OWASP Top 10 for Vibe Coding: A Practical Checklist

If you're building apps rapidly with AI coding tools — often called "vibe coding" — you might be shipping security holes just as fast. The OWASP Top 10 is the standard for web app security risks, and it applies directly to vibe-coded projects. Here's a quick checklist to audit your AI-generated code against the most common vulnerabilities.

What Is Vibe Coding and Why OWASP Matters?

Vibe coding means using AI assistants like Cursor, Bolt.new, v0, or Lovable to generate entire features or apps with minimal manual oversight. The problem? AI models are trained on public code, which includes plenty of insecure examples. Without a security review, your app could inherit SQL injections, broken authentication, or exposed secrets. This OWASP Top 10 checklist for vibe coding will help you catch those issues before they become breaches.

The OWASP Top 10 Checklist for Vibe-Coded Apps

1. Broken Access Control

What to check: Does your AI-generated code enforce proper permissions? Look for endpoints that don't verify user roles.

Example: A Bolt.new-generated API route that lets any user delete any record:

@app.route('/delete_user/<id>')
def delete_user(id):
    db.execute(f"DELETE FROM users WHERE id = {id}")
    return "Deleted"

Fix: Add authorization checks. Use middleware or decorators to ensure only admins can delete.

@app.route('/delete_user/<id>')
@admin_required
def delete_user(id):
    db.execute("DELETE FROM users WHERE id = ?", (id,))
    return "Deleted"

2. Cryptographic Failures

What to check: Sensitive data like passwords, API keys, or credit card numbers should be encrypted at rest and in transit.

Example: Cursor might generate code that stores passwords in plaintext:

# Never do this
user.password = request.form['password']

Fix: Use a strong hashing algorithm like bcrypt.

from werkzeug.security import generate_password_hash
user.password = generate_password_hash(request.form['password'])

Also ensure HTTPS is enforced and secrets are not hardcoded.

3. Injection (SQL, NoSQL, Command)

What to check: AI often concatenates user input directly into queries. Look for f-strings or string interpolation in database calls.

Example: Lovable-generated code with raw SQL:

const user = await db.query(`SELECT * FROM users WHERE id = ${req.params.id}`);

Fix: Use parameterized queries or ORM methods.

const user = await db.query('SELECT * FROM users WHERE id = ?', [req.params.id]);

4. Insecure Design

What to check: Does the AI-generated architecture follow security patterns? Are rate limits, throttling, and proper error handling in place?

Example: An AI-built login endpoint with no rate limiting allows brute force attacks.

Fix: Implement rate limiting per IP and per user, and return generic error messages (e.g., "Invalid credentials" instead of "User not found").

5. Security Misconfiguration

What to check: Default settings, debug modes, and unnecessary features left enabled.

Example: A v0-generated React app with CORS set to * in production:

app.use(cors({ origin: '*' }));

Fix: Restrict origins to your actual domain and disable debug endpoints in production.

6. Vulnerable and Outdated Components

What to check: AI tools may pull in libraries with known CVEs. Run npm audit or pip audit on your dependencies.

Example: A package.json generated by Replit Agent includes an old version of lodash with a prototype pollution vulnerability.

Fix: Regularly update dependencies and use dependency scanning tools.

7. Identification and Authentication Failures

What to check: Weak password policies, session management flaws, or missing MFA.

Example: An AI-coded signup form without password complexity requirements.

Fix: Enforce minimum password length, use secure session tokens, and consider adding MFA for sensitive actions.

8. Software and Data Integrity Failures

What to check: Does your app verify the integrity of updates or third-party scripts? CI/CD pipelines should be hardened.

Example: A Cursor-generated app loads external scripts over HTTP instead of HTTPS.

Fix: Use Subresource Integrity (SRI) for external scripts and sign your releases.

9. Security Logging and Monitoring Failures

What to check: Are security events logged? Can you detect breaches?

Example: An AI-built API that swallows errors without logging.

Fix: Log authentication attempts, critical errors, and access to sensitive data. Use a centralized monitoring service.

10. Server-Side Request Forgery (SSRF)

What to check: Does your app fetch user-supplied URLs? AI often generates code that blindly fetches URLs.

Example: A Bolt.new feature that accepts a URL and downloads an image:

import requests
def fetch_image(url):
    return requests.get(url).content

Fix: Validate and whitelist allowed URLs, and restrict network access to internal services.

How to Automate This Checklist for Vibe-Coded Apps

Manually checking every AI-generated line is tedious. That's where OverMCP comes in — it scans your vibe-coded apps against the OWASP Top 10 and surfaces vulnerabilities before you ship. But even without a tool, running through this checklist after each AI session will dramatically reduce your risk.

Conclusion

Vibe coding lets you build fast, but security shouldn't be an afterthought. By applying this OWASP Top 10 checklist for vibe coding, you can catch the most common flaws AI tools introduce. Run through it after every major feature, and consider automated scanning for ongoing protection.

FAQ

Is vibe coding inherently insecure?

Not necessarily, but the speed of AI generation often bypasses security review. The same vulnerabilities that appear in hand-written code can appear more frequently in AI-generated code if not audited.

Can I trust AI to fix security issues automatically?

AI can help, but it's not foolproof. Always verify fixes manually or use a dedicated security scanner like OverMCP to catch what AI misses.

How often should I run this OWASP checklist?

Run it after every major feature or deployment. For continuous protection, integrate security scanning into your CI/CD pipeline.