Security Penetration Testing

Hands-on offensive security testing skill for finding vulnerabilities before attackers do. This is NOT compliance checking (see senior-secops) or security policy writing (see senior-security) — this is about systematic vulnerability discovery through authorized testing.

Table of Contents

• Overview
• OWASP Top 10 Systematic Audit
• Static Analysis
• Dependency Vulnerability Scanning
• Secret Scanning
• API Security Testing
• Web Vulnerability Testing
• Infrastructure Security
• Pen Test Report Generation
• Responsible Disclosure Workflow
• Workflows
• Anti-Patterns
• Cross-References

Overview

What This Skill Does

This skill provides the methodology, checklists, and automation for offensive security testing — actively probing systems to discover exploitable vulnerabilities. It covers web applications, APIs, infrastructure, and supply chain security.

Distinction from Other Security Skills

Prerequisites

All testing described here assumes written authorization from the system owner. Unauthorized testing is illegal under the CFAA and equivalent laws worldwide. Always obtain a signed scope-of-work or rules-of-engagement document before starting.

OWASP Top 10 Systematic Audit

Use the vulnerability scanner tool for automated checklist generation:

# Generate OWASP checklist for a web application
python scripts/vulnerability_scanner.py --target web --scope full

# Quick API-focused scan
python scripts/vulnerability_scanner.py --target api --scope quick --json

Quick Reference

# Audit dependencies
python scripts/dependency_auditor.py --file package.json --severity high
python scripts/dependency_auditor.py --file requirements.txt --json

See owasp_top_10_checklist.md for detailed test procedures, code patterns to detect, remediation steps, and CVSS scoring guidance for each category.

Static Analysis

Recommended tools: CodeQL (custom queries for project-specific patterns), Semgrep (rule-based scanning with auto-fix), ESLint security plugins (eslint-plugin-security, eslint-plugin-no-unsanitized).

Key patterns to detect: SQL injection via string concatenation, hardcoded JWT secrets, unsafe YAML/pickle deserialization, missing security middleware (e.g., Express without Helmet).

See attack_patterns.md for code patterns and detection payloads across injection types.

Dependency Vulnerability Scanning

Ecosystem commands: npm audit, pip audit, govulncheck ./..., bundle audit check

CVE Triage Workflow:

1. Collect — Run ecosystem audit tools, aggregate findings
2. Deduplicate — Group by CVE ID across direct and transitive deps
3. Prioritize — Critical + exploitable + reachable = fix immediately
4. Remediate — Upgrade, patch, or mitigate with compensating controls
5. Verify — Rerun audit to confirm fix, update lock files

python scripts/dependency_auditor.py --file package.json --severity critical --json

Secret Scanning

Tools: TruffleHog (git history + filesystem), Gitleaks (regex-based with custom rules).

# Scan git history for verified secrets
trufflehog git file://. --only-verified --json

# Scan filesystem
trufflehog filesystem . --json

Integration points: Pre-commit hooks (gitleaks, trufflehog), CI/CD gates (GitHub Actions with trufflesecurity/trufflehog@main). Configure .gitleaks.toml for custom rules (AWS keys, API keys, private key headers) and allowlists for test fixtures.

API Security Testing

Authentication Bypass

• JWT manipulation: Change alg to none, RS256-to-HS256 confusion, claim modification (role: "admin", exp: 9999999999)
• Session fixation: Check if session ID changes after authentication

Authorization Flaws

• IDOR/BOLA: Change resource IDs in every endpoint — test read, update, delete across users
• BFLA: Regular user tries admin endpoints (expect 403)
• Mass assignment: Add privileged fields (role, is_admin) to update requests

Rate Limiting & GraphQL

• Rate limiting: Rapid-fire requests to auth endpoints; expect 429 after threshold
• GraphQL: Test introspection (should be disabled in prod), query depth attacks, batch mutations bypassing rate limits

See attack_patterns.md for complete JWT manipulation payloads, IDOR testing methodology, BFLA endpoint lists, GraphQL introspection/depth/batch attack patterns, and rate limiting bypass techniques.

Web Vulnerability Testing

See attack_patterns.md for complete test payloads (XSS filter bypasses, context-specific XSS, SQL injection per database engine, SSRF bypass techniques, and DOM-based XSS source/sink pairs).

Infrastructure Security

Key checks:

• Cloud storage: S3 bucket public access (aws s3 ls s3://bucket --no-sign-request), bucket policies, ACLs
• HTTP security headers: HSTS, CSP (no unsafe-inline/unsafe-eval), X-Content-Type-Options, X-Frame-Options, Referrer-Policy
• TLS configuration: nmap --script ssl-enum-ciphers -p 443 target.com or testssl.sh — reject TLS 1.0/1.1, RC4, 3DES, export-grade ciphers
• Port scanning: nmap -sV target.com — flag dangerous open ports (FTP/21, Telnet/23, Redis/6379, MongoDB/27017)

Pen Test Report Generation

Generate professional reports from structured findings:

# Generate markdown report from findings JSON
python scripts/pentest_report_generator.py --findings findings.json --format md --output report.md

# Generate JSON report
python scripts/pentest_report_generator.py --findings findings.json --format json --output report.json

Findings JSON Format

[
  {
    "title": "SQL Injection in Login Endpoint",
    "severity": "critical",
    "cvss_score": 9.8,
    "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
    "category": "A03:2021 - Injection",
    "description": "The /api/login endpoint is vulnerable to SQL injection via the email parameter.",
    "evidence": "Request: POST /api/login {\"email\": \"' OR 1=1--\", \"password\": \"x\"}\nResponse: 200 OK with admin session token",
    "impact": "Full database access, authentication bypass, potential remote code execution",
    "remediation": "Use parameterized queries. Replace string concatenation with prepared statements.",
    "references": ["https://cwe.mitre.org/data/definitions/89.html"]
  }
]

Report Structure

1. Executive Summary: Business impact, overall risk level, top 3 findings
2. Scope: What was tested, what was excluded, testing dates
3. Methodology: Tools used, testing approach (black/gray/white box)
4. Findings Table: Sorted by severity with CVSS scores
5. Detailed Findings: Each with description, evidence, impact, remediation
6. Remediation Priority Matrix: Effort vs. impact for each fix
7. Appendix: Raw tool output, full payload lists

Responsible Disclosure Workflow

Responsible disclosure is mandatory for any vulnerability found during authorized testing. Standard timeline: report on day 1, follow up at day 7, status update at day 30, public disclosure at day 90.

Key principles: Never exploit beyond proof of concept, encrypt all communications, do not access real user data, document everything with timestamps.

See responsible_disclosure.md for full disclosure timelines (standard 90-day, accelerated 30-day, extended 120-day), communication templates, legal considerations, bug bounty program integration, and CVE request process.

Workflows

Workflow 1: Quick Security Check (15 Minutes)

For pre-merge reviews or quick health checks:

# 1. Generate OWASP checklist
python scripts/vulnerability_scanner.py --target web --scope quick

# 2. Scan dependencies
python scripts/dependency_auditor.py --file package.json --severity high

# 3. Check for secrets in recent commits
# (Use gitleaks or trufflehog as described in Secret Scanning section)

# 4. Review HTTP security headers
curl -sI https://target.com | grep -iE "(strict-transport|content-security|x-frame|x-content-type)"

Decision: If any critical or high findings, block the merge.

Workflow 2: Full Penetration Test (Multi-Day Assessment)

Day 1 — Reconnaissance:

1. Map the attack surface: endpoints, authentication flows, third-party integrations
2. Run automated OWASP checklist (full scope)
3. Run dependency audit across all manifests
4. Run secret scan on full git history

Day 2 — Manual Testing:

1. Test authentication and authorization (IDOR, BOLA, BFLA)
2. Test injection points (SQLi, XSS, SSRF, command injection)
3. Test business logic flaws
4. Test API-specific vulnerabilities (GraphQL, rate limiting, mass assignment)

Day 3 — Infrastructure and Reporting:

1. Check cloud storage permissions
2. Verify TLS configuration and security headers
3. Port scan for unnecessary services
4. Compile findings into structured JSON
5. Generate pen test report

# Generate final report
python scripts/pentest_report_generator.py --findings findings.json --format md --output pentest-report.md

Workflow 3: CI/CD Security Gate

Automated security checks on every PR: secret scanning (TruffleHog), dependency audit (npm audit, pip audit), SAST (Semgrep with p/security-audit, p/owasp-top-ten), and security headers check on staging.

Gate Policy: Block merge on critical/high findings. Warn on medium. Log low/info.

Anti-Patterns

1. Testing in production without authorization — Always get written permission and use staging/test environments when possible
2. Ignoring low-severity findings — Low findings compound; a chain of lows can become a critical exploit path
3. Skipping responsible disclosure — Every vulnerability found must be reported through proper channels
4. Relying solely on automated tools — Tools miss business logic flaws, chained exploits, and novel attack vectors
5. Testing without a defined scope — Scope creep leads to legal liability; document what is and isn't in scope
6. Reporting without remediation guidance — Every finding must include actionable remediation steps
7. Storing evidence insecurely — Pen test evidence (screenshots, payloads, tokens) is sensitive; encrypt and restrict access
8. One-time testing — Security testing must be continuous; integrate into CI/CD and schedule periodic assessments

Cross-References