Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
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:
# BAD: No authorization check -- any authenticated user can access any user@router.get("/users/{user_id}")asyncdefget_user(user_id: int, db: Session = Depends(get_db)):
returnawait user_repo.get(user_id)
# GOOD: Verify the requesting user owns the resource or is admin@router.get()
():
current_user. != user_id current_user.role != :
HTTPException(status_code=, detail=)
user_repo.get(user_id)
"/users/{user_id}"
async
def
get_user
user_id: int,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db),
if
id
and
"admin"
raise
403
"Forbidden"
return
await
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:
# BAD: Weak password hashingimport hashlib
password_hash = hashlib.md5(password.encode()).hexdigest()
# GOOD: Use bcrypt via passlibfrom passlib.context import CryptContext
pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
password_hash = pwd_context.hash(password)
# BAD: Secret in code
SECRET_KEY = "my-super-secret-key-123"# GOOD: Secret from environment
SECRET_KEY = os.environ["SECRET_KEY"]
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:
# BAD: SQL injection via string formatting
query = f"SELECT * FROM users WHERE email = '{email}'"
db.execute(text(query))
# GOOD: Parameterized query
db.execute(text("SELECT * FROM users WHERE email = :email"), {"email": email})
# GOOD: SQLAlchemy ORM (always parameterized)
user = db.query(User).filter(User.email == email).first()
# BAD: Command injection
subprocess.run(f"convert {filename}", shell=True)
# GOOD: Pass arguments as a list
subprocess.run(["convert", filename], shell=False)
# BAD: Code execution with user input
result = eval(user_input)
# GOOD: Never eval user input. Use ast.literal_eval for safe parsing.
result = ast.literal_eval(user_input) # Only for literal structures
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:
# BAD: Wide-open CORS
app.add_middleware(CORSMiddleware, allow_origins=["*"])
# GOOD: Explicit allowed origins
app.add_middleware(
CORSMiddleware,
allow_origins=["https://app.example.com"],
allow_methods=["GET", "POST", "PUT", "DELETE"],
allow_headers=["Authorization", "Content-Type"],
)
# BAD: Debug mode in production
app = FastAPI(debug=True)
# GOOD: Debug only in development
app = FastAPI(debug=settings.DEBUG) # DEBUG=False in production
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
// BAD: XSS via dangerouslySetInnerHTML
<div dangerouslySetInnerHTML={{ __html: userBio }} />
// GOOD: Sanitize first, or use text contentimportDOMPurifyfrom"dompurify";
<divdangerouslySetInnerHTML={{__html:DOMPurify.sanitize(userBio) }} />// BETTER: Use text content when HTML is not needed<p>{userBio}</p>// BAD: javascript: URL<ahref={userLink}>Click</a>// userLink could be "javascript:alert(1)"// GOOD: Validate protocolconst safeHref = /^https?:\/\//.test(userLink) ? userLink : "#";
<ahref={safeHref}>Click</a>
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:
## Security Finding: [Title]**Severity:** Critical | High | Medium | Low | Info
**Category:** OWASP A01-A10 or custom category
**File:** path/to/file.py:42
**CWE:** CWE-89 (if applicable)
### Description
Brief description of the vulnerability and its impact.
### Vulnerable Code```python
# The problematic code
vulnerable_function(user_input)
Recommended Fix
# The secure alternative
safe_function(sanitize(user_input))
Impact
What an attacker could achieve by exploiting this vulnerability.
References
Link to relevant OWASP page
Link to relevant CWE entry
### 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):**
```bash
# Python dependencies
pip-audit --requirement requirements.txt --output json > dep-audit.json
# npm dependencies
npm audit --json > npm-audit.json
Examples
Example Review Comment (Critical)
SECURITY: SQL Injection (Critical, OWASP A03)
File: app/repositories/user_repository.py:47
query = f"SELECT * FROM users WHERE name LIKE '%{search_term}%'"
This constructs a raw SQL query with string interpolation, allowing SQL injection.
An attacker could input '; DROP TABLE users; -- to destroy data.
