Security-focused code review checklist and automated scanning patterns. Use when reviewing pull requests for security issues, auditing authentication/authorization code, checking for OWASP Top 10 vulnerabilities, or validating input sanitization. Covers SQL injection prevention, XSS protection, CSRF

Code Review Security When to Use Activate this skill when: Reviewing pull requests for security vulnerabilities Auditing authentication or authorization code changes Reviewing code that handles user input, file uploads, or external data Checking for OWASP Top 10 vulnerabilities in new features Validating that secrets are not committed to the repository Scanning dependencies for known vulnerabilities Reviewing API endpoints that expose sensitive data Output: Write findings to security review.md with severity, file:line, description, and recommendations. Do NOT use this skill for: Deployment infrastructure security (use docker best practices ) Incident response procedures (use incident response ) General code quality review without security focus (use pre merge checklist ) Writing implementation code (use python backend expert or react frontend expert ) Instructions OWASP Top 10 Checklist Review every PR against the OWASP Top 10 (2021 edition). Each category below includes specific checks for Python/FastAPI and React codebases. A01: Broken Access Control What to look for: Missing authorization checks on endpoints Direct object reference without ownership verification Endpoints that expose data without role based filtering Missing Depends() for auth on new routes Python/FastAPI checks: Review checklist: [ ] Every route has authentication ( Depends(get current user) ) [ ] Resource access is verified against the requesting user [ ] Admin only endpoints check role == "admin" [ ] List endpoints filter by user ownership (unless admin) [ ] No IDOR (Insecure Direct Object Reference) vulnerabilities A02: Cryptographic Failures What to look for: Passwords stored in plaintext or with weak hashing Sensitive data in logs or error messages Hardcoded secrets, API keys, or tokens Weak JWT configuration Python checks: Review checklist: [ ] Passwords hashed with bcrypt (never MD5, SHA1, or plaintext) [ ] JWT secret loaded from environment, not hardcoded [ ] Sensitive data excluded from logs (passwords, tokens, PII) [ ] HTTPS enforced for all external communication [ ] No secrets in source code (check .env.example has placeholders only) A03: Injection What to look for: Raw SQL queries with string interpolation eval() , exec() , compile() with user input subprocess calls with shell=True Template injection Python checks: Review checklist: [ ] No raw SQL with string interpolation (use ORM or parameterized queries) [ ] No eval() , exec() , or compile() with external input [ ] No subprocess.run(..., shell=True) with dynamic arguments [ ] No pickle.loads() on untrusted data [ ] All user input validated by Pydantic schemas before use A04: Insecure Design What to look for: Missing rate limiting on authentication endpoints No account lockout after failed login attempts Missing CAPTCHA on public facing forms Business logic flaws (e.g., negative amounts, self privilege escalation) Review checklist: [ ] Rate limiting on login, registration, and password reset [ ] Account lockout or exponential backoff after 5+ failed attempts [ ] Business logic validates constraints (positive amounts, valid transitions) [ ] Sensitive operations require re authentication A05: Security Misconfiguration What to look for: Debug mode enabled in production CORS configured with wildcard origins Default credentials or admin accounts Verbose error messages exposing stack traces Python/FastAPI checks: Review checklist: [ ] CORS origins are explicit (no wildcard in production) [ ] Debug mode disabled in production configuration [ ] Error responses do not expose stack traces or internal details [ ] Default admin credentials are changed or removed [ ] Security headers set (X Content Type Options, X Frame Options, etc.) A06: Vulnerable and Outdated Components Review checklist: [ ] No known CVEs in Python dependencies ( pip audit or safety check ) [ ] No known CVEs in npm dependencies ( npm audit ) [ ] Dependencies pinned to specific versions in lock files [ ] No deprecated packages still in use A07: Identification and Authentication Failures What to look for: Weak password policies Session tokens that do not expire Missing multi factor authentication for admin actions JWT tokens without expiration Python checks: Review checklist: [ ] JWT tokens have expiration ( exp claim) [ ] Refresh tokens are stored securely and can be revoked [ ] Password policy enforces minimum length (12+) and complexity [ ] Session invalidation on password change or logout [ ] No user enumeration via login error messages A08: Software and Data Integrity Failures Review checklist: [ ] CI/CD pipeline validates artifact integrity [ ] No unsigned or unverified packages [ ] Deserialization of untrusted data uses safe methods (no pickle.loads ) [ ] Database migrations are reviewed before execution A09: Security Logging and Monitoring Failures Review checklist: [ ] Authentication events are logged (login, logout, failed attempts) [ ] Authorization failures are logged with context [ ] Sensitive data is NOT included in logs (passwords, tokens, PII) [ ] Log entries include timestamp, user ID, IP address, action [ ] Alerting configured for suspicious patterns (brute force, unusual access) A10: Server Side Request Forgery (SSRF) What to look for: User supplied URLs used in server side requests Redirect endpoints that accept arbitrary URLs Python checks: Review checklist: [ ] No server side requests to user controlled URLs without validation [ ] URL allowlists used for external integrations [ ] Internal service URLs not exposed in error messages Python Specific Security Checks Beyond OWASP, review Python code for these patterns: Pattern Risk Fix eval(user input) Remote code execution Remove or use ast.literal eval pickle.loads(data) Arbitrary code execution Use JSON or msgpack subprocess.run(cmd, shell=True) Command injection Pass args as list, shell=False yaml.load(data) Code execution Use yaml.safe load(data) os.system(cmd) Command injection Use subprocess.run([...]) Raw SQL strings SQL injection Use ORM or parameterized queries hashlib.md5(password) Weak hashing Use bcrypt via passlib jwt.decode(token, options={"verify signature": False}) Auth bypass Always verify signature open(user path) Path traversal Validate path, use pathlib.resolve() tempfile.mktemp() Race condition Use tempfile.mkstemp() React Specific Security Checks Pattern Risk Fix dangerouslySetInnerHTML XSS Use text content or sanitize with DOMPurify javascript: in href XSS Validate URLs, allow only https: window.location = userInput Open redirect Validate against allowlist Storing tokens in localStorage Token theft via XSS Use httpOnly cookies Inline event handlers from data XSS Use React event handlers eval() or Function() Code execution Remove entirely Rendering user HTML XSS Use a sanitization library React code review: Severity Classification Classify each finding by severity for prioritization: Severity Description Examples SLA Critical Exploitable remotely, no auth needed, data breach SQL injection, RCE, auth bypass Block merge, fix immediately High Exploitable with auth, privilege escalation IDOR, broken access control, XSS (stored) Block merge, fix before release Medium Requires specific conditions to exploit CSRF, XSS (reflected), open redirect Fix within sprint Low Defense in depth, informational Missing headers, verbose errors Fix when convenient Info Best practice recommendations Dependency updates, code style Track in backlog Finding Report Format When reporting security findings, use this format for consistency: python The problematic code vulnerable function(user input) python The secure alternative safe function(sanitize(user input)) Automated Scanning Use scripts/security scan.py to perform AST based scanning for common vulnerability patterns in Python code. The script scans for: eval() / exec() / compile() calls subprocess with shell=True pickle.loads() on potentially untrusted data Raw SQL string construction yaml.load() without Loader=SafeLoader Hardcoded secret patterns (API keys, passwords) Weak hash functions (MD5, SHA1 for passwords) Run: python scripts/security scan.py path ./app output dir ./security results Dependency scanning (run separately): Examples Example Review Comment (Critical) SECURITY: SQL Injection (Critical, OWASP A03) File: app/repositories/user repository.py:47 This constructs a raw SQL query with string interpolation, allowing SQL injection. An attacker could input '; DROP TABLE users; to destroy data. Fix: Use SQLAlchemy ORM filtering: Example Review Comment (Medium) SECURITY: Missing Rate Limiting (Medium, OWASP A04) File: app/routes/auth.py:12 The /auth/login endpoint has no rate limiting. An attacker could perform brute force password attacks at unlimited speed. Fix: Add rate limiting middleware: Output File Write security findings to security review.md :

code-review-security