic secure coding patterns. Pixee's framework-aware fixes match what your team already uses. +- **Dependencies** — the libraries and versions in your manifest files inform what fix patterns are available and safe. If your project already includes an input validation library, Pixee prefers it over introducing a new dependency. +- **Existing security controls** — middleware, sanitization utilities, authentication layers, and framework-provided security features. A finding protected by framework-level controls is classified differently from the same pattern without protection. + +This analysis is performed at the repository level for each analysis run. Code is not stored after the analysis completes. See [Security Architecture](/enterprise/security-architecture) for data handling details. + +## PIXEE.yaml + +Team-level preferences and repository configuration are specified in a `PIXEE.yaml` file in the repository root. PIXEE.yaml is the primary mechanism for telling Pixee how to behave in your repository. + +Common configuration includes: + +- Scoping fix generation to specific severity levels, vulnerability types, or repository paths +- Excluding files, directories, or patterns from analysis +- Setting branch targeting preferences +- Configuring PR batching and delivery behavior + +PIXEE.yaml is optional — Pixee works with sensible defaults without it. For the full schema and all available options, see [PIXEE.yaml Reference](/configuration/pixee-yaml). + +## Learning from Feedback + +Pixee improves from the signals your team sends when it interacts with Pixee-generated PRs. These signals are the primary mechanism by which Pixee adapts to your team's preferences and risk tolerance over time. + +**Signals Pixee collects:** + +| Signal | What It Means | +| ------------------------------ | ---------------------------------------------------------------------------------------------- | +| PR merged (as-is) | Fix was correct and matched team conventions — positive signal for this fix pattern | +| PR merged (with modifications) | Fix was directionally correct but needed adjustment — Pixee notes the delta | +| PR closed / declined | Fix was not accepted — negative signal for this finding type or fix approach | +| Triage override | Team disagreed with Pixee's classification — updates classification logic for similar findings | + +**Observing improvement:** Teams that have been using Pixee for several weeks typically see improved triage outcomes and higher merge rates as the system calibrates to their codebase and review preferences. + +## Triage Overrides + +When Pixee classifies a finding as a true positive but your team disagrees — or vice versa — you can override the triage verdict. Overrides are the strongest feedback signal available. + +**How to override:** Overrides can be submitted in three ways: by providing feedback directly on an individual triage result, via natural language preferences in PIXEE.yaml, or through Organization Preferences in the UI. + +**What happens when you override:** + +- The specific finding's verdict is updated immediately. +- The override is recorded with the rationale (if provided). +- Future findings matching the same pattern in the same codebase context receive adjusted classification. + +**Influence on future classifications:** Triage overrides influence how Pixee classifies similar findings going forward. The more specific the context (same rule ID, same file pattern, same framework), the more targeted the adjustment. + +## Enterprise Context + +For organizations with specific policies — approved libraries, banned patterns, internal framework conventions — surfacing that context to Pixee allows fix generation to align with enterprise standards rather than generic open-source patterns. + +**Mechanisms for providing enterprise context:** + +- **PIXEE.yaml** — per-repository configuration for fix scope and behavior preferences. +- **Organization Preferences** — org-level configuration in the UI for specifying approved libraries, banned patterns, and internal framework conventions that apply across all repositories. +- **Codebase reading** — Pixee automatically detects internal libraries and frameworks by analyzing imports, dependency manifests, and usage patterns. If your organization uses an internal HTTP client wrapper, Pixee detects it and uses it in fixes. + +For organizations managing hundreds of repositories, the [Phased Rollout Guide](/enterprise/phased-rollout) covers organization-wide deployment strategy that accounts for repository-level variation in conventions and risk tolerance. diff --git a/docs/platform/remediation.md b/docs/platform/remediation.md new file mode 100644 index 00000000..b34fb2b3 --- /dev/null +++ b/docs/platform/remediation.md @@ -0,0 +1,94 @@ +--- +title: Remediation +slug: /platform/remediation +track: both +content_type: guide +seo_title: "Automated Vulnerability Remediation | 76% Merge Rate" +description: How Pixee generates security fixes using deterministic codemods and AI-powered fixes with independent quality evaluation. +sidebar_position: 4 +--- + +Pixee generates validated security fixes and delivers them as pull requests. The hybrid-intelligence engine routes each vulnerability to the best fix method: deterministic codemods handle known patterns with zero AI variance, while AI-powered fixes handle novel and complex scenarios. Every fix passes independent quality evaluation before reaching a developer. Across production deployments, 76% of Pixee-generated fixes are merged by development teams after human review. + +Remediation is co-equal with [triage](/platform/triage). Triage determines what is real; remediation fixes what is real. + +## Hybrid Intelligence Model + +Pixee uses two fundamentally different fix engines, routed automatically based on vulnerability type: + +| Engine | How It Works | When It Fires | Risk Profile | +| -------------------------- | -------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------- | +| **Deterministic codemods** | Pre-built, rule-based transformations encoding OWASP/SANS patterns | Known patterns: SQL injection parameterization, SSRF prevention, insecure deserialization, weak cryptography, insecure temp files, SSL/TLS upgrades | Zero hallucination risk. Same input, same output, every time. | +| **AI-powered fixes** | Constrained AI generation with dataflow-bounded context and per-rule knowledge base guidance | Custom frameworks, multi-file dataflow vulnerabilities, novel patterns, context-dependent sanitization | AI-generated, independently evaluated before reaching a PR. | + +Routing is automatic. The system checks whether a deterministic codemod exists for the vulnerability type. If yes, the codemod fires — sub-second, zero LLM cost. If no deterministic rule handles it, an AI-powered fix is generated using scanner-aware context. + +**Open-source engines.** The deterministic codemod engines (codemodder-java, codemodder-python) are publicly inspectable. Customers and auditors can read the transformation rules before trusting them. + +**Native scanner support.** Pixee extracts maximum metadata from each scanner's native output format, normalizing findings for consistent downstream processing regardless of source scanner. Native integrations benefit from richer metadata than generic SARIF ingestion. + +## Context Gathering + +Fix quality is bounded by what the system can see. Context gathering adapts based on the quality and completeness of dataflow evidence available for each finding. Pixee evaluates whether the full taint path from source to sink is traceable and adjusts context accordingly — tracing full cross-file dataflow when available, and using targeted excerpts when evidence is limited. + +Key capabilities: follows SARIF-based taint propagation across files, highlights the vulnerable region with inline markers, adapts between whole-file and targeted excerpts based on file size, and merges consecutive vulnerable regions to reduce token cost. + +## Fix Evaluation + +:::info +Every generated fix passes through an independent quality gate before a developer sees it. **Bad fixes are rejected, not shipped** — a fix that cannot pass evaluation is suppressed entirely and never reaches a PR. +::: + +**Three-dimension rubric:** + +| Dimension | What It Checks | Why It Matters | +| ----------------- | ----------------------------------------------------------------- | ----------------------------------------------------------- | +| **Safety** | No breaking changes, no regressions, no unintended side effects | Prevents the fix from creating new problems | +| **Effectiveness** | Correctly resolves the security vulnerability | Prevents cosmetic changes that leave the vulnerability open | +| **Cleanliness** | Proper formatting, no extraneous changes, preserves existing code | Prevents unnecessary diff noise that frustrates reviewers | + +**Architectural independence.** The evaluator runs as a separate inference call — the generator does not grade its own work. This is not self-critique from the same model. The separation prevents the "grading your own homework" failure mode. + +**Retry and suppression.** Fixes that fail evaluation receive specific reasoning and suggestions. The generator uses this feedback to produce a better fix. If a fix still cannot pass after retries, it is suppressed entirely — the developer never sees it. + +**Quality scores are visible.** When a fix passes evaluation and reaches a PR, the Safety, Effectiveness, and Cleanliness scores are included in the PR description. Transparency builds trust over time. + +## Multi-Agent Fix Planning + +Some security fixes span multiple files. A vulnerable dependency may require upgrading the library version in a manifest file, updating import statements, and refactoring call sites — all as a single, atomic change. + +Pixee decomposes complex fixes across specialized agents rather than cramming everything into a single AI prompt: + +- **Version decision logic** — determines which library version resolves the vulnerability while maintaining compatibility +- **Source file identification** — uses the vulnerability's dataflow evidence to identify which source files need edits +- **Manifest declaration updates** — locates the exact line in the manifest file that needs to change + +The fix plan is evaluated for quality before execution begins. Plans that are incomplete or inconsistent receive structured feedback and are refined. Plans that cannot reach acceptable quality are not executed. + +The result is an atomic PR: manifest change plus source-file refactoring in a single pull request. No "upgrade succeeded, tests broken" half-states. + +## Developer Experience + +Fixes ship as native pull requests on GitHub, GitLab, Azure DevOps, or Bitbucket. A typical Pixee PR includes: + +- **Code diff** — usually 1-5 lines adding input validation, parameterized queries, or safe API calls +- **Vulnerability context** — what the scanner found and why it matters +- **Quality scores** — Safety, Effectiveness, and Cleanliness scores from the evaluation gate +- **Fix rationale** — why this specific remediation approach was chosen + +Developers review, modify, reject, or merge like any other code change. Your code review policies, CI/CD pipelines, SAST re-scanning, and branch protection rules all apply. + +Standard `git revert` applies if any merged change needs to be undone. There is no runtime dependency — removing Pixee leaves all previously merged fixes intact as standard code in your repository. + +## Language and Scanner Coverage + +| Coverage Type | Details | +| ------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Languages** | Java, Python, JavaScript/TypeScript, .NET/C#, Go, Ruby, PHP, Kotlin, Rust, Scala, Swift + IaC (Terraform, Dockerfile, K8s/Helm, CloudFormation) | +| **Native scanner integrations** | 15 (CodeQL, SonarQube, Checkmarx, Veracode, Snyk Code, Semgrep, AppScan, Polaris, Fortify, Contrast, GitLab SAST, GitLab SCA, Trivy, Arnica, Datadog SAST) | +| **Universal SARIF** | Any SARIF-producing scanner (50+ validated) | +| **Platforms** | GitHub, GitLab, Azure DevOps, Bitbucket | + +Deterministic codemod coverage is deepest for Java and Python. JavaScript/TypeScript, .NET, Go, and PHP have expanding codemod libraries supplemented by AI-powered generation for patterns not yet covered by deterministic rules. + +SCA findings flow through the same remediation pipeline as SAST findings — see [SCA](/platform/sca) for dependency-specific details. diff --git a/docs/platform/sca.md b/docs/platform/sca.md new file mode 100644 index 00000000..3af09c0a --- /dev/null +++ b/docs/platform/sca.md @@ -0,0 +1,90 @@ +--- +title: SCA +slug: /platform/sca +track: both +content_type: guide +seo_title: "SCA Triage & Remediation | Dependency Vulnerability Verification" +description: How Pixee verifies CVE exploitability in your codebase and delivers atomic dependency upgrade PRs with code-level fixes. +sidebar_position: 5 +--- + +Pixee applies the same triage and remediation model to third-party dependency vulnerabilities that it applies to first-party code findings. When your SCA tools flag a CVE, Pixee determines whether the vulnerability is actually exploitable in your specific codebase — not just whether the version is affected. Confirmed vulnerabilities get atomic upgrade PRs that include both the manifest version bump and any downstream source-file changes. + +SCA findings flow through the same triage engine, remediation pipeline, and PR delivery as SAST findings. No separate tools, no context-switching between first-party and third-party vulnerabilities. + +## Version Matching vs. Exploitability + +Standard SCA tools flag every CVE associated with an affected dependency version, regardless of actual exploitability: + +- **Version matching is not vulnerability matching.** A CVE may require specific configuration or API usage that your code never exercises. +- **CVSS scores carry zero codebase context.** A CVSS 9.8 in a library where the vulnerable function is never called does not represent a 9.8 in your application. + +Pixee answers "Can this CVE actually be triggered in this codebase?" — not just "Is this version theoretically affected?" + +## CVE Exploitability Verification + +**How it works:** + +| Step | What Happens | +| ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| **1. External research** | A CVE research agent gathers CVE details, changelogs, patches, and release notes to identify the specific conditions required for exploitation | +| **2. Internal analysis** | The triage agent examines how the library is actually used in your code — which functions are called, what input reaches them, what security controls exist | +| **3. Evidence-based classification** | Every "Not Exploitable" verdict includes the conditions the CVE requires, analysis of each condition against your code, code snippets demonstrating why conditions are or are not met, and a defensible conclusion | +| **4. Efficient reanalysis** | Previously evaluated CVE+dependency combinations are not reanalyzed unnecessarily, keeping SCA processing efficient across repositories sharing common dependencies | + +**Concrete example:** A scanner flags a Spring WebFlux static resource authorization bypass (CVSS 6.9). The CVE requires three conditions: WebFlux controllers, Spring static resource handling, and a non-permitAll security rule. Pixee's analysis finds no WebFlux controllers, no Spring static resource APIs, and no non-permitAll protection rules. Two of three conditions are unmet. Classification: Not Exploitable, with the evidence. + +**The three approaches compared:** + +| Approach | What It Tells You | What It Misses | +| --------------------------------------- | ----------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- | +| **Version matching** (legacy SCA) | "This dependency version has a known CVE" | Whether the vulnerable function is called, whether exploitation conditions are met, whether security controls mitigate the risk | +| **Basic reachability** | "The vulnerable function is reachable from your code" | Exploitation preconditions, input validation, configuration states | +| **Exploitability verification** (Pixee) | "This CVE requires conditions X, Y, Z. Your code meets/does not meet each one. Here is the evidence." | — | + +## Efficient Reanalysis + +Pixee avoids redundant reanalysis of previously evaluated dependency/vulnerability combinations, keeping SCA processing efficient at scale. Organizations with many repositories sharing common dependencies benefit automatically — repeated CVE analysis across repositories is avoided without requiring manual coordination. + +## Transitive Dependency Handling + +Transitive dependencies require full chain analysis. A vulnerability four layers deep through an unused code path carries different risk than a direct exposure. + +**Key concepts:** + +- **TID (Taint Introducing Dependency):** The direct dependency in your manifest that begins the chain to the vulnerable transitive dependency. This tells developers exactly which dependency to upgrade. +- **TCD (Taint Consuming Dependency):** The package that actually contains the vulnerable code. +- **Severity calibration by depth:** Risk is adjusted based on the depth and nature of the dependency chain. +- **Blast radius analysis:** When multiple taint-initiating dependencies lead to the same vulnerable transitive dependency, Pixee surfaces the combined exposure. + +Pixee traces the full dependency chain from your application root through every intermediate library to the vulnerable package. Developers get a direct answer: which dependency in your manifest to upgrade. + +## Dependency Remediation + +When an SCA finding is confirmed as exploitable, Pixee generates a justified upgrade — not a blind version bump. + +**Justified upgrades only.** The dependency agent bumps a version only when a verified vulnerability and exploitable path justify the change. + +**Multi-manifest support:** + +| Language | Supported Manifest Formats | +| -------------- | -------------------------------------------------------------- | +| **Python** | requirements.txt, pyproject.toml, Pipfile, setup.py, setup.cfg | +| **Java** | pom.xml, build.gradle | +| **JavaScript** | package.json | +| **.NET** | .csproj, packages.config | + +**Atomic PRs.** A single Pixee PR contains both the manifest version bump AND the downstream source-file changes the upgrade requires. When a major version upgrade changes an API, the import statements and call sites are updated in the same diff. No "upgrade succeeded, tests broken" half-states. + +**Fix evaluation gate.** The same three-dimension quality rubric (Safety, Effectiveness, Cleanliness) that validates SAST fixes also validates dependency upgrade PRs. + +## Cross-Tool Intelligence + +The SCA pipeline benefits from Pixee's unified platform architecture. SAST and SCA findings share context and inform each other: + +| Intelligence Source | What It Provides | +| ------------------------------- | ---------------------------------------------------------------------------------------------------------------- | +| **SAST results** | Inform SCA risk scoring — a dependency vulnerability in code that also has SAST findings carries compounded risk | +| **Historical triage decisions** | Prevent re-triaging the same CVEs across repositories | +| **Secure coding guidelines** | Team preferences in natural language enrich SCA analysis | +| **GitHub PRs and Jira tickets** | Previous SCA upgrade context provides upgrade history | diff --git a/docs/platform/scanner-integration.md b/docs/platform/scanner-integration.md new file mode 100644 index 00000000..1173aaa7 --- /dev/null +++ b/docs/platform/scanner-integration.md @@ -0,0 +1,97 @@ +--- +title: Scanner Integration +slug: /platform/scanner-integration +track: both +content_type: guide +seo_title: "Scanner Integration | Native Scanners + Universal SARIF" +description: How Pixee integrates with natively supported scanners and any SARIF-producing tool. Two-tier integration architecture and metadata extraction. +sidebar_position: 7 +--- + +Pixee integrates with a growing list of natively supported scanners and any SARIF-producing tool through a two-tier architecture. Dedicated handlers extract scanner-specific metadata from tools like CodeQL, Semgrep, and Checkmarx for maximum triage accuracy. Universal SARIF ingestion handles everything else — including proprietary and internal scanners — with zero pre-built integration required. + +Pixee does not replace your scanners. It sits downstream of them. Your existing SAST tools continue to scan your code exactly as they do today. Pixee consumes each tool's output, triages every finding, and delivers remediation as pull requests for confirmed vulnerabilities. + +## Two-Tier Integration Architecture + +**Tier 1 — Native (Dedicated) Handlers.** For the most widely deployed SAST tools, Pixee has dedicated handlers that extract scanner-specific metadata. Each handler understands the idiosyncrasies of that tool's SARIF output — where rule descriptions live, whether dataflow traces are available, and what metadata the scanner includes or omits. Richer metadata extraction means higher triage accuracy. + +**Tier 2 — Universal SARIF Ingestion.** For any scanner that produces SARIF output (the OASIS open standard for static analysis results), Pixee ingests findings automatically. No pre-built integration required. The system dynamically adapts its handling strategy based on whatever metadata the SARIF contains. + +Both tiers feed into the same downstream [triage](/platform/triage) and [remediation](/platform/remediation) pipeline. + +## Deep Scanner Integrations + +### CodeQL (GitHub Advanced Security) + +- Extracts **codeFlows** — multi-step source-to-sink dataflow traces that give the triage engine full dataflow context +- Handles CodeQL's non-standard SARIF behavior where rule metadata is stored on `tool.extensions` rather than `driver` +- Extracts `help.markdown` from rule metadata for rich vulnerability descriptions +- Pre-configured handlers for common CodeQL rules + +### Semgrep + +- Extracts `fullDescription.text` for rule explanations used in triage context +- Supports both Semgrep OSS and Semgrep Pro rule output + +### Checkmarx + +- Compensates for Checkmarx's sparse SARIF output (minimal rule descriptions, no codeFlows) +- Uses compensatory strategies that re-derive triage context directly from the codebase when scanner metadata is sparse +- Includes Checkmarx-specific remediation codemods (SQL parameterization for .NET and JavaScript, NoSQL parameterization for JavaScript) + +## Standard Scanner Integrations + +| Scanner | Status | Integration Method | +| -------------------------- | ------ | ----------------------------------------------------------- | +| **Veracode** | GA | SARIF pipeline with tool-specific identification | +| **Snyk Code** | GA | SARIF pipeline with native metadata extraction | +| **SonarQube / SonarCloud** | GA | SARIF pipeline with native metadata extraction | +| **HCL AppScan** | GA | SARIF ingestion pipeline | +| **Polaris (Synopsys)** | GA | SARIF ingestion pipeline | +| **Fortify** | GA | SARIF ingestion pipeline | +| **Contrast** | GA | SARIF ingestion pipeline | +| **GitLab SAST** | GA | SARIF pipeline with dedicated namespace | +| **GitLab SCA** | GA | SARIF pipeline | +| **Trivy** | GA | SARIF pipeline with native metadata extraction | +| **DefectDojo** | GA | SARIF pipeline (aggregates findings from multiple scanners) | + +All named scanner integrations are GA. See individual scanner integration pages under [Integrations](/integrations/overview) for per-tool setup guides. + +## Universal SARIF Support + +Any scanner that produces SARIF output works with Pixee — no pre-built integration required. + +**SARIF** (Static Analysis Results Interchange Format) is the OASIS open standard for static analysis results. Most modern SAST, SCA, and secret-scanning tools produce SARIF output natively or via converters. + +- Internal and proprietary scanners that output SARIF work out of the box +- New commercial scanners are supported on day one if they produce SARIF +- The system dynamically adapts its handling strategy based on available metadata +- Resilient processing degrades gracefully on malformed or novel tool output + +Over 50 scanner tools have been validated via this path. + +## What Metadata Matters + +Triage accuracy scales with the richness of metadata each scanner includes in its SARIF output. + +| Metadata Type | Which Scanners Provide It | How Pixee Uses It | +| ----------------------------------- | ------------------------------------------------------ | ------------------------------------------------------------------------- | +| **codeFlows** (dataflow paths) | CodeQL (multi-step source-to-sink) | Full dataflow context for triage | +| **Rule descriptions** | Semgrep (fullDescription.text), CodeQL (help.markdown) | Enriches triage context with rule semantics | +| **Severity ratings** | Most scanners | Input to context-aware severity adjustment | +| **Language tags** | Most scanners | Routes to language-specific codemods and analysis strategies | +| **Rule ID only** (minimal metadata) | Checkmarx, some internal tools | Triggers compensatory strategies that re-derive context from the codebase | + +Rich-metadata scanners get deep extraction. Sparse-metadata scanners get compensatory strategies. No scanner is left behind. + +## Platform Integrations + +| Platform | SARIF Ingestion | Native CodeQL/GHAS | Notes | +| ---------------- | --------------- | ------------------ | -------------------------------------------- | +| **GitHub** | Full support | Deep integration | CodeQL findings via GHAS API or SARIF upload | +| **GitLab** | Full support | Via SARIF upload | GitLab SAST has dedicated namespace | +| **Azure DevOps** | Full support | Via SARIF upload | Standard SARIF pipeline | +| **Bitbucket** | Full support | Via SARIF upload | Standard SARIF pipeline | + +All scanner integrations are available across SaaS and Enterprise deployment models. diff --git a/docs/platform/security.md b/docs/platform/security.md new file mode 100644 index 00000000..fd420e63 --- /dev/null +++ b/docs/platform/security.md @@ -0,0 +1,124 @@ +--- +title: "Security & Trust" +slug: /platform/security +track: both +content_type: guide +seo_title: "Security & Trust | Pixee AI Safety and Guardrails" +description: How Pixee validates AI-generated fixes, protects your code, and preserves human authority. Fix validation layers, data handling, and deployment models. +sidebar_position: 6 +--- + +Pixee applies multiple independent validation layers before any AI-generated code change reaches a developer. Every fix passes automated quality evaluation, and every fix ships as a pull request — never a direct commit. Your existing code review, CI/CD pipelines, and SAST re-scanning all apply to Pixee changes exactly as they do to human-written code. The measured result: a 76% merge rate on production deployments. + +## Trust Framework + +Pixee's trust model rests on three governing principles: + +**1. Narrow scope.** Pixee fixes SAST-identified security issues — typically 1-5 lines adding input validation, parameterized queries, or safe API calls. It does not write features, generate business logic, or create new functionality. + +**2. Defense in depth.** No single validation layer is considered sufficient. Multiple independent checks operate in sequence: constrained generation, independent evaluation, pull request review, CI/CD testing, and SAST re-scanning. If one layer misses something, the next catches it. + +**3. Human authority preserved.** Pixee adds validation layers before changes reach your existing review process. Developers always have final approval. There is no mode, setting, or override that bypasses human review. + +## Deterministic vs. AI Fixes + +This distinction is the most important concept on this page. + +| Dimension | Deterministic Codemods | AI-Generated Fixes | +| ------------------------------- | ------------------------------------------------------------------------------ | --------------------------------------------------------------------- | +| **Input/output predictability** | Identical output every time | Output varies based on context; constrained by dataflow-bounded input | +| **Scope** | Known vulnerability patterns (SQL injection, XSS, SSRF, deserialization, etc.) | Novel, custom, and multi-file patterns | +| **Hallucination risk** | Zero | Mitigated by independent evaluation and retry/suppression | +| **Validation requirement** | Pre-validated by design; open-source engines inspectable | Mandatory independent evaluation gate | +| **LLM involvement** | None | Constrained generation with per-rule knowledge base guidance | + +**Deterministic codemods** handle known vulnerability patterns — SQL injection parameterization, SSRF prevention, insecure deserialization, weak cryptography, and more. These are pre-built, rule-based transformations with zero LLM involvement. The open-source engines (codemodder-java, codemodder-python) are publicly inspectable — your security team or auditors can review the transformation rules before deployment. + +**AI-powered fixes** fire only when deterministic rules cannot reach — custom framework wrappers, multi-file dataflow vulnerabilities, novel patterns. Every AI-powered fix passes through the full independent evaluation pipeline. + +Routing between modes is automatic — no manual configuration. + +## Independent Fix Evaluation + +Every AI-generated fix passes through an independent quality gate before a developer sees it. + +**Separate inference call, not self-critique.** The evaluator runs as a structurally independent inference call — separate context window, separate system prompt, separate scoring rubric — not the same process that generated the fix. This prevents the "grading your own homework" failure mode. + +**Three-dimension rubric:** + +| Dimension | What It Checks | +| ----------------- | -------------------------------------------------------------------------------------------------------------------------- | +| **Safety** | No behavior changes beyond fixing the vulnerability. No breaking API changes, missing imports, or unintended side effects. | +| **Effectiveness** | Correctly addresses the security issue. The SAST scanner should stop flagging this finding after the fix is applied. | +| **Cleanliness** | Proper formatting, indentation, no extraneous changes. Preserves existing comments and code structure. | + +**All three dimensions must pass.** This is not an aggregate score that lets a dangerous fix through because it scored well on formatting. + +**Structured feedback loop.** Fixes that fail receive specific reasoning. The generator uses this feedback to produce a better fix. If a fix still cannot pass after retries, it is suppressed entirely — with the suppression reasoning logged. + +## Your Existing Gates Still Apply + +Pixee adds validation before your existing quality controls. It does not replace them. + +After Pixee creates a PR: + +1. **Code review** by your development team +2. **CI/CD pipeline execution** — tests, builds, and any other automated checks +3. **SAST re-scanning** by the same tools that found the original vulnerability +4. **Branch protection rules** and merge requirements you have configured + +Every Pixee change flows through your full approval pipeline. PR-only delivery is an architectural constraint — there is no mode, setting, or override that allows direct branch commits. + +## Data Handling + +**Input scope limitation.** Only code relevant to the specific vulnerability is sent to AI models — not entire repositories. File paths are relative to project root only. No absolute paths, repository URLs, git metadata, commit hashes, or author information are sent. + +**Stateless inference.** Each analysis is isolated. A single analysis cannot modify the model, persist across analyses, or affect other applications. + +**Adversarial input protection.** Code analyzed by an LLM is itself a potential attack vector — malicious comments or string literals could attempt prompt injection. Mitigations: input scope limitation (only vulnerability-relevant snippets sent), independent output validation (separate evaluator catches anomalous fixes), narrow generation scope (constrained to OWASP/SANS patterns), and deterministic-first routing (most fixes use zero-LLM codemods). + +**Customer-controlled AI deployment.** Pixee uses your own AI deployment — Azure OpenAI, Azure AI Foundry, Anthropic Claude, or any OpenAI-compatible endpoint. Your contractual terms with that provider govern data handling. + +## Deployment Models + +| Model | What It Provides | +| ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Dedicated SaaS** | Pixee-managed infrastructure, dedicated single-tenant environment per customer. Pixee accesses repositories via SCM integration (read-only code access, write access limited to PR creation). | +| **Embedded cluster** | Turnkey self-hosted deployment on a single Linux VM. No Kubernetes expertise required. All data stays in your network. | +| **Helm / BYO Kubernetes** | Deploys into your existing Kubernetes infrastructure (EKS, GKE, AKS, or self-managed). | +| **Air-gapped** | Fully disconnected operation with customer-hosted LLM. Zero outbound internet after installation. | + +For air-gapped deployments, a customer-hosted LLM is required. The only outbound connection is license validation, which can be proxied. + +## Rollback and Reversibility + +- **Standard git revert.** Every Pixee change is a normal Git commit within a pull request. +- **Full traceability.** All fixes are stored in Git history with complete context. +- **No lock-in dependency.** If Pixee were removed entirely, all previously merged fixes remain as standard code in the repository. +- **Pre-merge rejection is trivial.** Closing a PR without merging discards the proposed change with zero impact. + +## Responsible AI Governance + +Pixee is designed for AI governance committee review. Concrete answers to common governance questions: + +| Question | Answer | +| ----------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **What does the AI generate?** | Security fixes only — 1-5 line changes applying OWASP/SANS patterns. | +| **Who validates the output?** | An independent evaluation layer (separate inference call), then your developers via PR review, then your CI/CD and SAST re-scanning. | +| **Can it bypass human approval?** | No. PR-only delivery is an architectural constraint, not a configuration option. | +| **What data does it access?** | Only code relevant to the specific vulnerability. No entire repositories, no PII, no secrets. | +| **What if it is wrong?** | Fixes that fail quality evaluation are suppressed. Fixes that pass are reviewed by developers. Merged fixes can be reverted with standard Git operations. | +| **What is the deterministic floor?** | Common vulnerability patterns are fixed with zero AI involvement using publicly inspectable, open-source codemod engines. | +| **What controls exist on the AI itself?** | Constrained generation with security-specific context only, independent evaluation, structured retry with feedback, suppression on failure. | + +## Audit Defensibility + +For regulated industries, every Pixee fix creates a defensible audit record: + +- Typed triage verdict (true positive, false positive, won't fix, suspicious) with code-level evidence +- Fix quality scores (Safety, Effectiveness, Cleanliness) on every PR +- Full Git history showing what changed, when, and why +- SAST re-scanning confirmation that the fix does not introduce new findings +- Developer approval recorded in the merge event + +Compliance teams reviewing automated code changes need to see that the change was validated by independent evaluation, reviewed by a human, tested by CI/CD, and re-scanned by the same tools that found the original issue. Pixee's pipeline provides all four. diff --git a/docs/platform/triage.md b/docs/platform/triage.md new file mode 100644 index 00000000..591e167f --- /dev/null +++ b/docs/platform/triage.md @@ -0,0 +1,94 @@ +--- +title: Triage +slug: /platform/triage +track: both +content_type: guide +seo_title: "Automated Vulnerability Triage | Up to 98% False Positive Reduction" +description: How Pixee's three-tier triage engine classifies every vulnerability finding with structured, auditable evidence. +sidebar_position: 3 +--- + +Pixee's triage engine classifies every vulnerability finding as true positive, false positive, or won't-fix through codebase-aware exploitability analysis. The three-tier progressive architecture handles known patterns at sub-second speed, investigates ambiguous cases via AI agents, and generates custom analyzers for novel vulnerability types. + +:::info[Up to 98% false positive reduction] +Every verdict includes structured, auditable evidence — specific code paths, security controls, or context signals that drove the decision. Not a score. An investigation trail. +::: + +Triage is co-equal with [remediation](/platform/remediation). Together they close the loop from "scanner found something" to "vulnerability is fixed." + +## Three-Tier Progressive Architecture + +Pixee routes every finding through a tiered system that applies the cheapest sufficient intelligence. Routing is automatic — no configuration required. + +| Tier | Strategy | Speed | Coverage | +| ---------------------- | --------------------------------------------------------------------------- | ------------------------- | ------------------------------------------------------------------------------ | +| **Tier 1: Structured** | 15+ deterministic analyzers — no LLM, zero cost | Sub-second | Known classes: SQL injection, XSS, command injection, path traversal, 12+ more | +| **Tier 2: Agentic** | AI agents dynamically search the codebase | Seconds | Ambiguous findings, novel frameworks, custom security controls | +| **Tier 3: Adaptive** | Auto-generates coverage for novel rule types; expands on each new encounter | Minutes (first encounter) | Proprietary scanners, custom Semgrep/CodeQL rules, internal rulesets | + +**End-to-end flow:** + +1. A finding arrives from any SARIF-producing scanner. +2. Tier 1 checks whether a deterministic analyzer exists for this vulnerability class. If yes and confidence is sufficient, triage completes at sub-second speed. +3. If Tier 1 cannot decide, the finding routes to Tier 2. An AI agent investigates the codebase — searching for security controls, tracing dataflow, and building an evidence chain. +4. If Tier 2 cannot resolve the finding (typically because the rule type is novel), Tier 3 handles it automatically and coverage expands for future findings of the same type. +5. Regardless of which tier resolved it, every finding exits with the same structured verdict. + +**Cost efficiency:** Most findings resolve at Tier 1, where there is no LLM cost. Only genuinely complex findings incur AI inference cost. + +**Expanding coverage:** Pixee handles novel and custom rule types automatically — including proprietary scanners, custom Semgrep rules, and internal CodeQL queries — without manual configuration. Coverage expands as new rule types are encountered. + +## Context-Aware Intelligence + +A shared intelligence layer enriches all three tiers with codebase context. Reachability analysis alone is not sufficient — reachability tells you whether code can be reached, not whether a vulnerability is actually exploitable. + +**Context signals evaluated on every finding:** + +**Dataflow quality.** Pixee evaluates the quality and completeness of dataflow evidence available for each finding. Findings with stronger dataflow evidence — where the full taint path from source to sink is traceable — receive higher-confidence verdicts. Findings with limited dataflow evidence are handled conservatively. + +**Production vs. test classification.** A SQL injection in a production API endpoint is critical. The same pattern in a test fixture is not. Pixee classifies code context and adjusts severity accordingly, so dashboards reflect real exploit risk rather than raw rule counts. + +**Security control detection.** When a sanitizer, validator, or framework-specific protection exists between a source and a sink, the system identifies it and factors it into the verdict. This is the difference between "this function is reachable" and "this function is reachable but the input is sanitized before it arrives." + +**Intentionally-vulnerable project filtering.** Demo applications, CTF challenges, and security training repositories generate permanent scanner noise. Pixee detects these projects and filters them from the triage pipeline. + +**Severity adjustment.** When context signals indicate real-world risk differs from raw scanner severity, the system adjusts up or down. Every adjustment includes an audit trail. + +## Triage Outcomes + +Every triage verdict is a structured, machine-processable artifact. + +| Status | Meaning | Recommended Action | +| ------------------ | ----------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------- | +| **True Positive** | The finding is a real, exploitable vulnerability in this code context | Escalate for remediation — Pixee can generate a fix automatically | +| **False Positive** | The scanner fired on a pattern that is not exploitable in this context | Suppress from developer view; remove from backlog noise | +| **Won't Fix** | Technically real but not worth fixing given the context (test code, acceptable risk, compensating controls) | Deprioritize; document the rationale for auditors | +| **Suspicious** | Insufficient evidence for a definitive verdict | Route to a security engineer for manual assessment | + +**What ships with every verdict:** + +| Component | What It Contains | +| ---------------------------------- | ----------------------------------------------------------------------------------- | +| **Typed status** | True Positive, False Positive, Won't Fix, or Suspicious — not a numeric score | +| **Adjusted severity** | Severity re-ranked based on context signals | +| **Justification prose** | Human-readable explanation of why this verdict was reached | +| **Code snippets** | The sanitizer location, dataflow path, or framework control that drove the decision | +| **Confidence score** | Quantified confidence in the verdict | +| **Investigation trail** (Tier 2/3) | Step-by-step record of agent searches, control checks, and reasoning chain | + +**Audit defensibility.** Compliance officers and auditors see exactly why a finding was suppressed. The justification and code snippets provide a defensible record for every triage decision. + +**Machine processability.** Typed statuses mean downstream systems can consume verdicts programmatically — dashboards, workflow triggers, SLA tracking, and SIEM integrations all work with structured data rather than freeform text. + +**Override capability.** Security engineers can disagree with a verdict and override it, because they can see exactly what evidence the system used. Overrides are recorded and used to improve future classifications for your codebase. + +## Scanner-Agnostic Coverage + +Triage works across any SARIF-producing scanner. Customers with heterogeneous stacks — multiple commercial scanners plus custom rules — get a single triage layer that handles all of it. + +- **Natively integrated scanners** with scanner-specific metadata extraction (CodeQL, SonarQube, Checkmarx, Veracode, Snyk Code, Semgrep, AppScan, Polaris, Fortify, Contrast, GitLab SAST, GitLab SCA, Trivy, and others) +- **Universal SARIF ingestion** for any additional scanner (50+ validated) +- **Custom rule coverage** — proprietary Semgrep rules, internal CodeQL queries, and custom scanner rulesets are handled by Tier 2 and Tier 3 without vendor integration work +- **Cross-tool deduplication** — when multiple scanners flag the same finding, the system eliminates duplicates + +The triage layer sits above your existing detection stack. You do not need to change, consolidate, or replace any scanners to use Pixee. diff --git a/docs/platform/what-is-agentic-security-engineering.md b/docs/platform/what-is-agentic-security-engineering.md new file mode 100644 index 00000000..65c06ad4 --- /dev/null +++ b/docs/platform/what-is-agentic-security-engineering.md @@ -0,0 +1,76 @@ +--- +title: What is Agentic Security Engineering? +slug: /platform/what-is-agentic-security-engineering +track: leader +content_type: conceptual +seo_title: "What is Agentic Security Engineering? | Pixee" +description: Agentic security engineering uses purpose-built AI agents to triage and remediate application security vulnerabilities. Definition, architecture, and processing flow. +sidebar_position: 1 +--- + +Agentic security engineering is a discipline where purpose-built AI agents autonomously triage and remediate application security vulnerabilities across the full development lifecycle. Pixee sits downstream of your existing scanners — receiving findings via webhook or API, determining which are exploitable, generating validated fixes, and delivering them as pull requests. + +## The Four-Layer Security Stack + +Pixee adds triage, remediation, and delivery layers on top of your existing detection tools: + +| Layer | Function | Who Provides It | +| ------------------ | ----------------------------------------- | ------------------------------------------------------------------------------------ | +| **1. Detection** | Find vulnerabilities | Your existing scanners (SonarQube, Checkmarx, Semgrep, CodeQL, Snyk, Veracode, etc.) | +| **2. Triage** | Determine which findings are real threats | Pixee — see [Triage](/platform/triage) | +| **3. Remediation** | Generate validated code fixes | Pixee — deterministic + AI hybrid. See [Remediation](/platform/remediation) | +| **4. Delivery** | Ship fixes through existing workflow | Pixee — PRs in GitHub, GitLab, ADO, Bitbucket | + +Pixee integrates natively with a growing list of scanners and accepts any SARIF-producing tool. No changes to your detection stack are required. + +## Two Co-Equal Capabilities + +### Triage Automation + +Every scanner finding passes through exploitability analysis that goes beyond basic pattern matching. The triage engine classifies each finding as TRUE_POSITIVE, FALSE_POSITIVE, or WONT_FIX. Every classification includes a structured justification — the specific code paths, security controls, or context that drove the decision. This is not a confidence score. It is an auditable investigation trail. + +Up to 98% false positive reduction. See [Triage](/platform/triage) for the full architecture. + +### Remediation Automation + +For confirmed vulnerabilities, the platform generates context-aware code fixes: + +- **Deterministic codemods:** Pre-built, rule-based transformations for known vulnerability patterns. Same input, same output, every time. Zero LLM involvement. Zero hallucination risk. +- **AI-powered fixes:** For novel or complex patterns where deterministic rules cannot reach, constrained AI generates fixes that are independently evaluated for Safety, Effectiveness, and Cleanliness before any developer sees them. +- **Pull request delivery:** Every fix ships as a standard PR in GitHub, GitLab, Azure DevOps, or Bitbucket. Never a direct commit. + +76% merge rate on production deployments. See [Remediation](/platform/remediation) and [Security & Trust](/platform/security) for details. + +## What Makes It "Agentic" + +The term "agentic" distinguishes this approach from both rule-based automation and general-purpose AI coding tools: + +**Purpose-built agents, not general-purpose assistants.** These agents are built for security vulnerability analysis. They do not write features, generate business logic, or perform open-ended code completion. Their scope is narrow: SAST-identified security issues, typically 1-5 lines of code applying OWASP/SANS established patterns. + +**Reasoning-and-acting loop.** Agents observe a finding, select an investigative tool (code search, call-graph traversal, security-control detection), execute it, evaluate the result, and iterate until they have sufficient evidence to make a classification. This is a dynamic investigation, not a single-pass classification. + +**Multi-agent orchestration.** Specialized agents handle distinct tasks independently: triage analysis, fix planning, dependency resolution, and fix quality evaluation. The agent that generates a fix is not the agent that evaluates it — preventing self-grading. + +**Hybrid intelligence architecture.** The system routes each task to the cheapest sufficient method. Known patterns get deterministic rules (sub-second, zero cost). Complex patterns get AI investigation. Novel and custom rule types — including proprietary scanners and custom rulesets — are handled automatically, with coverage expanding as new rule types are encountered. Routing is automatic. + +## End-to-End Processing Flow + +| Stage | What Happens | Output | +| ----------------------- | ---------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | +| **1. Scan Ingestion** | Finding arrives via webhook or API; normalized into a common internal format | Standardized finding with maximum available metadata | +| **2. Triage** | Three-tier progressive analysis determines exploitability | Typed verdict (true positive, false positive, won't fix) with structured evidence | +| **3. Remediation** | Hybrid engine generates a validated fix for confirmed vulnerabilities | Code change that passed independent quality evaluation | +| **4. PR Delivery** | Fix shipped as a native pull request on your platform | Reviewable diff with vulnerability context, quality scores, and description | +| **5. Developer Review** | Your team reviews, tests, and merges through existing workflow | Merged fix or feedback | + +SAST and SCA findings both flow through this same pipeline. + +## Technical Stack + +| Component | Responsibility | +| -------------------- | -------------------------------------------------------------------------------------------- | +| **Backend Platform** | Platform orchestration, scan ingestion, PR authoring, API layer, webhook processing | +| **Analysis Service** | Triage analysis, remediation generation, fix evaluation, SCA processing, code transformation | +| **User Interface** | Dashboard, findings management, configuration, reporting | + +See [Platform Architecture](/platform/architecture) for the full technical stack and LLM orchestration details. diff --git a/docs/platform/what-pixee-fixes.md b/docs/platform/what-pixee-fixes.md new file mode 100644 index 00000000..94fc65da --- /dev/null +++ b/docs/platform/what-pixee-fixes.md @@ -0,0 +1,76 @@ +--- +title: What Pixee Fixes +slug: /platform/what-pixee-fixes +track: both +content_type: reference +seo_title: "What Pixee Fixes | Vulnerability Types, Triage, and Fix Modes" +description: Canonical reference for all vulnerability types, finding categories, and fix modes Pixee handles across SAST, SCA, and IaC findings. +sidebar_position: 3 +--- + +This page is the canonical reference for what Pixee can triage and fix. It covers all vulnerability types and finding categories across SAST, SCA, and IaC findings. + +## Vulnerability Coverage Table + +| Vulnerability Category | Examples | Triage | Fix Mode | +| -------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- | ------ | -------------------- | +| **Injection — SQL** | SQL injection via string concatenation, unparameterized queries | Yes | Deterministic / Both | +| **Injection — Command** | OS command injection, shell metacharacters in exec calls | Yes | Deterministic / Both | +| **Injection — LDAP** | LDAP injection via unsanitized directory search filters | Yes | AI | +| **Injection — XPath** | XPath injection via user-controlled node selection | Yes | AI | +| **Injection — NoSQL** | NoSQL injection in MongoDB, Redis, and similar query patterns | Yes | AI | +| **Injection — Expression Language** | EL/OGNL injection via template or framework evaluation | Yes | AI | +| **Cross-Site Scripting (XSS) — Reflected** | Reflected XSS via unencoded user input in HTTP responses | Yes | Deterministic / Both | +| **Cross-Site Scripting (XSS) — Stored** | Stored XSS persisted in database and rendered to other users | Yes | Both | +| **Cross-Site Scripting (XSS) — DOM-Based** | DOM XSS via document.write, innerHTML, eval with user data | Yes | Both | +| **Path Traversal** | Directory traversal via `../` sequences, file inclusion flaws | Yes | Deterministic / Both | +| **Server-Side Request Forgery (SSRF)** | SSRF via unvalidated URL parameters to internal or cloud metadata endpoints | Yes | Deterministic / Both | +| **Insecure Deserialization** | Unsafe deserialization of untrusted data | Yes | Both | +| **Weak Cryptography** | MD5, SHA-1 for security-sensitive operations; ECB mode; short key lengths | Yes | Deterministic / Both | +| **Insecure Randomness** | Insecure random number generators used for security-sensitive tokens | Yes | Deterministic / Both | +| **Hardcoded Secrets** | Hardcoded API keys, passwords, tokens in source code | Yes | AI | +| **Authentication / Session Weaknesses** | Broken authentication, session fixation, missing session invalidation, insecure cookie flags | Yes | Both | +| **Insecure Direct Object Reference (IDOR)** | Missing authorization checks on resource identifiers | Yes | AI | +| **XML / XXE Vulnerabilities** | XML External Entity injection, DTD processing, XXE via SSRF | Yes | Deterministic / Both | +| **Insecure Temp Files** | Predictable temp file creation, race conditions on tempfile usage | Yes | Deterministic / Both | +| **Logging Sensitive Data** | PII, credentials, tokens written to logs | Yes | AI | +| **Security Misconfigurations** | Missing security headers, insecure defaults, disabled CSRF protection | Yes | Both | +| **SSL/TLS Weaknesses** | Disabled hostname verification, accepting all certificates, weak protocols | Yes | Deterministic / Both | +| **Dependency Vulnerabilities (SCA)** | CVEs in direct and transitive open-source dependencies | Yes | Deterministic / Both | +| **Container / Dockerfile Misconfigurations** | Running as root, insecure base image patterns, exposed secrets in layers | Yes | Both | +| **Infrastructure as Code (IaC) Misconfigurations** | Terraform / CloudFormation / Kubernetes / Helm security misconfigurations, overly permissive IAM, unencrypted storage | Yes | Both | +| **Open Redirect** | Redirects to attacker-controlled URLs via unvalidated redirect parameters | Yes | Both | +| **Code Injection / Eval Injection** | Dynamic code execution from untrusted input | Yes | Both | +| **Prototype Pollution** | JavaScript object prototype manipulation via untrusted key assignment | Yes | Both | +| **Template Injection (SSTI)** | Server-side template injection via user input rendered in template engines | Yes | Both | +| **Insecure File Upload** | Unrestricted file type or content upload without validation | Yes | Both | +| **Missing Security Headers** | CSP, HSTS, X-Frame-Options, and other protective headers absent from responses | Yes | Both | +| **CORS Misconfiguration** | Overly permissive cross-origin resource sharing allowing untrusted origins | Yes | Both | +| **Race Conditions / TOCTOU** | Time-of-check to time-of-use vulnerabilities in file and resource access | Yes | Triage | +| **Improper Input Validation** | Missing or insufficient validation of input data before processing | Yes | Both | +| **Integer Overflow / Underflow** | Arithmetic boundary condition errors leading to unexpected behavior | Yes | Both | + +## Secrets Detection + +Pixee primarily triages secrets findings — detecting hardcoded credentials, API keys, tokens, and cloud provider secrets in source code. Automated fixes are available for common patterns where a safe remediation is unambiguous. + +| Category | Examples | +| ------------------------------- | ------------------------------------------------------------ | +| **API Keys & Tokens** | Hardcoded API keys, OAuth tokens, service account keys | +| **Credentials in Code** | Hardcoded passwords, database connection strings | +| **Cloud Provider Secrets** | AWS access keys, GCP service account JSON, Azure credentials | +| **Private Keys & Certificates** | RSA/EC private keys, TLS certificates committed to repos | + +## Custom Rules + +Pixee's triage engine handles custom scanner rules — including custom Semgrep rules, custom CodeQL queries, and internal rule sets — through its adaptive analysis tier. Custom rules don't require Pixee configuration; the engine generates triage logic for novel rule types automatically. + +## Fix Modes Explained + +**Deterministic** — A pre-built codemod applies a rule-based transformation. Same input always produces the same output. Zero LLM involvement. Fastest fix path and most predictable output. + +**AI** — An AI-powered fix is generated for patterns where deterministic rules do not reach — custom framework wrappers, multi-file dataflows, context-dependent sanitization, or novel vulnerability patterns. Every AI-generated fix passes through an independent quality evaluation before delivery. + +**Both** — A deterministic codemod handles well-understood patterns (standard libraries, known frameworks), while AI handles custom or complex variants. Routing is automatic. + +Fix mode and coverage depth vary by language and scanner. For supported languages and IaC formats, see [Language Support](/languages/overview). For per-scanner setup, see [Integrations](/integrations/overview). diff --git a/docs/running_on_public_github_repos.md b/docs/running_on_public_github_repos.md deleted file mode 100644 index 52eac565..00000000 --- a/docs/running_on_public_github_repos.md +++ /dev/null @@ -1,49 +0,0 @@ ---- -sidebar_position: 2 ---- - -# For public repositories without tools - -This page describes how to help set up Pixee on a public GitHub repository that doesn't have any tools configured yet. Note that some features are only available in our enterprise offering. - -## Step 1: Choose and set up your repository - -On the repository you want to secure, enable GitHub _Issues_ so you can see the Pixee dashboard. You can always disable this later if, after you review, you prefer using our dashboard. - -1. In your repository, go to `Settings` > `General`. -2. Under the `Features`, select `Issues`. - -## Step 2: Choose CodeQL or SonarQube Cloud - -For ease of integration, we suggest picking either CodeQL (through GitHub Advanced Security) or SonarQube Cloud. Both can be used to find vulnerabilities in your code, are free for public repositories, and offer simple onboarding. CodeQL is more focused on security than quality, but Sonar has a large rule based and is trusted by developers all over the world. Both are great choices. - -### SonarQube Cloud - -[Follow these instructions](https://docs.sonarsource.com/sonarqube-cloud/getting-started/github/) for installing SonarQube Cloud (to make things easier, login with your GitHub identity). - -### CodeQL through GitHub Advanced Security (GHAS) - -1. In your repository, go to `Settings` > `Code Security`. -2. Under the `Tools` > `CodeQL analysis`, hit `Set up`, then `Default`. - -You may want to wait until the first scan finishes before moving onto the next step. You can see when it finishes by going to `Actions` and watching the progress of the recently-run CodeQL job. - -## Step 3: Install Pixeebot - -With the tool properly configured, the next step is to install Pixee. - -1. Go to our [GitHub App page](https://github.com/apps/pixeebot/). -2. Click `Install` (or `Configure`) and follow the prompts from GitHub. You'll be directed to your Pixee dashboard once the installation process is complete. - -## Step 4: See fixes available - -1. Wait a few minutes for Pixee to process the results associated with the default branch. -2. There should be a new issue that shows which fixes are currently available. - -import IssueDashboard from '/img/issue-dashboard.png'; - -Issue dashboard - -You can use this dashboard to see what fixes are available, coming soon or summon Pixee to issue the fixes. - -> Note: This GitHub-led experience will only show output from our AutoTriage AI agent when you make PRs that have security issues. To take advantage of this feature at scale, [contact us](https://pixee.ai/demo-landing-page)! diff --git a/docs/supported-scms.md b/docs/supported-scms.md deleted file mode 100644 index d032e495..00000000 --- a/docs/supported-scms.md +++ /dev/null @@ -1,49 +0,0 @@ ---- -title: "Supported SCMs" -sidebar_position: 1.5 ---- - -# Supported SCMs - -
- - - - - - - - - - - - - -
GitHubGitLabAzure DevOpsBitbucket
GitHubGitLabAzure DevOpsBitbucket
-
- -
- -
- Pixee integrates with the following Source Control Management (SCM) platforms: -
- -### GitHub - -Fully supported for PR improvements, automated triage, and automated fixes in both public and private repositories. - -### GitLab - -Fully supported for PR improvements, automated triage, and automated fixes in both public and private repositories. - -### Azure DevOps - -Fully supported for PR improvements, automated triage, and automated fixes in both public and private repositories. - -### Bitbucket - -Fully supported for PR improvements, automated triage, and automated fixes in both public and private repositories. - -## Don't See Your Platform? - -Reach out to us at [hi@pixee.ai](mailto:support@pixeebot.com) to discuss support for additional SCM platforms. diff --git a/docs/using-pixeebot.md b/docs/using-pixeebot.md deleted file mode 100644 index 7ea9dcfe..00000000 --- a/docs/using-pixeebot.md +++ /dev/null @@ -1,51 +0,0 @@ ---- -sidebar_position: 6 ---- - -# User guide - -## Continuous improvement - -After installing Pixee and connecting it to your code scanning services, Pixee will begin opening pull requests against your repositories. There is no need to summon Pixee manually - all of your improvements will come automatically at a manageable weekly cadence. - -## Summoning Pixee - -If you have merged all your Pixee pull requests and you're eager to see more recommendations, you can summon Pixee manually. Simply reply to a pull request or open an issue with the following command: - -`@pixeebot next` - -This will let Pixee know it should immediately open a new pull request with additional improvements for this repository. - -### Summon via an issue - -GitHub users can also open an issue with the summon command in the issue body: - -![Summon from issue](/img/summon1.png) - -Within a couple of minutes, Pixee will open a new pull request with additional improvements for your repository: - -![Summon from issue](/img/summon3.png) - -## Pull request reminders - -If a Pixee pull request remains open, two automatic reminders will occur over time in the form of comments on the pull request. - -If the pull request is still not merged or closed after two weeks, Pixee will close it automatically with a final comment. - -If a closed pull request indicates additional recommendations are available, Pixee can still be summoned after the pull request has been reopened. - -## Pixee status - -When a pull request is opened, Pixee will initiate its run, and you can monitor progress in the status checks section of your pull request. - -If Pixee does not have any recommendations, it will mark the check as Successful. If recommendations are found, a separate pull request will be generated, and the check will be marked as Neutral. Review the check details to access the new pull request link and additional information regarding the recommendations. If you merge the new pull request, the original check will register this and be updated to Successful. - -> Note: Pixee will only run when the pull request is first opened. If subsequent commits are introduced, Pixee will not initiate another run and the check will disappear, as progress is linked to the initial commit. - -![checks in progress](/img/checks_in_progress.png) - -## Pixee activity - -The Activity dashboard exists as a GitHub Issue and offers a holistic perspective on Pixee's functionality within your repository. Through this interface, you can conveniently monitor your open pull requests, other available recommendations, and more. The dashboard is automatically enabled upon installation, provided that GitHub Issues are also enabled for your repository. - -The issue can remain open, and the data will automatically refresh with each Pixee analysis that occurs. If the issue is closed, the feature will be disabled and the data will become stale. Reopening it will reactivate the dashboard, and resume auto-updates when Pixee runs. diff --git a/docusaurus.config.js b/docusaurus.config.js index 3f138097..689ea20b 100644 --- a/docusaurus.config.js +++ b/docusaurus.config.js @@ -70,27 +70,141 @@ const config = { "@docusaurus/plugin-client-redirects", { redirects: [ + // Old top-level pages → new IA + { from: "/intro", to: "/" }, + { from: "/installing", to: "/" }, + { from: "/faqs", to: "/faq/general" }, + { from: "/languages", to: "/languages/overview" }, + { from: "/open-pixee", to: "/open-source/codemodder" }, + { from: "/open-source/overview", to: "/open-source/codemodder" }, + { from: "/open-source/contributing", to: "/open-source/codemodder" }, { - to: "/code-scanning-tools/overview", - from: "/integrations", + from: "/running_on_public_github_repos", + to: "/getting-started/source-control", }, + { from: "/supported-scms", to: "/getting-started/source-control" }, + { from: "/using-pixeebot", to: "/getting-started/source-control" }, + { from: "/getting-started", to: "/" }, + { + from: "/configuration/scheduling", + to: "/configuration/operations", + }, + { from: "/api/codetf", to: "/api/overview" }, + + // Old code-scanning-tools/* → new integrations/scanners/* + { + from: "/code-scanning-tools/overview", + to: "/integrations/overview", + }, + { + from: "/code-scanning-tools/codeql", + to: "/integrations/scanners/codeql", + }, + { + from: "/code-scanning-tools/contrast", + to: "/integrations/scanners/contrast", + }, + { + from: "/code-scanning-tools/semgrep", + to: "/integrations/scanners/semgrep", + }, + { + from: "/code-scanning-tools/snyk", + to: "/integrations/scanners/snyk-code", + }, + { + from: "/code-scanning-tools/sonar", + to: "/integrations/scanners/sonarqube", + }, + { + from: "/code-scanning-tools/sonarqube", + to: "/integrations/scanners/sonarqube", + }, + + // Pre-existing /integrations/* aliases → updated to new IA + { from: "/integrations", to: "/integrations/overview" }, { - to: "/code-scanning-tools/sonar", from: "/integrations/sonar", + to: "/integrations/scanners/sonarqube", }, + + // Flat /integrations/ URLs from the prior PR → new SCM/scanner subfolders { - to: "/code-scanning-tools/codeql", from: "/integrations/codeql", + to: "/integrations/scanners/codeql", }, { - to: "/code-scanning-tools/semgrep", from: "/integrations/semgrep", + to: "/integrations/scanners/semgrep", + }, + { + from: "/integrations/snyk-code", + to: "/integrations/scanners/snyk-code", + }, + { + from: "/integrations/sonarqube", + to: "/integrations/scanners/sonarqube", }, + { + from: "/integrations/veracode", + to: "/integrations/scanners/veracode", + }, + { + from: "/integrations/checkmarx", + to: "/integrations/scanners/checkmarx", + }, + { + from: "/integrations/appscan", + to: "/integrations/scanners/appscan", + }, + { + from: "/integrations/contrast", + to: "/integrations/scanners/contrast", + }, + { + from: "/integrations/gitlab-sast", + to: "/integrations/scanners/gitlab-sast", + }, + { from: "/integrations/github", to: "/integrations/scms/github" }, - // You can add more redirects here as needed + // Removed consolidated wrappers → overview + { + from: "/integrations/commercial-scanners", + to: "/integrations/overview", + }, + { + from: "/integrations/oss-aggregator-scanners", + to: "/integrations/overview", + }, + { + from: "/integrations/scm-platforms", + to: "/integrations/overview", + }, ], }, ], + "docusaurus-plugin-llms", + ], + + headTags: [ + { + tagName: "script", + attributes: { type: "application/ld+json" }, + innerHTML: JSON.stringify({ + "@context": "https://schema.org", + "@type": "Organization", + name: "Pixee", + url: "https://pixee.ai", + logo: "https://pixee.ai/images/pixee-logo.png", + sameAs: [ + "https://github.com/pixee", + "https://www.linkedin.com/company/pixee/", + "https://twitter.com/pixaboratory", + ], + description: + "Pixee automates security vulnerability triage and remediation at scale.", + }), + }, ], themeConfig: diff --git a/migration/ASSESSMENT.md b/migration/ASSESSMENT.md new file mode 100644 index 00000000..f35154f0 --- /dev/null +++ b/migration/ASSESSMENT.md @@ -0,0 +1,284 @@ +# docs.pixee.ai Migration — Assessment & Plan + +**Date:** 2026-05-05 +**Status:** Migration executed locally on branch `redesign/v2-content` (`pixee/docs`). Three commits ready to push. Build clean, all 72 pages return 200, redirects working. Awaiting push + PR. + +--- + +## 1. The three repos and how they fit together + +| Repo | Role | +| ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------ | +| `pixee-resources/Pixee-Marketing-OS` | Source of the **new** docs content (PR #117, merged 2026-04-28). Lives at `10_execute_short_term/pixee_docs/`. | +| `pixee/docs` | Docusaurus 3.x **source** repo. Currently has ~9 thin pages. Migration PR target. | +| `pixee/internal-docs` | **Deploy target only.** Every commit is `Deploy website - based on `. Serves `docs.pixee.ai` via GitHub Pages. We never edit this directly. | + +**Deploy flow** (`pixee/docs/.github/workflows/deploy.yml`): + +- PR to `pixee/docs#main` → `yarn build` runs as a check (test build only, no deploy). +- Push to `pixee/docs#main` → SSH-deploys via `yarn deploy` to `pixee/internal-docs#main`. That commit is what `docs.pixee.ai` serves. + +`docusaurus.config.js` confirms: `organizationName: "pixee"`, `projectName: "internal-docs"`, `deploymentBranch: "main"`. + +--- + +## 2. What's coming from PR #117 + +Lives at `Pixee-Marketing-OS/10_execute_short_term/pixee_docs/`: + +- **71 markdown pages** in `pages/` across 10 sections: api (5), configuration (7), enterprise (11), faq (3), getting-started (8), how-it-works (6), integrations (14), languages (7), open-source (4), platform (6). + - The handoff spec says 76; on-disk has 71. PR #117 did 13→4 consolidation in some folders. **Treat on-disk as truth.** +- Frontmatter is already Docusaurus-shaped: `title`, `slug`, `track` (`dev` | `leader` | `both`), `content_type`, `seo_title`, `meta_description`. +- Filenames are prefixed with a global ordinal (`01_…65_`). **Drop on copy.** +- No JSX/MDX in body content. Only `<…>` are inside code fences (Maven XML, csproj). Conversion is essentially a copy. + +**Two data-quality issues the migration script must handle:** + +1. **Track field case is inconsistent** — values include `dev`, `DEV`, `both`, `BOTH`, `leader`, `LEADER`, plus one stray `[leader, …]` array. Normalize to lowercase string. +2. **29 of 71 pages have duplicated frontmatter keys** (e.g., `title:` and `slug:` listed twice). Dedup, keeping the last occurrence (YAML parsers vary; Docusaurus accepts the last). + +Companion artifacts in `pixee_docs/`: + +- `site_architecture.md` — IA, sidebar mockup, URL structure +- `HANDOFF_SPEC.md` — implementation checklist +- `content_briefs/` — 76 per-page SEO briefs (we may extract some metadata from these later; not in v1 scope) +- `technical/` — `llms.txt`, `schema_specs.md`, `cross_domain_linking.md`, `entity_consistency.md` +- `gated_content/`, `quality_reviews/`, `extracts/`, `research_*` — out of scope for the docs migration. + +--- + +## 3. What's there today (`pixee/docs`) + +Total: ~9 pages, 729 lines. Auto-generated sidebar from filesystem. + +``` +docs/ +├── intro.md +├── installing.md +├── faqs.md +├── languages.md +├── open-pixee.md +├── running_on_public_github_repos.md +├── supported-scms.md +├── using-pixeebot.md +└── code-scanning-tools/ + ├── overview.md + ├── codeql.md + ├── contrast.md + ├── semgrep.md + ├── snyk.md + ├── sonar.md + └── sonarqube.md +``` + +Existing redirects in `docusaurus.config.js`: + +- `/integrations` → `/code-scanning-tools/overview` +- `/integrations/sonar` → `/code-scanning-tools/sonar` +- `/integrations/codeql` → `/code-scanning-tools/codeql` +- `/integrations/semgrep` → `/code-scanning-tools/semgrep` + +These flip direction in v1: the new IA _is_ `/integrations/*`. + +--- + +## 4. Decisions + +| # | Decision | Rationale | +| --- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------ | +| 1 | **Drop numeric filename prefixes.** Inject `sidebar_position` from prefix into frontmatter (renumbered dense per folder). | Filenames are messy; ordering belongs in frontmatter. | +| 2 | **Autogen sidebar.** No hand-built sidebar, no swizzle. | User preference. | +| 3 | **No track badges in the sidebar.** Originally we agreed to put `[DEV]/[LEADER]/[BOTH]` badges in `_category_.json` labels. Reverted after seeing it rendered — the badges read as visual noise. The `track:` field stays in frontmatter for potential v2 use (in-page audience pill). | Cleaner sidebar; no information lost since users can still see context per page. | +| 4 | **Skip the in-page "for: Developers" badge.** | Avoids swizzling theme components. | +| 5 | **Flatten Integrations** — drop the spec's `── Deep Integrations ── / ── Scanner Integrations ── / ── Platforms ──` sub-headers. All 14 integrations sit at the same level under `/integrations/`. | Sub-headers would require either a hand-built sidebar or splitting into subfolders (which would change URLs). Flat is cleaner. | +| 6 | **Skip React components for v1.** No ``, no ``, no ``. Defer to v2. | Trim scope. | +| 7 | **Include all config-file-level SEO improvements in v1.** See §6. | "Free" wins via headTags + static files + plugins. | +| 8 | **Redirect every old URL** to its closest new equivalent. Preserve SEO regardless of traffic ranking. | With only 9 old pages, the redirect table is trivial; cost of being thorough is negligible. | +| 9 | **Create `/integrations/contrast`** as part of the migration (the new IA needs a Contrast page; PR #117 didn't include one). Drafted from the existing 4-line `contrast.md` + public Contrast Security docs, matching the new docs voice (neutral, no marketing). David reviews before merge. | Contrast must exist in the new IA. | +| 10 | **One big PR** on `pixee/docs`, branch `redesign/v2-content`. Iterate locally. | User preference. | +| 11 | **Replace the React landing page with the welcome doc at `/`.** Deleted `src/pages/index.js` + `src/components/HomepageFeatures/`. Set `slug: /` on the welcome page so `docs.pixee.ai/` IS the welcome content (matches the spec). | Two competing landings (React hero + welcome doc) was confusing; the spec puts welcome at root. | + +--- + +## 5. Redirect table + +All old URLs → new equivalents. Implemented via `@docusaurus/plugin-client-redirects` (already installed). + +| Old URL | New URL | Notes | +| --------------------------------- | ----------------------------- | -------------------------------------------------------------- | +| `/intro` | `/` | Welcome doc lives at root. | +| `/installing` | `/` | Welcome page has platform tiles. | +| `/faqs` | `/faq/general` | New IA splits FAQ into general / enterprise / troubleshooting. | +| `/languages` | `/languages/overview` | | +| `/open-pixee` | `/open-source/overview` | | +| `/running_on_public_github_repos` | `/configuration/repositories` | Verify on review — fallback `/getting-started/github`. | +| `/supported-scms` | `/` | Welcome page lists all platforms with setup links. | +| `/using-pixeebot` | `/getting-started/github` | Pixeebot is the GitHub bot. | +| `/getting-started` | `/` | Welcome page promoted to root after Decision #11. | +| `/code-scanning-tools/overview` | `/integrations/overview` | | +| `/code-scanning-tools/codeql` | `/integrations/codeql` | | +| `/code-scanning-tools/contrast` | `/integrations/contrast` | New page authored as part of this PR. | +| `/code-scanning-tools/semgrep` | `/integrations/semgrep` | | +| `/code-scanning-tools/snyk` | `/integrations/snyk-code` | | +| `/code-scanning-tools/sonar` | `/integrations/sonarqube` | Old IA had both `sonar` and `sonarqube` — collapsing. | +| `/code-scanning-tools/sonarqube` | `/integrations/sonarqube` | | +| `/integrations` | `/integrations/overview` | Was `→ /code-scanning-tools/overview`; flipped. | +| `/integrations/sonar` | `/integrations/sonarqube` | Was `→ /code-scanning-tools/sonar`; updated. | + +Total: 18 redirect rules. The pre-existing 4 redirects in `docusaurus.config.js` are repointed; everything else is net-new. + +--- + +## 6. SEO additions in v1 (config-file-only) — DONE + +All cheap, all React-free, all unblock AI crawlers and search engines. ~50 lines of config + 2 small static files. All five items below shipped. + +| Item | Where | Why | +| --------------------------------------------- | ----------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- | +| **Site-wide Organization JSON-LD** ✓ | `docusaurus.config.js` → `headTags` | Standard Org schema for Google AI Overviews / Bing Copilot. | +| **`llms.txt` + `llms-full.txt`** ✓ | `docusaurus-plugin-llms@^0.4.0` | Lets Claude / ChatGPT / Perplexity index the site cleanly. The handoff spec specifically calls this out. | +| **`robots.txt` allow-list for AI crawlers** ✓ | `static/robots.txt` | Explicit allow for `GPTBot`, `ClaudeBot`, `PerplexityBot`, `Google-Extended`, etc. | +| **Sitemap** ✓ | Default in `@docusaurus/preset-classic`. Verified on new tree. | Free. | +| **Canonical URLs** ✓ | Default Docusaurus behavior. `url` + `baseUrl` confirmed correct. | Free. | + +**Explicitly deferred to v2 (require components):** + +- Per-page `FAQPage` JSON-LD (the spec's claimed 3.2x AI-Overview lift) → needs `` component +- Per-page `HowTo` JSON-LD on setup pages → needs `` component +- `` to raw `.md` → needs swizzle +- `` in-page rendering → needs swizzle +- `` thumbs-up/down → needs component + analytics endpoint +- Algolia DocSearch → defer; default search works +- HubSpot lead capture / gated content forms → out of scope for docs (marketing assets) + +--- + +## 7. Migration plan — EXECUTED + +**Branch:** `redesign/v2-content` on `pixee/docs`. Three commits ready to push: + +``` +f4a18e4 sidebar: drop track badges from category labels +7d97768 redesign: replace React landing with welcome page at root +4e3a5d5 redesign: replace docs with new IA from Pixee-Marketing-OS PR #117 +``` + +PRs only run `yarn build` — no deploy until merge — so iteration is safe. + +Phases below describe what was done. + +### Phase A — Prep ✓ + +1. Branched off `pixee/docs#main`. +2. Deleted the existing `docs/*.md` and `docs/code-scanning-tools/`. + +### Phase B — Content port ✓ + +A migration script (`migrate.py` at docswork root, ~150 lines, idempotent) walked `Pixee-Marketing-OS/10_execute_short_term/pixee_docs/pages/
/` and, for each `NN_.md`: + +1. Reads frontmatter + body. +2. **Strips numeric prefix** from filename → `.md`. +3. **Dedups frontmatter keys** (last wins). +4. **Normalizes `track:`** to lowercase string (`dev` | `leader` | `both`). +5. **Injects `sidebar_position: `** where `` is the dense rank (1, 2, 3…) of the original prefix within the folder. +6. **Removes** non-Docusaurus frontmatter fields the spec carries that we don't use (`content_type`, `seo_title`, `meta_description` stay; we'll reuse them in v2 for schema). +7. Writes to `pixee/docs/docs/
/.md`. + +For each section folder, the script writes a `_category_.json`: + +```json +{ + "label": "Getting Started", + "position": 1, + "link": { "type": "doc", "id": "" } +} +``` + +Section order and labels (track badges initially included, then dropped per Decision #3): + +| # | Folder | Label | +| --- | ------------------ | ------------------- | +| 1 | `getting-started/` | `Getting Started` | +| 2 | `platform/` | `Platform Overview` | +| 3 | `how-it-works/` | `How It Works` | +| 4 | `integrations/` | `Integrations` | +| 5 | `configuration/` | `Configuration` | +| 6 | `enterprise/` | `Enterprise` | +| 7 | `languages/` | `Language Support` | +| 8 | `api/` | `API & Reference` | +| 9 | `open-source/` | `Open Source` | +| 10 | `faq/` | `FAQ` | + +### Phase C — Author the new Contrast page ✓ + +Drafted `docs/integrations/contrast.md` modeled on the new CodeQL/Semgrep page pattern (intro, "What Contrast Detects", "How Pixee Enhances Contrast" with Triage + Remediation, Setup, Common False Positive Patterns, FAQ). Source: existing 4-line `contrast.md` + public Contrast Security docs. Flagged in PR for David's review. + +### Phase D — Config changes (`docusaurus.config.js`) ✓ + +1. Replaced the existing `redirects` array with the 18-entry table from §5. +2. Added Organization JSON-LD to `headTags`. +3. `yarn add docusaurus-plugin-llms@^0.4.0`, registered in `plugins[]` with default config. +4. Added `static/robots.txt` with AI-crawler allow-list. +5. Left navbar, footer, sitemap, GA / GTM as-is. + +### Phase E — Build & link sanity ✓ + +1. Ran `yarn install` (picked up the new plugin). +2. Ran `yarn build` — surfaced 15 broken-link patterns (consolidated pages, IA renames, one missing `/demo` cross-domain link). Fixed via `fixup_links.py` (idempotent regex pass at docswork root) plus one manual edit. Re-built clean: 72 docs, zero broken links. +3. Ran `yarn serve` and curl-probed all 72 page slugs (all 200), all 10 category landings, JSON-LD on homepage, redirect targets, and sidebar order. + +### Phase F — Homepage cleanup ✓ + +After initial verification, decided the React landing at `/` was redundant with the new welcome doc. Deleted `src/pages/index.js`, `src/pages/index.module.css`, `src/components/HomepageFeatures/`. Set `slug: /` on the welcome doc. Updated 5 internal `[](/getting-started)` references → `[](/)`. Added `/getting-started → /` redirect. Updated the three redirects that were targeting `/getting-started` (intro, installing, supported-scms) to target `/` instead. + +### Phase G — Sidebar polish ✓ + +Initial implementation included `[DEV]`/`[LEADER]`/`[BOTH]` track badges in category labels per the original spec. After eyeballing in dev preview, reverted — labels now read as plain section names. The `track:` field is still present in page frontmatter for v2 use (in-page audience pill via swizzle). + +### Phase H — Push + PR (next) + +1. Push `redesign/v2-content` to `pixee/docs`. **(David runs locally; SSH agent.)** +2. Open PR. CI runs `yarn build` test only (no deploy). +3. Iterate via force-push as review feedback comes in. +4. Merge when ready → SSH deploy to `pixee/internal-docs` → live on `docs.pixee.ai`. + +--- + +## 8. Risks / how each one resolved + +1. **`onBrokenLinks: "throw"`** — landed: 15 broken-link patterns surfaced on first build, fixed via `fixup_links.py` (27 substitutions across 9 files) + one manual `/demo` → `pixee.ai/demo` edit. ✓ +2. **Slug field consistency.** Every migrated page had an explicit `slug:` in frontmatter; all 72 slugs return 200. ✓ +3. **Images / static assets.** No image references in the migrated body content. ✓ +4. **Existing redirects flip direction.** Done — pre-existing 4 `/integrations/* → /code-scanning-tools/*` rules replaced. ✓ +5. **Old integrations not in new IA.** Contrast handled (Decision #9). No other gaps identified. ✓ +6. **Page count.** 71 (not the spec's 76). ✓ — reflected in commit message. + +--- + +## 9. Out of scope for v1 (tracked for v2) + +- React components: ``, ``, `` +- Per-page JSON-LD (FAQPage, HowTo, TechArticle, SoftwareApplication) +- Raw markdown alternates for AI agents (`.md` URL routes + ``) +- Algolia DocSearch +- HubSpot lead capture, gated PDF downloads (the spec's 4 gated assets) +- GA4 custom events (scroll depth, code copy, CTA clicks) +- Cross-domain canonical / pixee.ai linking strategy from `cross_domain_linking.md` + +--- + +## 10. Open items requiring human input before merge + +- Verify `/configuration/repositories` is the right target for the `/running_on_public_github_repos` redirect. (Read the new page first; fall back to `/getting-started/github` if not the right fit.) +- David reviews the new `/integrations/contrast` page before merge. +- David eyeballs the deployed dev preview from the PR (or `yarn start` locally) and signals if anything reads off — sidebar order, integrations flat list, homepage content, redirects. + +## 11. Tooling archived alongside this doc + +This file lives at `migration/ASSESSMENT.md` in the `pixee/docs` repo, alongside: + +- `migrate.py` — content port script that ran during the initial migration +- `fixup_links.py` — link-fixup pass that ran after `migrate.py` +- `README.md` — short orientation for anyone reading these files later + +All three are checked in for historical reference. **Do not re-run them** — `migrate.py` would wipe manually-authored pages (e.g., `docs/integrations/contrast.md`) and ignore in-repo edits made after the migration commit (e.g., `slug: /` on the welcome doc). The scripts assumed a working tree containing both `Pixee-Marketing-OS/` and `docs/` as siblings; that layout no longer exists. diff --git a/migration/README.md b/migration/README.md new file mode 100644 index 00000000..d77a2973 --- /dev/null +++ b/migration/README.md @@ -0,0 +1,31 @@ +# Migration archive + +These files document the 2026-05-05 docs redesign — replacing the previous ~9-page site with the 71-page IA from `Pixee-Marketing-OS` PR #117. + +## Contents + +| File | What it is | +| ----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `ASSESSMENT.md` | The planning + decision-log document. Captures the three-repo deploy flow, decisions made, redirect table, SEO additions, and what was actually executed. | +| `migrate.py` | One-shot Python script that ported content from `Pixee-Marketing-OS/10_execute_short_term/pixee_docs/pages/` into `docs/docs/`. Normalized frontmatter, dropped numeric prefixes, generated `_category_.json` files. | +| `fixup_links.py` | One-shot Python script that fixed 27 internal markdown links across 9 files (consolidated/renamed pages, IA renames). | +| `integrations_restructure.py` | Follow-up restructure that split flat `/integrations/` into `/integrations/scms/` and `/integrations/scanners/`. Captures the moves, frontmatter updates, body-link fixup, and wrapper-file deletions. | + +## Do not re-run the scripts + +These are committed for historical reference, not as a re-runnable pipeline. + +- `migrate.py` is destructive: it wipes `docs/docs/` and rewrites everything from `Pixee-Marketing-OS/`. Re-running it would delete `docs/integrations/contrast.md` (manually authored) and revert the welcome doc's `slug: /` (set after migration). +- The scripts also assume a sibling working-tree layout (`Pixee-Marketing-OS/` next to `docs/`) that no longer exists. +- For future content updates, edit `docs/` directly. `Pixee-Marketing-OS` is no longer the source of truth for these docs. + +## Why keep them + +Future-you (or future-someone) will eventually ask: + +- _Why is the file numbering weird?_ — Because `pages/` files used `NN_.md` for global ordering; we kept the order in `sidebar_position` instead. +- _Why is there a Contrast page that doesn't match the format of the others?_ — Because PR #117 dropped Contrast from the IA; we re-added it. +- _Why does the redirect table have so many rules?_ — The old `/code-scanning-tools/*` IA was inverted to `/integrations/*`. +- _Why is `track:` in frontmatter if nothing renders it?_ — Reserved for a v2 audience-badge component. + +`ASSESSMENT.md` answers all of those. diff --git a/migration/fixup_links.py b/migration/fixup_links.py new file mode 100644 index 00000000..3cfa2b18 --- /dev/null +++ b/migration/fixup_links.py @@ -0,0 +1,74 @@ +#!/usr/bin/env python3 +""" +Fix internal links in the migrated docs that reference pages consolidated/renamed +in PR #117 but still appear in body content. + +ARCHIVED — committed for historical reference. NOT INTENDED TO BE RE-RUN. +Re-running is safe (regex no-ops if patterns already replaced), but the link +shape has since drifted (e.g., /getting-started → /). See README.md. + +Originally placed at /fixup_links.py alongside migrate.py and run after it. +Idempotent: each rule is a regex that becomes a no-op once applied. +""" + +import pathlib +import re + +DOCS = pathlib.Path(__file__).parent / "docs/docs" + +# Each rule is a (regex, replacement). Patterns target markdown link bodies +# `](URL)` and `](URL#anchor)` to avoid matching the same path elsewhere. +# Order matters: prefix-matched rules must come before their parent prefixes. +RULES = [ + # Configuration: notifications + reporting were folded into operations.md + (r"\]\(/configuration/notifications(?=[)#])", "](/configuration/operations"), + (r"\]\(/configuration/reporting(?=[)#])", "](/configuration/operations"), + + # Integrations: individual scanner pages folded into bundles + (r"\]\(/integrations/defectdojo(?=[)#])", "](/integrations/oss-aggregator-scanners"), + (r"\]\(/integrations/trivy(?=[)#])", "](/integrations/oss-aggregator-scanners"), + (r"\]\(/integrations/fortify(?=[)#])", "](/integrations/commercial-scanners"), + (r"\]\(/integrations/polaris(?=[)#])", "](/integrations/commercial-scanners"), + + # SCM platforms: gitlab/azure/bitbucket folded into scm-platforms + (r"\]\(/integrations/azure-devops(?=[)#])", "](/integrations/scm-platforms"), + (r"\]\(/integrations/bitbucket(?=[)#])", "](/integrations/scm-platforms"), + (r"\]\(/integrations/gitlab(?=[)#])", "](/integrations/scm-platforms"), + + # SARIF naming + (r"\]\(/integrations/sarif(?=[)#])", "](/integrations/sarif-universal"), + (r"\]\(/integrations/universal-sarif(?=[)#])", "](/integrations/sarif-universal"), + + # Section overview links that dropped the /overview suffix + (r"\]\(/integrations(?=[)#])", "](/integrations/overview"), + (r"\]\(/languages(?=[)#])", "](/languages/overview"), + + # Typos / wrong sections + (r"\]\(/enterprise/deployment-options(?=[)#])", "](/enterprise/deployment"), + (r"\]\(/getting-started/phased-rollout(?=[)#])", "](/enterprise/phased-rollout"), +] + +COMPILED = [(re.compile(p), r) for p, r in RULES] + + +def main(): + total_changes = 0 + files_changed = 0 + for md in DOCS.rglob("*.md"): + text = md.read_text(encoding="utf-8") + original = text + file_changes = 0 + for pat, rep in COMPILED: + new_text, n = pat.subn(rep, text) + file_changes += n + text = new_text + if text != original: + md.write_text(text, encoding="utf-8") + total_changes += file_changes + files_changed += 1 + print(f" {md.relative_to(DOCS)}: {file_changes} fix(es)") + print(f"\n{total_changes} link fix(es) across {files_changed} file(s)") + + +if __name__ == "__main__": + main() diff --git a/migration/integrations_restructure.py b/migration/integrations_restructure.py new file mode 100644 index 00000000..7ed12798 --- /dev/null +++ b/migration/integrations_restructure.py @@ -0,0 +1,184 @@ +#!/usr/bin/env python3 +""" +Restructure the integrations section from a flat layout into two subcategories: + /integrations/scms/ (GitHub, GitLab, Azure DevOps, Bitbucket) + /integrations/scanners/ (CodeQL, Semgrep, Snyk Code, ... 14 total) + +ARCHIVED — committed for historical reference. NOT INTENDED TO BE RE-RUN. +This script captures the mechanical operations performed during the 2026-05-05 +restructure. The new content authored alongside it (gitlab.md, azure-devops.md, +bitbucket.md, polaris.md, fortify.md, trivy.md, defectdojo.md, gitlab-sca.md) +was written by hand, not generated here. + +Re-running would fail anyway: the source paths it expects (the old flat layout +with consolidated wrapper pages) no longer exist. + +Working tree assumed at execution time: + docs/ (the pixee/docs repo root) + └── docs/integrations/ + ├── codeql.md, semgrep.md, ... (flat scanner pages) + ├── github-platform.md (flat SCM page) + ├── commercial-scanners.md (consolidated wrapper, deleted) + ├── oss-aggregator-scanners.md (consolidated wrapper, deleted) + ├── scm-platform-reference.md (consolidated wrapper, deleted) + ├── integrations-overview.md + └── sarif-universal.md + +The script was placed at /docs/migration/integrations_restructure.py and +run with `python3 migration/integrations_restructure.py`. It performed: + + 1. mkdir docs/integrations/{scms,scanners}/ + 2. git mv github-platform.md -> scms/github.md + 3. git mv 9 scanner pages -> scanners/.md + 4. Update slugs to /integrations/scms/ and /integrations/scanners/ + 5. Update sidebar_position values (alphabetical within each subcategory) + 6. Rename github page title from "GitHub Platform Integration" to "GitHub Integration" + 7. Body-content link fixup: rewrite /integrations/ references to point at + the new /integrations/scanners/ or /integrations/scms/ paths + 8. Delete the three consolidated wrappers (their content was extracted into + individual scanner pages by hand) + +Idempotent within its assumed layout. Each step is safe to re-run; the regex +substitutions are no-ops once applied. +""" + +import pathlib +import re +import shutil +import subprocess + +REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent +INTEGRATIONS = REPO_ROOT / "docs/integrations" + +# (filename to move from flat layout, target subdir, new slug, sidebar_position, optional title rewrite) +SCANNER_MOVES = [ + ("appscan.md", "scanners", "/integrations/scanners/appscan", 1, None), + ("checkmarx.md", "scanners", "/integrations/scanners/checkmarx", 2, None), + ("codeql.md", "scanners", "/integrations/scanners/codeql", 3, None), + ("contrast.md", "scanners", "/integrations/scanners/contrast", 4, None), + # defectdojo, fortify, polaris, trivy, gitlab-sca authored fresh (positions 5, 6, 9, 14, 8) + ("gitlab-sast.md", "scanners", "/integrations/scanners/gitlab-sast", 7, None), + ("semgrep.md", "scanners", "/integrations/scanners/semgrep", 11, None), + ("snyk-code.md", "scanners", "/integrations/scanners/snyk-code", 12, None), + ("sonarqube.md", "scanners", "/integrations/scanners/sonarqube", 13, None), + ("veracode.md", "scanners", "/integrations/scanners/veracode", 15, None), +] + +SCM_MOVES = [ + ("github-platform.md", "scms", "/integrations/scms/github", 3, "GitHub Integration"), +] +SCM_RENAMES = {"github-platform.md": "github.md"} # rename on move + +LINK_RULES = [ + # Removed wrappers → overview + (r"\]\(/integrations/commercial-scanners(?=[)#])", "](/integrations/overview"), + (r"\]\(/integrations/oss-aggregator-scanners(?=[)#])", "](/integrations/overview"), + (r"\]\(/integrations/scm-platforms(?=[)#])", "](/integrations/overview"), + # Flat scanner URLs → /scanners/ subfolder + (r"\]\(/integrations/codeql(?=[)#])", "](/integrations/scanners/codeql"), + (r"\]\(/integrations/semgrep(?=[)#])", "](/integrations/scanners/semgrep"), + (r"\]\(/integrations/snyk-code(?=[)#])", "](/integrations/scanners/snyk-code"), + (r"\]\(/integrations/sonarqube(?=[)#])", "](/integrations/scanners/sonarqube"), + (r"\]\(/integrations/veracode(?=[)#])", "](/integrations/scanners/veracode"), + (r"\]\(/integrations/checkmarx(?=[)#])", "](/integrations/scanners/checkmarx"), + (r"\]\(/integrations/appscan(?=[)#])", "](/integrations/scanners/appscan"), + (r"\]\(/integrations/contrast(?=[)#])", "](/integrations/scanners/contrast"), + (r"\]\(/integrations/gitlab-sast(?=[)#])", "](/integrations/scanners/gitlab-sast"), + # Flat SCM URL → /scms/ subfolder + (r"\]\(/integrations/github(?=[)#])", "](/integrations/scms/github"), +] + +WRAPPER_FILES = [ + "commercial-scanners.md", + "oss-aggregator-scanners.md", + "scm-platform-reference.md", +] + + +def update_frontmatter(md_path: pathlib.Path, slug: str, position: int, new_title: str | None): + text = md_path.read_text(encoding="utf-8") + text = re.sub(r"^slug: .*$", f"slug: {slug}", text, count=1, flags=re.M) + text = re.sub(r"^sidebar_position: .*$", f"sidebar_position: {position}", text, count=1, flags=re.M) + if new_title: + text = re.sub(r"^title: .*$", f"title: {new_title}", text, count=1, flags=re.M) + text = re.sub(r"^# .*$", f"# {new_title}", text, count=1, flags=re.M) + md_path.write_text(text, encoding="utf-8") + + +def move_files(): + (INTEGRATIONS / "scms").mkdir(exist_ok=True) + (INTEGRATIONS / "scanners").mkdir(exist_ok=True) + for filename, subdir, _, _, _ in SCANNER_MOVES + SCM_MOVES: + src = INTEGRATIONS / filename + dest_name = SCM_RENAMES.get(filename, filename) + dest = INTEGRATIONS / subdir / dest_name + if not src.exists(): + print(f" skip (already moved or absent): {filename}") + continue + # Use git mv when possible; fall back to plain rename otherwise. + try: + subprocess.run(["git", "mv", str(src.relative_to(REPO_ROOT)), str(dest.relative_to(REPO_ROOT))], + cwd=REPO_ROOT, check=True, capture_output=True) + except subprocess.CalledProcessError: + shutil.move(str(src), str(dest)) + print(f" moved {filename} -> {subdir}/{dest_name}") + + +def update_all_frontmatter(): + for filename, subdir, slug, position, new_title in SCANNER_MOVES + SCM_MOVES: + dest_name = SCM_RENAMES.get(filename, filename) + dest = INTEGRATIONS / subdir / dest_name + if not dest.exists(): + print(f" skip frontmatter (missing): {dest}") + continue + update_frontmatter(dest, slug, position, new_title) + print(f" frontmatter: {dest.name} slug={slug} pos={position}") + + +def fixup_body_links(): + docs_root = REPO_ROOT / "docs" + compiled = [(re.compile(p), r) for p, r in LINK_RULES] + total_subs = total_files = 0 + for md in docs_root.rglob("*.md"): + text = md.read_text(encoding="utf-8") + new_text = text + file_subs = 0 + for pat, rep in compiled: + new_text, n = pat.subn(rep, new_text) + file_subs += n + if new_text != text: + md.write_text(new_text, encoding="utf-8") + total_subs += file_subs + total_files += 1 + print(f" link fix: {md.relative_to(docs_root)} ({file_subs})") + print(f"\n {total_subs} link substitution(s) across {total_files} file(s)") + + +def remove_wrappers(): + for name in WRAPPER_FILES: + target = INTEGRATIONS / name + if not target.exists(): + print(f" already removed: {name}") + continue + try: + subprocess.run(["git", "rm", str(target.relative_to(REPO_ROOT))], + cwd=REPO_ROOT, check=True, capture_output=True) + except subprocess.CalledProcessError: + target.unlink() + print(f" removed: {name}") + + +def main(): + print("Step 1: move files") + move_files() + print("\nStep 2: update frontmatter") + update_all_frontmatter() + print("\nStep 3: body-content link fixup") + fixup_body_links() + print("\nStep 4: remove consolidated wrappers") + remove_wrappers() + print("\nDone.") + + +if __name__ == "__main__": + main() diff --git a/migration/migrate.py b/migration/migrate.py new file mode 100644 index 00000000..fcb92be9 --- /dev/null +++ b/migration/migrate.py @@ -0,0 +1,191 @@ +#!/usr/bin/env python3 +""" +Migrate PR #117 content from Pixee-Marketing-OS into pixee/docs. + +ARCHIVED — committed for historical reference. NOT INTENDED TO BE RE-RUN. +Re-running would wipe manually-authored pages (e.g., docs/integrations/contrast.md) +and ignore later in-repo edits like the slug change on the welcome doc. See README.md. + +Working tree assumed at execution time: + / + ├── Pixee-Marketing-OS/10_execute_short_term/pixee_docs/pages/
/NN_.md + └── docs/docs/
/.md (target, this repo) + +The script was placed at /migrate.py and run with `python3 migrate.py`. + +Behavior: walks every section, drops numeric filename prefixes, dedups frontmatter +keys (last wins), normalizes `track:` to lowercase, injects sidebar_position, +renames meta_description -> description, writes _category_.json per section. +Idempotent within its assumed layout: always rewrites the target tree from scratch. +""" + +import json +import pathlib +import re +import shutil +import sys + +ROOT = pathlib.Path(__file__).parent.resolve() +SRC = ROOT / "Pixee-Marketing-OS/10_execute_short_term/pixee_docs/pages" +DST = ROOT / "docs/docs" + +# (folder, sidebar label, position, link spec) +# link spec: ("doc", "") | ("generated-index", None) +CATEGORIES = [ + ("getting-started", "Getting Started", 1, ("doc", "getting-started/getting-started")), + ("platform", "Platform Overview", 2, ("doc", "platform/what-is-agentic-security-engineering")), + ("how-it-works", "How It Works", 3, ("generated-index", None)), + ("integrations", "Integrations", 4, ("doc", "integrations/integrations-overview")), + ("configuration", "Configuration", 5, ("doc", "configuration/config-overview")), + ("enterprise", "Enterprise", 6, ("doc", "enterprise/enterprise-overview")), + ("languages", "Language Support", 7, ("doc", "languages/languages-overview")), + ("api", "API & Reference", 8, ("doc", "api/api-overview")), + ("open-source", "Open Source", 9, ("doc", "open-source/oss-overview")), + ("faq", "FAQ", 10, ("doc", "faq/faq-general")), +] + +# Frontmatter fields we keep (and rename if needed). All other unknown keys are kept verbatim. +RENAME = {"meta_description": "description"} + +PREFIX_RE = re.compile(r"^(\d+)_(.+\.md)$") +FM_LINE_RE = re.compile(r"^([A-Za-z_][A-Za-z0-9_]*):\s*(.*)$") + + +def parse_frontmatter(text: str): + """Return (ordered list of (key, value) pairs with last-wins dedup, body).""" + if not text.startswith("---\n") and not text.startswith("---\r\n"): + return [], text + # Locate closing --- + lines = text.splitlines(keepends=True) + end_idx = None + for i in range(1, len(lines)): + if lines[i].rstrip() == "---": + end_idx = i + break + if end_idx is None: + return [], text + fm_lines = lines[1:end_idx] + body = "".join(lines[end_idx + 1:]).lstrip("\n") + + # Build ordered dict with last-wins dedup. + pairs = [] + seen = {} + for raw in fm_lines: + m = FM_LINE_RE.match(raw.rstrip("\n")) + if not m: + # Skip blank/comment lines silently. We don't expect nested YAML structures + # in this content set (verified manually); flag if assumption breaks. + if raw.strip() and not raw.lstrip().startswith("#"): + print(f" WARN: unparseable frontmatter line: {raw!r}", file=sys.stderr) + continue + key, val = m.group(1), m.group(2).strip() + # Strip surrounding quotes (single or double). + if (val.startswith('"') and val.endswith('"')) or (val.startswith("'") and val.endswith("'")): + val = val[1:-1] + if key in seen: + pairs[seen[key]] = (key, val) # last wins + else: + seen[key] = len(pairs) + pairs.append((key, val)) + return pairs, body + + +def normalize_track(val: str) -> str: + """Normalize track values like 'DEV', 'BOTH', '[leader, both]' to a lowercase string.""" + v = val.strip().strip("[]") + # Take first item if comma-separated (e.g., "leader, both") + v = v.split(",")[0].strip().strip("'\"") + return v.lower() + + +def serialize_frontmatter(pairs) -> str: + """Emit a YAML frontmatter block. Quote any value that needs quoting.""" + out = ["---"] + for k, v in pairs: + sv = str(v) + # Quote if value contains YAML-special chars or starts with whitespace. + needs_quote = ( + sv == "" or + any(c in sv for c in [':', '#', '|', '>', '"', "'", '*', '&', '!']) or + sv != sv.strip() + ) + if isinstance(v, int): + out.append(f"{k}: {v}") + elif needs_quote: + out.append(f"{k}: {json.dumps(sv)}") + else: + out.append(f"{k}: {sv}") + out.append("---") + return "\n".join(out) + + +def migrate_section(section: str, label: str, position: int, link_spec): + src_dir = SRC / section + dst_dir = DST / section + if dst_dir.exists(): + shutil.rmtree(dst_dir) + dst_dir.mkdir(parents=True, exist_ok=True) + + files = [] + for p in src_dir.glob("*.md"): + m = PREFIX_RE.match(p.name) + if not m: + print(f" WARN: no numeric prefix on {p.name}, skipping", file=sys.stderr) + continue + files.append((int(m.group(1)), m.group(2), p)) + files.sort() + + for sidebar_pos, (orig_n, slug_name, src_file) in enumerate(files, start=1): + text = src_file.read_text(encoding="utf-8") + pairs, body = parse_frontmatter(text) + + # Normalize / rename / inject. + normalized = [] + for k, v in pairs: + if k == "track": + v = normalize_track(v) + new_k = RENAME.get(k, k) + normalized.append((new_k, v)) + + # Inject sidebar_position (replace if already present). + for i, (k, _) in enumerate(normalized): + if k == "sidebar_position": + normalized[i] = ("sidebar_position", sidebar_pos) + break + else: + normalized.append(("sidebar_position", sidebar_pos)) + + out_text = serialize_frontmatter(normalized) + "\n\n" + body + (dst_dir / slug_name).write_text(out_text, encoding="utf-8") + + # _category_.json + cat = {"label": label, "position": position, "collapsible": True, "collapsed": False} + if link_spec[0] == "doc": + cat["link"] = {"type": "doc", "id": link_spec[1]} + elif link_spec[0] == "generated-index": + cat["link"] = {"type": "generated-index"} + (dst_dir / "_category_.json").write_text(json.dumps(cat, indent=2) + "\n", encoding="utf-8") + + print(f" {section}: {len(files)} pages") + + +def main(): + if not SRC.exists(): + sys.exit(f"Source not found: {SRC}") + if not DST.parent.exists(): + sys.exit(f"Target docs repo not found: {DST.parent}") + + # Wipe everything under docs/docs/ first so we start clean. + if DST.exists(): + shutil.rmtree(DST) + DST.mkdir(parents=True, exist_ok=True) + + print("Migrating sections:") + for section, label, position, link_spec in CATEGORIES: + migrate_section(section, label, position, link_spec) + + print(f"\nDone. Wrote to {DST}") + + +if __name__ == "__main__": + main() diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 00000000..bc9e5f6c --- /dev/null +++ b/package-lock.json @@ -0,0 +1,18594 @@ +{ + "name": "pixee-doc-site", + "version": "0.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "pixee-doc-site", + "version": "0.0.0", + "dependencies": { + "@docusaurus/core": "^3.8.1", + "@docusaurus/plugin-client-redirects": "^3.8.1", + "@docusaurus/preset-classic": "^3.8.1", + "@mdx-js/react": "^3.0.0", + "clsx": "^2.0.0", + "docusaurus-plugin-llms": "^0.4.0", + "prism-react-renderer": "^2.3.1", + "react": "^19.0.0", + "react-dom": "^19.0.0", + "yarn": "^1.22.22" + }, + "devDependencies": { + "@docusaurus/module-type-aliases": "^3.8.1", + "@docusaurus/types": "^3.8.1", + "prettier": "^3.2.5" + }, + "engines": { + "node": ">=18.0" + } + }, + "node_modules/@ai-sdk/gateway": { + "version": "2.0.0", + "resolved": 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"@docusaurus/preset-classic": "^3.8.1", + "docusaurus-plugin-llms": "^0.4.0", "@mdx-js/react": "^3.0.0", "clsx": "^2.0.0", "prism-react-renderer": "^2.3.1", diff --git a/src/components/HomepageFeatures/index.js b/src/components/HomepageFeatures/index.js deleted file mode 100644 index af3dbea9..00000000 --- a/src/components/HomepageFeatures/index.js +++ /dev/null @@ -1,74 +0,0 @@ -import React from "react"; -import styles from "./styles.module.css"; -import Link from "@docusaurus/Link"; - -export default function HomepageFeatures() { - const navigateToDocs = (type) => { - if (type === 1) { - window.location = "/intro"; - } else if (type === 2) { - window.location = "/code-scanning-tools/overview"; - } else if (type === 3) { - window.location = "/installing"; - } else if (type === 4) { - window.location = "/configuring"; - } else if (type === 5) { - window.location = "/running-your-own"; - } else if (type === 6) { - window.location = "/faqs"; - } else if (type === 7) { - window.location = "/using-pixeebot"; - } else { - window.location = "/release-notes"; - } - }; - return ( - <> -
-
navigateToDocs(1)}> -

- 👋 Introduction -

-

- Welcome to Pixee! Learn how Pixee can:{" "} -

    -
  • Fix security issues reported by your tools
    • -
  • Triage security tool findings
    • -
  • Harden your code
    • -
-

-
-
navigateToDocs(2)}> -

- 🛠️ Supported Tools -

-

- Learn about the code scanning tools Pixee supports and how to give - Pixee access to your tool findings. -

-
-
navigateToDocs(3)}> -

- ⬇ Get Started -

-

- Reach out to us to{" "} - learn more,{" "} - see a demo, and get a free trial. -

-
-
navigateToDocs(6)}> -

- ❓ FAQs -

-

- Addressing common topics such as data handling, our use of AI, on - premise offering, etc. -

-
-
-
-
- - ); -} diff --git a/src/components/HomepageFeatures/styles.module.css b/src/components/HomepageFeatures/styles.module.css deleted file mode 100644 index c676fd97..00000000 --- a/src/components/HomepageFeatures/styles.module.css +++ /dev/null @@ -1,98 +0,0 @@ -/* Grid style */ -.grid { - display: grid; - grid-template-columns: 1fr 1fr; - gap: 32px; - margin: 0 200px; -} - -.lastGrid { - display: grid; - grid-template-columns: 1fr; - gap: 32px; - margin: 32px 200px 72px 200px; -} - -.item { - border-radius: 16px; - border: 1px solid var(--neutral-neutral-20, #e6e4ea); - background: #fff; - padding: 24px; - cursor: pointer; -} - -.item:hover { - background: linear-gradient( - 45deg, - rgba(225, 230, 250, 1) 0%, - rgba(255, 255, 255, 1) 40%, - rgba(255, 255, 255, 1) 60%, - rgba(249, 214, 230, 1) 100% - ); - border: 1px solid var(--primary-barbie, #e80266); -} - -.grid h1, -.lastGrid h1 { - font-size: 24px; - font-style: normal; - font-weight: 700; - line-height: 32px; -} - -.grid h1 span, -.lastGrid h1 span { - font-family: "Poppins", sans-serif; - font-weight: 700; - color: var(--ifr-color-neutral-90); -} - -.grid p, -.lastGrid p { - font-size: 16px; - font-style: normal; - font-weight: 400; - line-height: 24px; - color: var(--ifr-color-neutral-90); -} - -/* Dark mode styles */ -[data-theme="dark"] .item { - border: 1px solid #ccc; - border-radius: 16px; - border: 1px solid #463b68; - background: var(--ifr-color-neutral-90); - padding: 24px; -} - -[data-theme="dark"] .grid h1 span, -[data-theme="dark"] .lastGrid h1 span, -[data-theme="dark"] .grid p, -[data-theme="dark"] .lastGrid p { - color: var(--ifr-color-neutral-10); -} - -[data-theme="dark"] .item:hover { - background: var( - --backgrounds-iris-focus, - radial-gradient(80.33% 96.88% at 84.06% -18.59%, #6000fe 0%, #2c2541 91.18%) - ); - border: 1px solid var(--primary-iris, #6000fe); -} - -/* Mobile view styles*/ -@media (max-width: 800px) { - .grid { - display: grid; - grid-template-columns: 1fr; - gap: 32px; - margin: 0 20px; - } - - .lastGrid { - display: grid; - grid-template-columns: 1fr; - gap: 32px; - margin: 32px 20px; - } -} diff --git a/src/pages/index.js b/src/pages/index.js deleted file mode 100644 index 67e893bc..00000000 --- a/src/pages/index.js +++ /dev/null @@ -1,30 +0,0 @@ -import React from "react"; -import Layout from "@theme/Layout"; -import HomepageFeatures from "@site/src/components/HomepageFeatures"; - -import styles from "./index.module.css"; - -function HomepageHeader() { - return ( -
-

PixeeDocs 🧚🤖

-

- Everything you need to know about Pixeebot, -
your automated product security engineer. -

-
- ); -} - -export default function Home() { - return ( -
- - -
- -
- -
- ); -} diff --git a/src/pages/index.module.css b/src/pages/index.module.css deleted file mode 100644 index a3a29404..00000000 --- a/src/pages/index.module.css +++ /dev/null @@ -1,61 +0,0 @@ -/** - * CSS files with the .module.css suffix will be treated as CSS modules - * and scoped locally. - */ - -.heroBanner { - padding: 72px 0 64px 0; - text-align: center; - position: relative; - overflow: hidden; -} - -.heroBanner h1 { - font-family: "Poppins", sans-serif; - font-size: 64px; - font-style: normal; - font-weight: 700; - line-height: 80px; - color: var(--ifr-color-neutral-90); -} - -.heroBanner p { - font-size: 20px; - font-style: normal; - font-weight: 400; - line-height: 32px; - color: var(--ifr-color-neutral-90); -} - -/* Dark mode styles */ -[data-theme="dark"] .heroBanner h1, -[data-theme="dark"] .heroBanner p { - color: var(--ifr-color-neutral-10); -} - -/* Mobile view styles*/ -@media (max-width: 800px) { - .heroBanner { - padding: 50px 0 50px 0; - } - - h1 { - margin-bottom: 0; - } - - .heroBanner h1 { - font-family: "Poppins", sans-serif; - font-size: 32px; - font-style: normal; - font-weight: 700; - color: var(--ifr-color-neutral-90); - } - - .heroBanner p { - font-size: 14px; - font-style: normal; - font-weight: 400; - line-height: 18px; - color: var(--ifr-color-neutral-90); - } -} diff --git a/src/pages/markdown-page.md b/src/pages/markdown-page.md deleted file mode 100644 index 9756c5b6..00000000 --- a/src/pages/markdown-page.md +++ /dev/null @@ -1,7 +0,0 @@ ---- -title: Markdown page example ---- - -# Markdown page example - -You don't need React to write simple standalone pages. diff --git a/static/robots.txt b/static/robots.txt new file mode 100644 index 00000000..f575a824 --- /dev/null +++ b/static/robots.txt @@ -0,0 +1,40 @@ +# docs.pixee.ai — robots.txt +# Explicit allow for AI crawlers used by ChatGPT, Claude, Perplexity, Google, etc. + +User-agent: * +Allow: / + +User-agent: GPTBot +Allow: / + +User-agent: ChatGPT-User +Allow: / + +User-agent: OAI-SearchBot +Allow: / + +User-agent: ClaudeBot +Allow: / + +User-agent: Claude-Web +Allow: / + +User-agent: anthropic-ai +Allow: / + +User-agent: PerplexityBot +Allow: / + +User-agent: Perplexity-User +Allow: / + +User-agent: Google-Extended +Allow: / + +User-agent: CCBot +Allow: / + +User-agent: Applebot-Extended +Allow: / + +Sitemap: https://docs.pixee.ai/sitemap.xml diff --git a/yarn.lock b/yarn.lock index 5881d5e0..281b5254 100644 --- a/yarn.lock +++ b/yarn.lock @@ -4,7 +4,7 @@ "@ai-sdk/gateway@2.0.0": version "2.0.0" - resolved "https://registry.yarnpkg.com/@ai-sdk/gateway/-/gateway-2.0.0.tgz#d291c40fa869174af5b7230bd838d1028488a6fd" + resolved "https://registry.npmjs.org/@ai-sdk/gateway/-/gateway-2.0.0.tgz" integrity sha512-Gj0PuawK7NkZuyYgO/h5kDK/l6hFOjhLdTq3/Lli1FTl47iGmwhH1IZQpAL3Z09BeFYWakcwUmn02ovIm2wy9g== dependencies: "@ai-sdk/provider" "2.0.0" @@ -13,7 +13,7 @@ "@ai-sdk/provider-utils@3.0.12": version "3.0.12" - resolved "https://registry.yarnpkg.com/@ai-sdk/provider-utils/-/provider-utils-3.0.12.tgz#9812a0b7ce36f2cae81dff3afe70f0c4bde76213" + resolved "https://registry.npmjs.org/@ai-sdk/provider-utils/-/provider-utils-3.0.12.tgz" integrity sha512-ZtbdvYxdMoria+2SlNarEk6Hlgyf+zzcznlD55EAl+7VZvJaSg2sqPvwArY7L6TfDEDJsnCq0fdhBSkYo0Xqdg== dependencies: "@ai-sdk/provider" "2.0.0" @@ -22,14 +22,14 @@ "@ai-sdk/provider@2.0.0": version "2.0.0" - resolved "https://registry.yarnpkg.com/@ai-sdk/provider/-/provider-2.0.0.tgz#b853c739d523b33675bc74b6c506b2c690bc602b" + resolved "https://registry.npmjs.org/@ai-sdk/provider/-/provider-2.0.0.tgz" integrity sha512-6o7Y2SeO9vFKB8lArHXehNuusnpddKPk7xqL7T2/b+OvXMRIXUO1rR4wcv1hAFUAT9avGZshty3Wlua/XA7TvA== dependencies: json-schema "^0.4.0" "@ai-sdk/react@^2.0.30": version "2.0.76" - resolved "https://registry.yarnpkg.com/@ai-sdk/react/-/react-2.0.76.tgz#eba2457f208d1762f16f807e1c4324cdf63bd969" + resolved "https://registry.npmjs.org/@ai-sdk/react/-/react-2.0.76.tgz" integrity sha512-ggAPzyaKJTqUWigpxMzI5DuC0Y3iEpDUPCgz6/6CpnKZY/iok+x5xiZhDemeaP0ILw5IQekV0kdgBR8JPgI8zQ== dependencies: "@ai-sdk/provider-utils" "3.0.12" @@ -39,7 +39,7 @@ "@algolia/abtesting@1.6.1": version "1.6.1" - resolved "https://registry.yarnpkg.com/@algolia/abtesting/-/abtesting-1.6.1.tgz#1074f6df6a59b371f56fdb5ddc2caec1853bcc58" + resolved "https://registry.npmjs.org/@algolia/abtesting/-/abtesting-1.6.1.tgz" integrity sha512-wV/gNRkzb7sI9vs1OneG129hwe3Q5zPj7zigz3Ps7M5Lpo2hSorrOnXNodHEOV+yXE/ks4Pd+G3CDFIjFTWhMQ== dependencies: "@algolia/client-common" "5.40.1" @@ -49,7 +49,7 @@ "@algolia/autocomplete-core@1.19.2": version "1.19.2" - resolved "https://registry.yarnpkg.com/@algolia/autocomplete-core/-/autocomplete-core-1.19.2.tgz#702df67a08cb3cfe8c33ee1111ef136ec1a9e232" + resolved "https://registry.npmjs.org/@algolia/autocomplete-core/-/autocomplete-core-1.19.2.tgz" integrity sha512-mKv7RyuAzXvwmq+0XRK8HqZXt9iZ5Kkm2huLjgn5JoCPtDy+oh9yxUMfDDaVCw0oyzZ1isdJBc7l9nuCyyR7Nw== dependencies: "@algolia/autocomplete-plugin-algolia-insights" "1.19.2" @@ -57,19 +57,19 @@ "@algolia/autocomplete-plugin-algolia-insights@1.19.2": version "1.19.2" - resolved "https://registry.yarnpkg.com/@algolia/autocomplete-plugin-algolia-insights/-/autocomplete-plugin-algolia-insights-1.19.2.tgz#3584b625b9317e333d1ae43664d02358e175c52d" + resolved "https://registry.npmjs.org/@algolia/autocomplete-plugin-algolia-insights/-/autocomplete-plugin-algolia-insights-1.19.2.tgz" integrity sha512-TjxbcC/r4vwmnZaPwrHtkXNeqvlpdyR+oR9Wi2XyfORkiGkLTVhX2j+O9SaCCINbKoDfc+c2PB8NjfOnz7+oKg== dependencies: "@algolia/autocomplete-shared" "1.19.2" "@algolia/autocomplete-shared@1.19.2": version "1.19.2" - resolved "https://registry.yarnpkg.com/@algolia/autocomplete-shared/-/autocomplete-shared-1.19.2.tgz#c0b7b8dc30a5c65b70501640e62b009535e4578f" + resolved "https://registry.npmjs.org/@algolia/autocomplete-shared/-/autocomplete-shared-1.19.2.tgz" integrity sha512-jEazxZTVD2nLrC+wYlVHQgpBoBB5KPStrJxLzsIFl6Kqd1AlG9sIAGl39V5tECLpIQzB3Qa2T6ZPJ1ChkwMK/w== "@algolia/client-abtesting@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-abtesting/-/client-abtesting-5.40.1.tgz#6674c20731e887a081edf7ea009fe00ce20537d4" + resolved "https://registry.npmjs.org/@algolia/client-abtesting/-/client-abtesting-5.40.1.tgz" integrity sha512-cxKNATPY5t+Mv8XAVTI57altkaPH+DZi4uMrnexPxPHODMljhGYY+GDZyHwv9a+8CbZHcY372OkxXrDMZA4Lnw== dependencies: "@algolia/client-common" "5.40.1" @@ -79,7 +79,7 @@ "@algolia/client-analytics@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-analytics/-/client-analytics-5.40.1.tgz#6550da491a59e9bc5112d9aeb1964e04b34543c5" + resolved "https://registry.npmjs.org/@algolia/client-analytics/-/client-analytics-5.40.1.tgz" integrity sha512-XP008aMffJCRGAY8/70t+hyEyvqqV7YKm502VPu0+Ji30oefrTn2al7LXkITz7CK6I4eYXWRhN6NaIUi65F1OA== dependencies: "@algolia/client-common" "5.40.1" @@ -89,12 +89,17 @@ "@algolia/client-common@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-common/-/client-common-5.40.1.tgz#df272c1eb491e7e4b15eaa44e4ad781630b4a438" + resolved "https://registry.npmjs.org/@algolia/client-common/-/client-common-5.40.1.tgz" integrity sha512-gWfQuQUBtzUboJv/apVGZMoxSaB0M4Imwl1c9Ap+HpCW7V0KhjBddqF2QQt5tJZCOFsfNIgBbZDGsEPaeKUosw== +"@algolia/client-common@5.52.1": + version "5.52.1" + resolved "https://registry.npmjs.org/@algolia/client-common/-/client-common-5.52.1.tgz" + integrity sha512-qCDoZfx5MpX7XQzvQ3bC4tSEMkQWQMaF/ABtLuoze03Y/flR563CCSws02qIJ23oX7lxl92LsilZjINVyTdtLw== + "@algolia/client-insights@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-insights/-/client-insights-5.40.1.tgz#db53a74d78b004b176213dfe84cb250323e64906" + resolved "https://registry.npmjs.org/@algolia/client-insights/-/client-insights-5.40.1.tgz" integrity sha512-RTLjST/t+lsLMouQ4zeLJq2Ss+UNkLGyNVu+yWHanx6kQ3LT5jv8UvPwyht9s7R6jCPnlSI77WnL80J32ZuyJg== dependencies: "@algolia/client-common" "5.40.1" @@ -104,7 +109,7 @@ "@algolia/client-personalization@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-personalization/-/client-personalization-5.40.1.tgz#9e9885a1855b893ddb3cefa484d5d08158b622f5" + resolved "https://registry.npmjs.org/@algolia/client-personalization/-/client-personalization-5.40.1.tgz" integrity sha512-2FEK6bUomBzEYkTKzD0iRs7Ljtjb45rKK/VSkyHqeJnG+77qx557IeSO0qVFE3SfzapNcoytTofnZum0BQ6r3Q== dependencies: "@algolia/client-common" "5.40.1" @@ -114,7 +119,7 @@ "@algolia/client-query-suggestions@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-query-suggestions/-/client-query-suggestions-5.40.1.tgz#45dd6d7ad53f87043d44ffe983ab2d2385c8270a" + resolved "https://registry.npmjs.org/@algolia/client-query-suggestions/-/client-query-suggestions-5.40.1.tgz" integrity sha512-Nju4NtxAvXjrV2hHZNLKVJLXjOlW6jAXHef/CwNzk1b2qIrCWDO589ELi5ZHH1uiWYoYyBXDQTtHmhaOVVoyXg== dependencies: "@algolia/client-common" "5.40.1" @@ -122,9 +127,19 @@ "@algolia/requester-fetch" "5.40.1" "@algolia/requester-node-http" "5.40.1" +"@algolia/client-search@>= 4.9.1 < 6": + version "5.52.1" + resolved "https://registry.npmjs.org/@algolia/client-search/-/client-search-5.52.1.tgz" + integrity sha512-gA8oJOV1LnQQkDf91iebNnFInHuW0gRPEgLSOQ7EfipCEjYTHm5swm1DlH9H5RaRw4RrHuzHBegnlzc0MAstcg== + dependencies: + "@algolia/client-common" "5.52.1" + "@algolia/requester-browser-xhr" "5.52.1" + "@algolia/requester-fetch" "5.52.1" + "@algolia/requester-node-http" "5.52.1" + "@algolia/client-search@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/client-search/-/client-search-5.40.1.tgz#9e179ac583dd9ddf638139e24971bb9229897931" + resolved "https://registry.npmjs.org/@algolia/client-search/-/client-search-5.40.1.tgz" integrity sha512-Mw6pAUF121MfngQtcUb5quZVqMC68pSYYjCRZkSITC085S3zdk+h/g7i6FxnVdbSU6OztxikSDMh1r7Z+4iPlA== dependencies: "@algolia/client-common" "5.40.1" @@ -134,12 +149,12 @@ "@algolia/events@^4.0.1": version "4.0.1" - resolved "https://registry.yarnpkg.com/@algolia/events/-/events-4.0.1.tgz#fd39e7477e7bc703d7f893b556f676c032af3950" + resolved "https://registry.npmjs.org/@algolia/events/-/events-4.0.1.tgz" integrity sha512-FQzvOCgoFXAbf5Y6mYozw2aj5KCJoA3m4heImceldzPSMbdyS4atVjJzXKMsfX3wnZTFYwkkt8/z8UesLHlSBQ== "@algolia/ingestion@1.40.1": version "1.40.1" - resolved "https://registry.yarnpkg.com/@algolia/ingestion/-/ingestion-1.40.1.tgz#eea0793d6e89b424d742d726de7419f5bcaefa16" + resolved "https://registry.npmjs.org/@algolia/ingestion/-/ingestion-1.40.1.tgz" integrity sha512-z+BPlhs45VURKJIxsR99NNBWpUEEqIgwt10v/fATlNxc4UlXvALdOsWzaFfe89/lbP5Bu4+mbO59nqBC87ZM/g== dependencies: "@algolia/client-common" "5.40.1" @@ -149,7 +164,7 @@ "@algolia/monitoring@1.40.1": version "1.40.1" - resolved "https://registry.yarnpkg.com/@algolia/monitoring/-/monitoring-1.40.1.tgz#50bf7286f3ba0fae220d7f5e0bf73c1b671f8958" + resolved "https://registry.npmjs.org/@algolia/monitoring/-/monitoring-1.40.1.tgz" integrity sha512-VJMUMbO0wD8Rd2VVV/nlFtLJsOAQvjnVNGkMkspFiFhpBA7s/xJOb+fJvvqwKFUjbKTUA7DjiSi1ljSMYBasXg== dependencies: "@algolia/client-common" "5.40.1" @@ -159,7 +174,7 @@ "@algolia/recommend@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/recommend/-/recommend-5.40.1.tgz#db8395ce0d17ccba03a877b42dce1f205bbdf5b9" + resolved "https://registry.npmjs.org/@algolia/recommend/-/recommend-5.40.1.tgz" integrity sha512-ehvJLadKVwTp9Scg9NfzVSlBKH34KoWOQNTaN8i1Ac64AnO6iH2apJVSP6GOxssaghZ/s8mFQsDH3QIZoluFHA== dependencies: "@algolia/client-common" "5.40.1" @@ -169,28 +184,49 @@ "@algolia/requester-browser-xhr@5.40.1": version "5.40.1" - resolved "https://registry.yarnpkg.com/@algolia/requester-browser-xhr/-/requester-browser-xhr-5.40.1.tgz#cddc52f7dc8e4b4a1051f90e55336d9573df62af" + resolved "https://registry.npmjs.org/@algolia/requester-browser-xhr/-/requester-browser-xhr-5.40.1.tgz" integrity sha512-PbidVsPurUSQIr6X9/7s34mgOMdJnn0i6p+N6Ab+lsNhY5eiu+S33kZEpZwkITYBCIbhzDLOvb7xZD3gDi+USA== dependencies: "@algolia/client-common" "5.40.1" +"@algolia/requester-browser-xhr@5.52.1": + version "5.52.1" + resolved "https://registry.npmjs.org/@algolia/requester-browser-xhr/-/requester-browser-xhr-5.52.1.tgz" + integrity sha512-CI7+/0I11QeZM59Uc8whd2or0kqzFVjpaPn9Qpwll/krHcBAxk24WkAQ6WX+IwDVMfpont4YGbKwAmCre3vE8Q== + dependencies: + "@algolia/client-common" "5.52.1" + "@algolia/requester-fetch@5.40.1": version "5.40.1" - 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resolved "https://registry.yarnpkg.com/@csstools/css-parser-algorithms/-/css-parser-algorithms-3.0.5.tgz#5755370a9a29abaec5515b43c8b3f2cf9c2e3076" + resolved "https://registry.npmjs.org/@csstools/css-parser-algorithms/-/css-parser-algorithms-3.0.5.tgz" integrity sha512-DaDeUkXZKjdGhgYaHNJTV9pV7Y9B3b644jCLs9Upc3VeNGg6LWARAT6O+Q+/COo+2gg/bM5rhpMAtf70WqfBdQ== "@csstools/css-tokenizer@^3.0.4": version "3.0.4" - resolved "https://registry.yarnpkg.com/@csstools/css-tokenizer/-/css-tokenizer-3.0.4.tgz#333fedabc3fd1a8e5d0100013731cf19e6a8c5d3" + resolved "https://registry.npmjs.org/@csstools/css-tokenizer/-/css-tokenizer-3.0.4.tgz" integrity sha512-Vd/9EVDiu6PPJt9yAh6roZP6El1xHrdvIVGjyBsHR0RYwNHgL7FJPyIIW4fANJNG6FtyZfvlRPpFI4ZM/lubvw== "@csstools/media-query-list-parser@^4.0.3": version "4.0.3" - resolved "https://registry.yarnpkg.com/@csstools/media-query-list-parser/-/media-query-list-parser-4.0.3.tgz#7aec77bcb89c2da80ef207e73f474ef9e1b3cdf1" + resolved "https://registry.npmjs.org/@csstools/media-query-list-parser/-/media-query-list-parser-4.0.3.tgz" integrity sha512-HAYH7d3TLRHDOUQK4mZKf9k9Ph/m8Akstg66ywKR4SFAigjs3yBiUeZtFxywiTm5moZMAp/5W/ZuFnNXXYLuuQ== "@csstools/postcss-alpha-function@^1.0.1": version "1.0.1" - 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resolved "https://registry.yarnpkg.com/@csstools/postcss-is-pseudo-class/-/postcss-is-pseudo-class-5.0.3.tgz#d34e850bcad4013c2ed7abe948bfa0448aa8eb74" + resolved "https://registry.npmjs.org/@csstools/postcss-is-pseudo-class/-/postcss-is-pseudo-class-5.0.3.tgz" integrity sha512-jS/TY4SpG4gszAtIg7Qnf3AS2pjcUM5SzxpApOrlndMeGhIbaTzWBzzP/IApXoNWEW7OhcjkRT48jnAUIFXhAQ== dependencies: "@csstools/selector-specificity" "^5.0.0" @@ -1288,7 +1324,7 @@ "@csstools/postcss-light-dark-function@^2.0.11": version "2.0.11" - resolved "https://registry.yarnpkg.com/@csstools/postcss-light-dark-function/-/postcss-light-dark-function-2.0.11.tgz#0df448aab9a33cb9a085264ff1f396fb80c4437d" + resolved "https://registry.npmjs.org/@csstools/postcss-light-dark-function/-/postcss-light-dark-function-2.0.11.tgz" integrity sha512-fNJcKXJdPM3Lyrbmgw2OBbaioU7yuKZtiXClf4sGdQttitijYlZMD5K7HrC/eF83VRWRrYq6OZ0Lx92leV2LFA== dependencies: "@csstools/css-parser-algorithms" "^3.0.5" @@ -1298,29 +1334,29 @@ "@csstools/postcss-logical-float-and-clear@^3.0.0": version "3.0.0" - resolved "https://registry.yarnpkg.com/@csstools/postcss-logical-float-and-clear/-/postcss-logical-float-and-clear-3.0.0.tgz#62617564182cf86ab5d4e7485433ad91e4c58571" + resolved "https://registry.npmjs.org/@csstools/postcss-logical-float-and-clear/-/postcss-logical-float-and-clear-3.0.0.tgz" integrity sha512-SEmaHMszwakI2rqKRJgE+8rpotFfne1ZS6bZqBoQIicFyV+xT1UF42eORPxJkVJVrH9C0ctUgwMSn3BLOIZldQ== "@csstools/postcss-logical-overflow@^2.0.0": version "2.0.0" - resolved "https://registry.yarnpkg.com/@csstools/postcss-logical-overflow/-/postcss-logical-overflow-2.0.0.tgz#c6de7c5f04e3d4233731a847f6c62819bcbcfa1d" + resolved "https://registry.npmjs.org/@csstools/postcss-logical-overflow/-/postcss-logical-overflow-2.0.0.tgz" integrity sha512-spzR1MInxPuXKEX2csMamshR4LRaSZ3UXVaRGjeQxl70ySxOhMpP2252RAFsg8QyyBXBzuVOOdx1+bVO5bPIzA== "@csstools/postcss-logical-overscroll-behavior@^2.0.0": version "2.0.0" - resolved "https://registry.yarnpkg.com/@csstools/postcss-logical-overscroll-behavior/-/postcss-logical-overscroll-behavior-2.0.0.tgz#43c03eaecdf34055ef53bfab691db6dc97a53d37" + resolved "https://registry.npmjs.org/@csstools/postcss-logical-overscroll-behavior/-/postcss-logical-overscroll-behavior-2.0.0.tgz" integrity sha512-e/webMjoGOSYfqLunyzByZj5KKe5oyVg/YSbie99VEaSDE2kimFm0q1f6t/6Jo+VVCQ/jbe2Xy+uX+C4xzWs4w== "@csstools/postcss-logical-resize@^3.0.0": version "3.0.0" - resolved "https://registry.yarnpkg.com/@csstools/postcss-logical-resize/-/postcss-logical-resize-3.0.0.tgz#4df0eeb1a61d7bd85395e56a5cce350b5dbfdca6" + resolved "https://registry.npmjs.org/@csstools/postcss-logical-resize/-/postcss-logical-resize-3.0.0.tgz" integrity sha512-DFbHQOFW/+I+MY4Ycd/QN6Dg4Hcbb50elIJCfnwkRTCX05G11SwViI5BbBlg9iHRl4ytB7pmY5ieAFk3ws7yyg== dependencies: postcss-value-parser "^4.2.0" "@csstools/postcss-logical-viewport-units@^3.0.4": version "3.0.4" - resolved "https://registry.yarnpkg.com/@csstools/postcss-logical-viewport-units/-/postcss-logical-viewport-units-3.0.4.tgz#016d98a8b7b5f969e58eb8413447eb801add16fc" + resolved "https://registry.npmjs.org/@csstools/postcss-logical-viewport-units/-/postcss-logical-viewport-units-3.0.4.tgz" integrity sha512-q+eHV1haXA4w9xBwZLKjVKAWn3W2CMqmpNpZUk5kRprvSiBEGMgrNH3/sJZ8UA3JgyHaOt3jwT9uFa4wLX4EqQ== dependencies: "@csstools/css-tokenizer" "^3.0.4" @@ -1328,7 +1364,7 @@ "@csstools/postcss-media-minmax@^2.0.9": version "2.0.9" - resolved "https://registry.yarnpkg.com/@csstools/postcss-media-minmax/-/postcss-media-minmax-2.0.9.tgz#184252d5b93155ae526689328af6bdf3fc113987" + resolved "https://registry.npmjs.org/@csstools/postcss-media-minmax/-/postcss-media-minmax-2.0.9.tgz" integrity sha512-af9Qw3uS3JhYLnCbqtZ9crTvvkR+0Se+bBqSr7ykAnl9yKhk6895z9rf+2F4dClIDJWxgn0iZZ1PSdkhrbs2ig== dependencies: "@csstools/css-calc" "^2.1.4" @@ -1338,7 +1374,7 @@ "@csstools/postcss-media-queries-aspect-ratio-number-values@^3.0.5": version "3.0.5" - resolved "https://registry.yarnpkg.com/@csstools/postcss-media-queries-aspect-ratio-number-values/-/postcss-media-queries-aspect-ratio-number-values-3.0.5.tgz#f485c31ec13d6b0fb5c528a3474334a40eff5f11" + resolved "https://registry.npmjs.org/@csstools/postcss-media-queries-aspect-ratio-number-values/-/postcss-media-queries-aspect-ratio-number-values-3.0.5.tgz" integrity sha512-zhAe31xaaXOY2Px8IYfoVTB3wglbJUVigGphFLj6exb7cjZRH9A6adyE22XfFK3P2PzwRk0VDeTJmaxpluyrDg== dependencies: "@csstools/css-parser-algorithms" "^3.0.5" @@ -1347,7 +1383,7 @@ "@csstools/postcss-nested-calc@^4.0.0": version "4.0.0" - resolved "https://registry.yarnpkg.com/@csstools/postcss-nested-calc/-/postcss-nested-calc-4.0.0.tgz#754e10edc6958d664c11cde917f44ba144141c62" + resolved "https://registry.npmjs.org/@csstools/postcss-nested-calc/-/postcss-nested-calc-4.0.0.tgz" integrity sha512-jMYDdqrQQxE7k9+KjstC3NbsmC063n1FTPLCgCRS2/qHUbHM0mNy9pIn4QIiQGs9I/Bg98vMqw7mJXBxa0N88A== dependencies: "@csstools/utilities" "^2.0.0" @@ -1355,14 +1391,14 @@ "@csstools/postcss-normalize-display-values@^4.0.0": version "4.0.0" - resolved "https://registry.yarnpkg.com/@csstools/postcss-normalize-display-values/-/postcss-normalize-display-values-4.0.0.tgz#ecdde2daf4e192e5da0c6fd933b6d8aff32f2a36" + resolved "https://registry.npmjs.org/@csstools/postcss-normalize-display-values/-/postcss-normalize-display-values-4.0.0.tgz" integrity sha512-HlEoG0IDRoHXzXnkV4in47dzsxdsjdz6+j7MLjaACABX2NfvjFS6XVAnpaDyGesz9gK2SC7MbNwdCHusObKJ9Q== dependencies: postcss-value-parser "^4.2.0" "@csstools/postcss-oklab-function@^4.0.12": version "4.0.12" - resolved "https://registry.yarnpkg.com/@csstools/postcss-oklab-function/-/postcss-oklab-function-4.0.12.tgz#416640ef10227eea1375b47b72d141495950971d" + resolved "https://registry.npmjs.org/@csstools/postcss-oklab-function/-/postcss-oklab-function-4.0.12.tgz" integrity sha512-HhlSmnE1NKBhXsTnNGjxvhryKtO7tJd1w42DKOGFD6jSHtYOrsJTQDKPMwvOfrzUAk8t7GcpIfRyM7ssqHpFjg== dependencies: "@csstools/css-color-parser" "^3.1.0" @@ -1373,14 +1409,14 @@ "@csstools/postcss-progressive-custom-properties@^4.2.1": version "4.2.1" - resolved "https://registry.yarnpkg.com/@csstools/postcss-progressive-custom-properties/-/postcss-progressive-custom-properties-4.2.1.tgz#c39780b9ff0d554efb842b6bd75276aa6f1705db" + resolved "https://registry.npmjs.org/@csstools/postcss-progressive-custom-properties/-/postcss-progressive-custom-properties-4.2.1.tgz" integrity sha512-uPiiXf7IEKtUQXsxu6uWtOlRMXd2QWWy5fhxHDnPdXKCQckPP3E34ZgDoZ62r2iT+UOgWsSbM4NvHE5m3mAEdw== dependencies: postcss-value-parser "^4.2.0" "@csstools/postcss-random-function@^2.0.1": version "2.0.1" - 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resolved "https://registry.yarnpkg.com/@docsearch/react/-/react-4.2.0.tgz#9dac48dfb4c1e5f18cf7323d8221d99c0d5f3e4e" + resolved "https://registry.npmjs.org/@docsearch/react/-/react-4.2.0.tgz" integrity sha512-zSN/KblmtBcerf7Z87yuKIHZQmxuXvYc6/m0+qnjyNu+Ir67AVOagTa1zBqcxkVUVkmBqUExdcyrdo9hbGbqTw== dependencies: "@ai-sdk/react" "^2.0.30" @@ -1485,7 +1521,7 @@ "@docusaurus/babel@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/babel/-/babel-3.9.2.tgz#f956c638baeccf2040e482c71a742bc7e35fdb22" + resolved "https://registry.npmjs.org/@docusaurus/babel/-/babel-3.9.2.tgz" integrity sha512-GEANdi/SgER+L7Japs25YiGil/AUDnFFHaCGPBbundxoWtCkA2lmy7/tFmgED4y1htAy6Oi4wkJEQdGssnw9MA== dependencies: "@babel/core" "^7.25.9" @@ -1506,7 +1542,7 @@ "@docusaurus/bundler@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/bundler/-/bundler-3.9.2.tgz#0ca82cda4acf13a493e3f66061aea351e9d356cf" + resolved "https://registry.npmjs.org/@docusaurus/bundler/-/bundler-3.9.2.tgz" integrity sha512-ZOVi6GYgTcsZcUzjblpzk3wH1Fya2VNpd5jtHoCCFcJlMQ1EYXZetfAnRHLcyiFeBABaI1ltTYbOBtH/gahGVA== dependencies: "@babel/core" "^7.25.9" @@ -1534,9 +1570,9 @@ webpack "^5.95.0" webpackbar "^6.0.1" -"@docusaurus/core@3.9.2", "@docusaurus/core@^3.8.1": +"@docusaurus/core@^3.0.0", "@docusaurus/core@^3.8.1", "@docusaurus/core@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/core/-/core-3.9.2.tgz#cc970f29b85a8926d63c84f8cffdcda43ed266ff" + resolved "https://registry.npmjs.org/@docusaurus/core/-/core-3.9.2.tgz" integrity sha512-HbjwKeC+pHUFBfLMNzuSjqFE/58+rLVKmOU3lxQrpsxLBOGosYco/Q0GduBb0/jEMRiyEqjNT/01rRdOMWq5pw== dependencies: "@docusaurus/babel" "3.9.2" @@ -1584,7 +1620,7 @@ "@docusaurus/cssnano-preset@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/cssnano-preset/-/cssnano-preset-3.9.2.tgz#523aab65349db3c51a77f2489048d28527759428" + resolved "https://registry.npmjs.org/@docusaurus/cssnano-preset/-/cssnano-preset-3.9.2.tgz" integrity sha512-8gBKup94aGttRduABsj7bpPFTX7kbwu+xh3K9NMCF5K4bWBqTFYW+REKHF6iBVDHRJ4grZdIPbvkiHd/XNKRMQ== dependencies: cssnano-preset-advanced "^6.1.2" @@ -1594,7 +1630,7 @@ "@docusaurus/logger@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/logger/-/logger-3.9.2.tgz#6ec6364b90f5a618a438cc9fd01ac7376869f92a" + resolved "https://registry.npmjs.org/@docusaurus/logger/-/logger-3.9.2.tgz" integrity sha512-/SVCc57ByARzGSU60c50rMyQlBuMIJCjcsJlkphxY6B0GV4UH3tcA1994N8fFfbJ9kX3jIBe/xg3XP5qBtGDbA== dependencies: chalk "^4.1.2" @@ -1602,7 +1638,7 @@ "@docusaurus/mdx-loader@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/mdx-loader/-/mdx-loader-3.9.2.tgz#78d238de6c6203fa811cc2a7e90b9b79e111408c" + resolved "https://registry.npmjs.org/@docusaurus/mdx-loader/-/mdx-loader-3.9.2.tgz" integrity sha512-wiYoGwF9gdd6rev62xDU8AAM8JuLI/hlwOtCzMmYcspEkzecKrP8J8X+KpYnTlACBUUtXNJpSoCwFWJhLRevzQ== dependencies: "@docusaurus/logger" "3.9.2" @@ -1630,9 +1666,9 @@ vfile "^6.0.1" webpack "^5.88.1" -"@docusaurus/module-type-aliases@3.9.2", "@docusaurus/module-type-aliases@^3.8.1": +"@docusaurus/module-type-aliases@^3.8.1", "@docusaurus/module-type-aliases@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/module-type-aliases/-/module-type-aliases-3.9.2.tgz#993c7cb0114363dea5ef6855e989b3ad4b843a34" + resolved "https://registry.npmjs.org/@docusaurus/module-type-aliases/-/module-type-aliases-3.9.2.tgz" integrity sha512-8qVe2QA9hVLzvnxP46ysuofJUIc/yYQ82tvA/rBTrnpXtCjNSFLxEZfd5U8cYZuJIVlkPxamsIgwd5tGZXfvew== dependencies: "@docusaurus/types" "3.9.2" @@ -1645,7 +1681,7 @@ "@docusaurus/plugin-client-redirects@^3.8.1": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-client-redirects/-/plugin-client-redirects-3.9.2.tgz#9c27025c72aeeedeb783a94720163911567da0e8" + resolved "https://registry.npmjs.org/@docusaurus/plugin-client-redirects/-/plugin-client-redirects-3.9.2.tgz" integrity sha512-lUgMArI9vyOYMzLRBUILcg9vcPTCyyI2aiuXq/4npcMVqOr6GfmwtmBYWSbNMlIUM0147smm4WhpXD0KFboffw== dependencies: "@docusaurus/core" "3.9.2" @@ -1660,7 +1696,7 @@ "@docusaurus/plugin-content-blog@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-blog/-/plugin-content-blog-3.9.2.tgz#d5ce51eb7757bdab0515e2dd26a793ed4e119df9" + resolved "https://registry.npmjs.org/@docusaurus/plugin-content-blog/-/plugin-content-blog-3.9.2.tgz" integrity sha512-3I2HXy3L1QcjLJLGAoTvoBnpOwa6DPUa3Q0dMK19UTY9mhPkKQg/DYhAGTiBUKcTR0f08iw7kLPqOhIgdV3eVQ== dependencies: "@docusaurus/core" "3.9.2" @@ -1682,9 +1718,9 @@ utility-types "^3.10.0" webpack "^5.88.1" -"@docusaurus/plugin-content-docs@3.9.2": +"@docusaurus/plugin-content-docs@*", "@docusaurus/plugin-content-docs@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-docs/-/plugin-content-docs-3.9.2.tgz#cd8f2d1c06e53c3fa3d24bdfcb48d237bf2d6b2e" + resolved "https://registry.npmjs.org/@docusaurus/plugin-content-docs/-/plugin-content-docs-3.9.2.tgz" integrity sha512-C5wZsGuKTY8jEYsqdxhhFOe1ZDjH0uIYJ9T/jebHwkyxqnr4wW0jTkB72OMqNjsoQRcb0JN3PcSeTwFlVgzCZg== dependencies: "@docusaurus/core" "3.9.2" @@ -1708,7 +1744,7 @@ "@docusaurus/plugin-content-pages@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-content-pages/-/plugin-content-pages-3.9.2.tgz#22db6c88ade91cec0a9e87a00b8089898051b08d" + resolved "https://registry.npmjs.org/@docusaurus/plugin-content-pages/-/plugin-content-pages-3.9.2.tgz" integrity sha512-s4849w/p4noXUrGpPUF0BPqIAfdAe76BLaRGAGKZ1gTDNiGxGcpsLcwJ9OTi1/V8A+AzvsmI9pkjie2zjIQZKA== dependencies: "@docusaurus/core" "3.9.2" @@ -1722,7 +1758,7 @@ "@docusaurus/plugin-css-cascade-layers@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-css-cascade-layers/-/plugin-css-cascade-layers-3.9.2.tgz#358c85f63f1c6a11f611f1b8889d9435c11b22f8" + resolved "https://registry.npmjs.org/@docusaurus/plugin-css-cascade-layers/-/plugin-css-cascade-layers-3.9.2.tgz" integrity sha512-w1s3+Ss+eOQbscGM4cfIFBlVg/QKxyYgj26k5AnakuHkKxH6004ZtuLe5awMBotIYF2bbGDoDhpgQ4r/kcj4rQ== dependencies: "@docusaurus/core" "3.9.2" @@ -1733,7 +1769,7 @@ "@docusaurus/plugin-debug@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-debug/-/plugin-debug-3.9.2.tgz#b5df4db115583f5404a252dbf66f379ff933e53c" + resolved "https://registry.npmjs.org/@docusaurus/plugin-debug/-/plugin-debug-3.9.2.tgz" integrity sha512-j7a5hWuAFxyQAkilZwhsQ/b3T7FfHZ+0dub6j/GxKNFJp2h9qk/P1Bp7vrGASnvA9KNQBBL1ZXTe7jlh4VdPdA== dependencies: "@docusaurus/core" "3.9.2" @@ -1745,7 +1781,7 @@ "@docusaurus/plugin-google-analytics@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-analytics/-/plugin-google-analytics-3.9.2.tgz#857fe075fdeccdf6959e62954d9efe39769fa247" + resolved "https://registry.npmjs.org/@docusaurus/plugin-google-analytics/-/plugin-google-analytics-3.9.2.tgz" integrity sha512-mAwwQJ1Us9jL/lVjXtErXto4p4/iaLlweC54yDUK1a97WfkC6Z2k5/769JsFgwOwOP+n5mUQGACXOEQ0XDuVUw== dependencies: "@docusaurus/core" "3.9.2" @@ -1755,7 +1791,7 @@ "@docusaurus/plugin-google-gtag@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.9.2.tgz#df75b1a90ae9266b0471909ba0265f46d5dcae62" + resolved "https://registry.npmjs.org/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.9.2.tgz" integrity sha512-YJ4lDCphabBtw19ooSlc1MnxtYGpjFV9rEdzjLsUnBCeis2djUyCozZaFhCg6NGEwOn7HDDyMh0yzcdRpnuIvA== dependencies: "@docusaurus/core" "3.9.2" @@ -1766,7 +1802,7 @@ "@docusaurus/plugin-google-tag-manager@3.9.2": version "3.9.2" - 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resolved "https://registry.yarnpkg.com/@docusaurus/preset-classic/-/preset-classic-3.9.2.tgz#85cc4f91baf177f8146c9ce896dfa1f0fd377050" + resolved "https://registry.npmjs.org/@docusaurus/preset-classic/-/preset-classic-3.9.2.tgz" integrity sha512-IgyYO2Gvaigi21LuDIe+nvmN/dfGXAiMcV/murFqcpjnZc7jxFAxW+9LEjdPt61uZLxG4ByW/oUmX/DDK9t/8w== dependencies: "@docusaurus/core" "3.9.2" @@ -1826,7 +1862,7 @@ "@docusaurus/theme-classic@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/theme-classic/-/theme-classic-3.9.2.tgz#6e514f99a0ff42b80afcf42d5e5d042618311ce0" + resolved "https://registry.npmjs.org/@docusaurus/theme-classic/-/theme-classic-3.9.2.tgz" integrity sha512-IGUsArG5hhekXd7RDb11v94ycpJpFdJPkLnt10fFQWOVxAtq5/D7hT6lzc2fhyQKaaCE62qVajOMKL7OiAFAIA== dependencies: "@docusaurus/core" "3.9.2" @@ -1857,7 +1893,7 @@ "@docusaurus/theme-common@3.9.2": version "3.9.2" - resolved "https://registry.yarnpkg.com/@docusaurus/theme-common/-/theme-common-3.9.2.tgz#487172c6fef9815c2746ef62a71e4f5b326f9ba5" + resolved "https://registry.npmjs.org/@docusaurus/theme-common/-/theme-common-3.9.2.tgz" integrity sha512-6c4DAbR6n6nPbnZhY2V3tzpnKnGL+6aOsLvFL26VRqhlczli9eWG0VDUNoCQEPnGwDMhPS42UhSAnz5pThm5Ag== dependencies: "@docusaurus/mdx-loader" "3.9.2" @@ -1875,7 +1911,7 @@ "@docusaurus/theme-search-algolia@3.9.2": version "3.9.2" - 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resolved "https://registry.yarnpkg.com/@webassemblyjs/wast-printer/-/wast-printer-1.14.1.tgz#3bb3e9638a8ae5fdaf9610e7a06b4d9f9aa6fe07" + resolved "https://registry.npmjs.org/@webassemblyjs/wast-printer/-/wast-printer-1.14.1.tgz" integrity sha512-kPSSXE6De1XOR820C90RIo2ogvZG+c3KiHzqUoO/F34Y2shGzesfqv7o57xrxovZJH/MetF5UjroJ/R/3isoiw== dependencies: "@webassemblyjs/ast" "1.14.1" @@ -2823,17 +2840,17 @@ "@xtuc/ieee754@^1.2.0": version "1.2.0" - resolved "https://registry.yarnpkg.com/@xtuc/ieee754/-/ieee754-1.2.0.tgz#eef014a3145ae477a1cbc00cd1e552336dceb790" + resolved "https://registry.npmjs.org/@xtuc/ieee754/-/ieee754-1.2.0.tgz" integrity sha512-DX8nKgqcGwsc0eJSqYt5lwP4DH5FlHnmuWWBRy7X0NcaGR0ZtuyeESgMwTYVEtxmsNGY+qit4QYT/MIYTOTPeA== "@xtuc/long@4.2.2": version "4.2.2" - resolved "https://registry.yarnpkg.com/@xtuc/long/-/long-4.2.2.tgz#d291c6a4e97989b5c61d9acf396ae4fe133a718d" + resolved "https://registry.npmjs.org/@xtuc/long/-/long-4.2.2.tgz" integrity sha512-NuHqBY1PB/D8xU6s/thBgOAiAP7HOYDQ32+BFZILJ8ivkUkAHQnWfn6WhL79Owj1qmUnoN/YPhktdIoucipkAQ== accepts@~1.3.4, accepts@~1.3.8: version "1.3.8" - 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resolved "https://registry.yarnpkg.com/micromark-extension-gfm-footnote/-/micromark-extension-gfm-footnote-2.1.0.tgz#4dab56d4e398b9853f6fe4efac4fc9361f3e0750" + resolved "https://registry.npmjs.org/micromark-extension-gfm-footnote/-/micromark-extension-gfm-footnote-2.1.0.tgz" integrity sha512-/yPhxI1ntnDNsiHtzLKYnE3vf9JZ6cAisqVDauhp4CEHxlb4uoOTxOCJ+9s51bIB8U1N1FJ1RXOKTIlD5B/gqw== dependencies: devlop "^1.0.0" @@ -5930,7 +5963,7 @@ micromark-extension-gfm-footnote@^2.0.0: micromark-extension-gfm-strikethrough@^2.0.0: version "2.1.0" - resolved "https://registry.yarnpkg.com/micromark-extension-gfm-strikethrough/-/micromark-extension-gfm-strikethrough-2.1.0.tgz#86106df8b3a692b5f6a92280d3879be6be46d923" + resolved "https://registry.npmjs.org/micromark-extension-gfm-strikethrough/-/micromark-extension-gfm-strikethrough-2.1.0.tgz" integrity sha512-ADVjpOOkjz1hhkZLlBiYA9cR2Anf8F4HqZUO6e5eDcPQd0Txw5fxLzzxnEkSkfnD0wziSGiv7sYhk/ktvbf1uw== dependencies: devlop "^1.0.0" @@ -5942,7 +5975,7 @@ micromark-extension-gfm-strikethrough@^2.0.0: micromark-extension-gfm-table@^2.0.0: version "2.1.1" - 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resolved "https://registry.yarnpkg.com/micromark-extension-gfm-task-list-item/-/micromark-extension-gfm-task-list-item-2.1.0.tgz#bcc34d805639829990ec175c3eea12bb5b781f2c" + resolved "https://registry.npmjs.org/micromark-extension-gfm-task-list-item/-/micromark-extension-gfm-task-list-item-2.1.0.tgz" integrity sha512-qIBZhqxqI6fjLDYFTBIa4eivDMnP+OZqsNwmQ3xNLE4Cxwc+zfQEfbs6tzAo2Hjq+bh6q5F+Z8/cksrLFYWQQw== dependencies: devlop "^1.0.0" @@ -5971,7 +6004,7 @@ micromark-extension-gfm-task-list-item@^2.0.0: micromark-extension-gfm@^3.0.0: version "3.0.0" - resolved "https://registry.yarnpkg.com/micromark-extension-gfm/-/micromark-extension-gfm-3.0.0.tgz#3e13376ab95dd7a5cfd0e29560dfe999657b3c5b" + resolved "https://registry.npmjs.org/micromark-extension-gfm/-/micromark-extension-gfm-3.0.0.tgz" integrity sha512-vsKArQsicm7t0z2GugkCKtZehqUm31oeGBV/KVSorWSy8ZlNAv7ytjFhvaryUiCUJYqs+NoE6AFhpQvBTM6Q4w== dependencies: micromark-extension-gfm-autolink-literal "^2.0.0" @@ -5985,7 +6018,7 @@ micromark-extension-gfm@^3.0.0: micromark-extension-mdx-expression@^3.0.0: version "3.0.1" - resolved "https://registry.yarnpkg.com/micromark-extension-mdx-expression/-/micromark-extension-mdx-expression-3.0.1.tgz#43d058d999532fb3041195a3c3c05c46fa84543b" + resolved "https://registry.npmjs.org/micromark-extension-mdx-expression/-/micromark-extension-mdx-expression-3.0.1.tgz" integrity sha512-dD/ADLJ1AeMvSAKBwO22zG22N4ybhe7kFIZ3LsDI0GlsNr2A3KYxb0LdC1u5rj4Nw+CHKY0RVdnHX8vj8ejm4Q== dependencies: "@types/estree" "^1.0.0" @@ -5999,7 +6032,7 @@ micromark-extension-mdx-expression@^3.0.0: micromark-extension-mdx-jsx@^3.0.0: version "3.0.2" - resolved "https://registry.yarnpkg.com/micromark-extension-mdx-jsx/-/micromark-extension-mdx-jsx-3.0.2.tgz#ffc98bdb649798902fa9fc5689f67f9c1c902044" + resolved "https://registry.npmjs.org/micromark-extension-mdx-jsx/-/micromark-extension-mdx-jsx-3.0.2.tgz" integrity sha512-e5+q1DjMh62LZAJOnDraSSbDMvGJ8x3cbjygy2qFEi7HCeUT4BDKCvMozPozcD6WmOt6sVvYDNBKhFSz3kjOVQ== dependencies: "@types/estree" "^1.0.0" @@ -6015,14 +6048,14 @@ micromark-extension-mdx-jsx@^3.0.0: micromark-extension-mdx-md@^2.0.0: version "2.0.0" - resolved "https://registry.yarnpkg.com/micromark-extension-mdx-md/-/micromark-extension-mdx-md-2.0.0.tgz#1d252881ea35d74698423ab44917e1f5b197b92d" + resolved "https://registry.npmjs.org/micromark-extension-mdx-md/-/micromark-extension-mdx-md-2.0.0.tgz" integrity sha512-EpAiszsB3blw4Rpba7xTOUptcFeBFi+6PY8VnJ2hhimH+vCQDirWgsMpz7w1XcZE7LVrSAUGb9VJpG9ghlYvYQ== dependencies: micromark-util-types "^2.0.0" micromark-extension-mdxjs-esm@^3.0.0: version "3.0.0" - resolved "https://registry.yarnpkg.com/micromark-extension-mdxjs-esm/-/micromark-extension-mdxjs-esm-3.0.0.tgz#de21b2b045fd2059bd00d36746081de38390d54a" + resolved "https://registry.npmjs.org/micromark-extension-mdxjs-esm/-/micromark-extension-mdxjs-esm-3.0.0.tgz" integrity sha512-DJFl4ZqkErRpq/dAPyeWp15tGrcrrJho1hKK5uBS70BCtfrIFg81sqcTVu3Ta+KD1Tk5vAtBNElWxtAa+m8K9A== dependencies: "@types/estree" "^1.0.0" @@ -6037,7 +6070,7 @@ micromark-extension-mdxjs-esm@^3.0.0: micromark-extension-mdxjs@^3.0.0: version "3.0.0" - resolved "https://registry.yarnpkg.com/micromark-extension-mdxjs/-/micromark-extension-mdxjs-3.0.0.tgz#b5a2e0ed449288f3f6f6c544358159557549de18" + resolved "https://registry.npmjs.org/micromark-extension-mdxjs/-/micromark-extension-mdxjs-3.0.0.tgz" integrity sha512-A873fJfhnJ2siZyUrJ31l34Uqwy4xIFmvPY1oj+Ean5PHcPBYzEsvqvWGaWcfEIr11O5Dlw3p2y0tZWpKHDejQ== dependencies: acorn "^8.0.0" @@ -6051,7 +6084,7 @@ micromark-extension-mdxjs@^3.0.0: micromark-factory-destination@^2.0.0: version "2.0.1" - resolved "https://registry.yarnpkg.com/micromark-factory-destination/-/micromark-factory-destination-2.0.1.tgz#8fef8e0f7081f0474fbdd92deb50c990a0264639" + resolved "https://registry.npmjs.org/micromark-factory-destination/-/micromark-factory-destination-2.0.1.tgz" integrity sha512-Xe6rDdJlkmbFRExpTOmRj9N3MaWmbAgdpSrBQvCFqhezUn4AHqJHbaEnfbVYYiexVSs//tqOdY/DxhjdCiJnIA== dependencies: micromark-util-character "^2.0.0" @@ -6060,7 +6093,7 @@ micromark-factory-destination@^2.0.0: micromark-factory-label@^2.0.0: version "2.0.1" - resolved "https://registry.yarnpkg.com/micromark-factory-label/-/micromark-factory-label-2.0.1.tgz#5267efa97f1e5254efc7f20b459a38cb21058ba1" + resolved "https://registry.npmjs.org/micromark-factory-label/-/micromark-factory-label-2.0.1.tgz" integrity sha512-VFMekyQExqIW7xIChcXn4ok29YE3rnuyveW3wZQWWqF4Nv9Wk5rgJ99KzPvHjkmPXF93FXIbBp6YdW3t71/7Vg== dependencies: devlop "^1.0.0" @@ -6070,7 +6103,7 @@ micromark-factory-label@^2.0.0: micromark-factory-mdx-expression@^2.0.0: version "2.0.3" - resolved "https://registry.yarnpkg.com/micromark-factory-mdx-expression/-/micromark-factory-mdx-expression-2.0.3.tgz#bb09988610589c07d1c1e4425285895041b3dfa9" + resolved "https://registry.npmjs.org/micromark-factory-mdx-expression/-/micromark-factory-mdx-expression-2.0.3.tgz" integrity sha512-kQnEtA3vzucU2BkrIa8/VaSAsP+EJ3CKOvhMuJgOEGg9KDC6OAY6nSnNDVRiVNRqj7Y4SlSzcStaH/5jge8JdQ== dependencies: "@types/estree" "^1.0.0" @@ -6085,7 +6118,7 @@ micromark-factory-mdx-expression@^2.0.0: micromark-factory-space@^1.0.0: version "1.1.0" - resolved "https://registry.yarnpkg.com/micromark-factory-space/-/micromark-factory-space-1.1.0.tgz#c8f40b0640a0150751d3345ed885a080b0d15faf" + resolved "https://registry.npmjs.org/micromark-factory-space/-/micromark-factory-space-1.1.0.tgz" integrity sha512-cRzEj7c0OL4Mw2v6nwzttyOZe8XY/Z8G0rzmWQZTBi/jjwyw/U4uqKtUORXQrR5bAZZnbTI/feRV/R7hc4jQYQ== dependencies: micromark-util-character "^1.0.0" @@ -6093,7 +6126,7 @@ micromark-factory-space@^1.0.0: micromark-factory-space@^2.0.0: version "2.0.1" - resolved "https://registry.yarnpkg.com/micromark-factory-space/-/micromark-factory-space-2.0.1.tgz#36d0212e962b2b3121f8525fc7a3c7c029f334fc" + resolved "https://registry.npmjs.org/micromark-factory-space/-/micromark-factory-space-2.0.1.tgz" integrity sha512-zRkxjtBxxLd2Sc0d+fbnEunsTj46SWXgXciZmHq0kDYGnck/ZSGj9/wULTV95uoeYiK5hRXP2mJ98Uo4cq/LQg== dependencies: micromark-util-character "^2.0.0" @@ -6101,7 +6134,7 @@ micromark-factory-space@^2.0.0: micromark-factory-title@^2.0.0: version "2.0.1" - resolved "https://registry.yarnpkg.com/micromark-factory-title/-/micromark-factory-title-2.0.1.tgz#237e4aa5d58a95863f01032d9ee9b090f1de6e94" + resolved "https://registry.npmjs.org/micromark-factory-title/-/micromark-factory-title-2.0.1.tgz" integrity sha512-5bZ+3CjhAd9eChYTHsjy6TGxpOFSKgKKJPJxr293jTbfry2KDoWkhBb6TcPVB4NmzaPhMs1Frm9AZH7OD4Cjzw== dependencies: micromark-factory-space "^2.0.0" @@ -6111,7 +6144,7 @@ micromark-factory-title@^2.0.0: micromark-factory-whitespace@^2.0.0: version "2.0.1" - resolved "https://registry.yarnpkg.com/micromark-factory-whitespace/-/micromark-factory-whitespace-2.0.1.tgz#06b26b2983c4d27bfcc657b33e25134d4868b0b1" + resolved "https://registry.npmjs.org/micromark-factory-whitespace/-/micromark-factory-whitespace-2.0.1.tgz" integrity sha512-Ob0nuZ3PKt/n0hORHyvoD9uZhr+Za8sFoP+OnMcnWK5lngSzALgQYKMr9RJVOWLqQYuyn6ulqGWSXdwf6F80lQ== dependencies: micromark-factory-space "^2.0.0" @@ -6121,7 +6154,7 @@ micromark-factory-whitespace@^2.0.0: micromark-util-character@^1.0.0, micromark-util-character@^1.1.0: version "1.2.0" - resolved "https://registry.yarnpkg.com/micromark-util-character/-/micromark-util-character-1.2.0.tgz#4fedaa3646db249bc58caeb000eb3549a8ca5dcc" + resolved "https://registry.npmjs.org/micromark-util-character/-/micromark-util-character-1.2.0.tgz" integrity sha512-lXraTwcX3yH/vMDaFWCQJP1uIszLVebzUa3ZHdrgxr7KEU/9mL4mVgCpGbyhvNLNlauROiNUq7WN5u7ndbY6xg== dependencies: micromark-util-symbol "^1.0.0" @@ -6129,7 +6162,7 @@ micromark-util-character@^1.0.0, micromark-util-character@^1.1.0: micromark-util-character@^2.0.0: version "2.1.1" - 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