🔐 Cyhber Deploy

Systematic DevSecOps Analysis for Claude Code — 5-layer security review with standardized severity-tagged alerts

🚀 Quick Start • 📖 Documentation • 🧪 Test Results • 🐛 Report Bug

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✨ What's New in v2.0

Complete rebuild with TDD methodology:

• ✅ Systematic 5-layer review enforced (no ad-hoc analysis)
• ✅ Standardized severity-tagged alerts (CRITICO/ALTO/MEDIO/BAJO)
• ✅ Proactive scope expansion beyond user request
• ✅ Token-efficient (~450 words, 60% reduction)
• ✅ Pressure-tested with time/authority/exhaustion scenarios
• ✅ Full test documentation included

Observed in manual evaluation: 6-8 categorized alerts vs 1-2 ad-hoc findings on the same test scenarios. These are qualitative comparisons, not automated benchmarks.

See FINAL-REPORT.md for the full evaluation notes.

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🚀 Features

Systematic 5-Layer Analysis

Every security review follows this structured methodology:

1. Code Validation — Input validation, injection (SQL/XSS/Command), auth/authz, error handling
2. Dependencies — CVEs, outdated packages, unmaintained libraries, transitive dependencies
3. Secrets & PII — Hardcoded API keys, tokens, certificates, exposed personal data
4. CI/CD Pipeline — Branch restrictions, secret exposure, security gates, rollback plans
5. Infrastructure — Network exposure, IAM/RBAC permissions, encryption, security groups

No layer skipped — even "frontend-only" code triggers full review.

Standardized Alert Format

Every finding includes:

Campo	Valor
Severidad	🔴 CRITICO | 🟠 ALTO | 🟡 MEDIO | 🟢 BAJO
ID	CD-SEC-XXX (sequential)
Componente	file.js:line or resource name
Descripción	What + why it's a risk
Evidencia	Code snippet or config excerpt
Remediación	Specific fix steps

Risk Assessment Output

┌─────────────────────────────────────────────┐
│ 🔒 ESTADO DE SEGURIDAD                      │
├─────────────────────────────────────────────┤
│ Nivel de riesgo:  🔴 CRITICO                │
│ Alertas totales:  8                         │
│   • Críticas:     2                         │
│   • Altas:        3                         │
│   • Medias:       2                         │
│   • Bajas:        1                         │
├─────────────────────────────────────────────┤
│ ⚠️  RECOMENDACIÓN:                          │
│ BLOQUEAR despliegue hasta resolver          │
│ hallazgos críticos y altos.                 │
└─────────────────────────────────────────────┘

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📦 Installation

Claude Code CLI

# Install from local directory
git clone https://github.com/DevCop95/cyhber-deploy.git
cd cyhber-deploy
cp -r skills/cyhber-deploy ~/.claude/skills/

Verify Installation

# Check skill is loaded
claude # Start Claude Code session
# Skill auto-triggers on: deploy, CI/CD, Terraform, auth, secrets, injection

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🎯 Usage

Auto-Trigger Keywords

Skill activates when you mention:

• Deploy: staging, production, release
• CI/CD: GitHub Actions, GitLab CI, Jenkins, CircleCI
• IaC: Terraform, Kubernetes, Docker, Helm
• Cloud: AWS, GCP, Azure
• Security: auth, secrets, injection, SQL, XSS
• Review: "security review", "check this code"

Manual Invocation

@cyhber-deploy review this for production

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📸 Examples

Example 1: SQL Injection Detection

Input:

app.post('/login', (req, res) => {
  db.query(`SELECT * FROM users WHERE email='${req.body.email}'`);
});

Output:

Campo	Valor
Severidad	🔴 CRITICO
ID	CD-SEC-001
Componente	api/auth.js:2
Descripción	SQL injection - user-controlled email concatenated into query
Evidencia	db.query(`SELECT * FROM users WHERE email='${req.body.email}'`)
Remediación	Use parameterized query: db.query('SELECT * FROM users WHERE email = ?', [req.body.email])

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Example 2: CI/CD Secret Exposure

Input:

# .github/workflows/deploy.yml
- run: |
    echo "API_KEY=${{ secrets.API_KEY }}" >> .env
    cat .env

Output:

Campo	Valor
Severidad	🔴 CRITICO
ID	CD-SEC-002
Componente	.github/workflows/deploy.yml:3
Descripción	API key exposed in workflow logs via cat .env
Evidencia	cat .env prints secrets to logs accessible to all repo users
Remediación	Remove cat .env. Pass secrets via env vars: env: API_KEY: ${{ secrets.API_KEY }}

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Example 3: Infrastructure Overexposure

Input:

resource "aws_security_group" "db" {
  ingress {
    cidr_blocks = ["0.0.0.0/0"]
    from_port   = 5432
    to_port     = 5432
  }
}

Output:

Campo	Valor
Severidad	🔴 CRITICO
ID	CD-SEC-003
Componente	terraform/main.tf:3
Descripción	Database exposed to entire internet via overly permissive security group
Evidencia	cidr_blocks = ["0.0.0.0/0"] allows connections from any IP
Remediación	Restrict to application subnet: cidr_blocks = ["10.0.1.0/24"] or use VPC peering

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🖥️ Terminal Report (visual layer)

A zero-dependency Python renderer turns findings into colored alert cards plus a final ESTADO DE SEGURIDAD panel — a visual recap of the scan, right in your terminal.

# See it instantly with the bundled demo
python tools/cyhber_report.py --demo

# Render your own findings (see schema in tools/findings.example.json)
python tools/cyhber_report.py findings.json

# Pipe from another tool
cat findings.json | python tools/cyhber_report.py

Preview:

  ┌───────────────────────────────────────────────────────┐
  │ 🔒 ESTADO DE SEGURIDAD                                  │
  │ Objetivo: examples/vulnerable-api/server.js            │
  ├───────────────────────────────────────────────────────┤
  │ Nivel de riesgo:  🔴 CRITICO                            │
  │ Alertas totales:  8                                     │
  │   • CRITICO  3                                          │
  │   • ALTO     3                                          │
  │   • MEDIO    1                                          │
  │   • BAJO     1                                          │
  ├───────────────────────────────────────────────────────┤
  │ ⚠️  RECOMENDACIÓN:                                      │
  │ BLOQUEAR despliegue — resolver críticos/altos           │
  └───────────────────────────────────────────────────────┘

• Pure stdlib (no pip install), works on Windows / macOS / Linux.
• Auto-detects color; honors NO_COLOR / FORCE_COLOR.
• Exit code 1 when the run should block (any 🔴 or ≥3 🟠), 0 otherwise — drop it straight into a CI gate.

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🧪 Testing & Quality

TDD Methodology

Skill built following complete RED-GREEN-REFACTOR cycle:

• RED Phase: Baseline testing without skill (3 pressure scenarios)
• GREEN Phase: Skill enforcement verification (systematic 5-layer review)
• REFACTOR Phase: Edge case testing (frontend-only code)

Test Results

Metric	Baseline (No Skill)	With Skill
Issues found	1-2	6-8
Structure	Ad-hoc	5-layer systematic
Output format	Freeform	Severity tables
Scope	Limited	Proactive expansion

Numbers come from manual evaluation on the bundled test scenarios, not from an automated benchmark suite. Treat them as directional, not guaranteed.

Full documentation: tests/FINAL-REPORT.md

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📚 Documentation

• SKILL.md — Complete skill specification
• secret-patterns.md — 40+ secret detection patterns
• FINAL-REPORT.md — TDD testing documentation
• Examples — Vulnerable and secure code samples
• tools/cyhber_report.py — Terminal report renderer (visual layer)

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🛠 Configuration

Secret Patterns

Built-in detection for:

• AWS keys (AKIA...), Azure, GCP service accounts
• GitHub tokens (ghp_, gho_, glpat-)
• Private keys (RSA, EC, OpenSSH, PGP)
• Database connection strings
• JWT tokens
• Slack/Discord webhooks
• Payment provider keys (Stripe, PayPal, Square)

See secret-patterns.md for complete list.

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🤝 Contributing

Contributions welcome! For major changes:

1. Fork repo
2. Create feature branch (git checkout -b feature/improvement)
3. Follow TDD methodology (see tests/ for examples)
4. Commit with conventional commits
5. Push and open PR

Reporting Security Issues

DO NOT open public issues for vulnerabilities.

Email: yared.henriquezb@gmail.com

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📋 Roadmap

• SARIF output format for CI/CD integration
• Custom rule configuration (.cyhber-deploy.json)
• Multi-language support (Django, Flask, Spring Boot)
• GitHub Action for automated PR reviews
• VS Code extension
• Dashboard for security metrics over time

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📄 License

MIT License - see LICENSE

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🙏 Credits

Author: DevCop95

Built with guidance from:

• Claude Code Superpowers - TDD methodology for skills
• Anthropic Claude - AI platform

Inspired by:

• Semgrep - SAST scanning
• Snyk - Dependency analysis
• TruffleHog - Secret detection
• OWASP - Security standards

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📞 Support

• 🐛 Issues
• 💬 Discussions
• 📧 Email: yared.henriquezb@gmail.com
• 🐦 X/Twitter: @Devcop101

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⚠️ Disclaimer

Cyhber Deploy provides static analysis and does not replace professional security audits or penetration testing. Use as complement to existing security practices.

Production-Ready • TDD-Tested • Open Source

⭐ Star this repo if it helps your security workflow!