OWASP Security Best Practices Skill

Apply these security standards when writing or reviewing code.

Quick Reference: OWASP Top 10:2025

Security Code Review Checklist

When reviewing code, check for these issues:

Input Handling

• All user input validated server-side
• Using parameterized queries (not string concatenation)
• Input length limits enforced
• Allowlist validation preferred over denylist

Authentication & Sessions

• Passwords hashed with Argon2/bcrypt (not MD5/SHA1)
• Session tokens have sufficient entropy (128+ bits)
• Sessions invalidated on logout
• MFA available for sensitive operations

Access Control

• Authorization checked on every request
• Using object references user cannot manipulate
• Deny by default policy
• Privilege escalation paths reviewed

Data Protection

• Sensitive data encrypted at rest
• TLS for all data in transit
• No sensitive data in URLs/logs
• Secrets in environment/vault (not code)

Error Handling

• No stack traces exposed to users
• Fail-closed on errors (deny, not allow)
• All exceptions logged with context
• Consistent error responses (no enumeration)

Secure Code Patterns

SQL Injection Prevention

# UNSAFE
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")

# SAFE
cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))

Command Injection Prevention

# UNSAFE
os.system(f"convert {filename} output.png")

# SAFE
subprocess.run(["convert", filename, "output.png"], shell=False)

Password Storage

# UNSAFE
hashlib.md5(password.encode()).hexdigest()

# SAFE
from argon2 import PasswordHasher
PasswordHasher().hash(password)

Access Control

# UNSAFE - No authorization check
@app.route('/api/user/<user_id>')
def get_user(user_id):
    return db.get_user(user_id)

# SAFE - Authorization enforced
@app.route('/api/user/<user_id>')
@login_required
def get_user(user_id):
    if current_user.id != user_id and not current_user.is_admin:
        abort(403)
    return db.get_user(user_id)

Error Handling

# UNSAFE - Exposes internals
@app.errorhandler(Exception)
def handle_error(e):
    return str(e), 500

# SAFE - Fail-closed, log context
@app.errorhandler(Exception)
def handle_error(e):
    error_id = uuid.uuid4()
    logger.exception(f"Error {error_id}: {e}")
    return {"error": "An error occurred", "id": str(error_id)}, 500

Fail-Closed Pattern

# UNSAFE - Fail-open
def check_permission(user, resource):
    try:
        return auth_service.check(user, resource)
    except Exception:
        return True  # DANGEROUS!

# SAFE - Fail-closed
def check_permission(user, resource):
    try:
        return auth_service.check(user, resource)
    except Exception as e:
        logger.error(f"Auth check failed: {e}")
        return False  # Deny on error

Agentic AI Security (OWASP 2026)

When building or reviewing AI agent systems, check for:

Agent Security Checklist

• All agent inputs sanitized and validated
• Tools operate with minimum required permissions
• Credentials are short-lived and scoped
• Third-party plugins verified and sandboxed
• Code execution happens in isolated environments
• Agent communications authenticated and encrypted
• Circuit breakers between agent components
• Human approval for sensitive operations
• Behavior monitoring for anomaly detection
• Kill switch available for agent systems

ASVS 5.0 Key Requirements

Level 1 (All Applications)

• Passwords minimum 12 characters
• Check against breached password lists
• Rate limiting on authentication
• Session tokens 128+ bits entropy
• HTTPS everywhere

Level 2 (Sensitive Data)

• All L1 requirements plus:
• MFA for sensitive operations
• Cryptographic key management
• Comprehensive security logging
• Input validation on all parameters

Level 3 (Critical Systems)

• All L1/L2 requirements plus:
• Hardware security modules for keys
• Threat modeling documentation
• Advanced monitoring and alerting
• Penetration testing validation

Language-Specific Security Quirks

Important: The examples below are illustrative starting points, not exhaustive. When reviewing code, think like a senior security researcher: consider the language's memory model, type system, standard library pitfalls, ecosystem-specific attack vectors, and historical CVE patterns. Each language has deeper quirks beyond what's listed here.

Different languages have unique security pitfalls. Here are the top 20 languages with key security considerations. Go deeper for the specific language you're working in:

JavaScript / TypeScript

Main Risks: Prototype pollution, XSS, eval injection

// UNSAFE: Prototype pollution
Object.assign(target, userInput)
// SAFE: Use null prototype or validate keys
Object.assign(Object.create(null), validated)

// UNSAFE: eval injection
eval(userCode)
// SAFE: Never use eval with user input

Watch for: eval(), innerHTML, document.write(), prototype chain manipulation, __proto__

Python

Main Risks: Pickle deserialization, format string injection, shell injection

# UNSAFE: Pickle RCE
pickle.loads(user_data)
# SAFE: Use JSON or validate source
json.loads(user_data)

# UNSAFE: Format string injection
query = "SELECT * FROM users WHERE name = '%s'" % user_input
# SAFE: Parameterized
cursor.execute("SELECT * FROM users WHERE name = %s", (user_input,))

Watch for: pickle, eval(), exec(), os.system(), subprocess with shell=True

Java

Main Risks: Deserialization RCE, XXE, JNDI injection

// UNSAFE: Arbitrary deserialization
ObjectInputStream ois = new ObjectInputStream(userStream);
Object obj = ois.readObject();

// SAFE: Use