Pre-Launch Security Checklist MVP: AI-Built Apps Guide

TL;DR

If you built your MVP with AI coding tools like Cursor, Bolt.new, or Replit Agent, you need a pre-launch security checklist MVP that covers leaked secrets, broken access control, and common OWASP vulnerabilities. Run through these 8 steps before deploying: scan for hardcoded API keys, check authentication logic, fix CORS misconfigurations, add rate limiting, validate all inputs, review database rules, audit npm dependencies, and add security headers. Each step takes 5–15 minutes and can prevent a data breach or account takeover.

Introduction: Why Your AI-Built MVP Needs a Security Check

Building an MVP with AI is fast. But AI coding tools often skip security best practices. They don't know your threat model. They might hardcode secrets, forget input validation, or leave endpoints open. A single leaked API key or an insecure database rule can cost you thousands. This guide walks through a concrete pre-launch security checklist MVP that takes under two hours and covers the most common flaws in AI-generated code.

Step 1: Scan for Hardcoded Secrets and API Keys

AI models sometimes output real-looking API keys, database URLs, or tokens directly into your code. Even if you use environment variables, a stray string can slip into a config file or a client-side bundle.

What to check:

Example fix:

Before:

const OPENAI_API_KEY = 'sk-1234567890abcdef';

After:

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;

Step 2: Verify Authentication and Authorization

AI-generated auth code often has logic bugs. A common mistake is checking authentication but not authorization — any logged-in user can access another user's data.

Checklist:

Example vulnerability:

app.get('/api/user/:id', async (req, res) => {
  const user = await db.findUser(req.params.id);
  res.json(user); // No check if req.user.id === req.params.id
});

Fix: Compare req.user.id with req.params.id or use a query scoped to the authenticated user.

Step 3: Review CORS and API Security Headers

AI often sets overly permissive CORS policies (like Access-Control-Allow-Origin: *) or omits security headers.

What to add:

Example fix (Express.js):

const helmet = require('helmet');
app.use(helmet());

app.use(cors({
  origin: 'https://yourapp.com',
  methods: ['GET', 'POST'],
  credentials: true
}));

Step 4: Implement Rate Limiting

Without rate limiting, your API is vulnerable to brute force attacks and DDoS. AI-generated apps often skip this.

What to do:

Example:

const rateLimit = require('express-rate-limit');
const limiter = rateLimit({
  windowMs: 15 * 60 * 1000, // 15 minutes
  max: 100
});
app.use('/api/', limiter);

Step 5: Validate and Sanitize All User Inputs

AI-generated code often trusts user input directly. This leads to XSS, SQL injection, and command injection.

Checklist:

Example fix (Next.js API route):

export async function POST(req) {
  const { email } = await req.json();
  if (!email || !email.includes('@')) {
    return new Response('Invalid email', { status: 400 });
  }
  // Continue safely
}

Step 6: Check Database Security Rules

If you use Firebase, Supabase, or MongoDB Atlas, AI may generate overly permissive security rules.

What to check:

Example Firebase rule fix:

service cloud.firestore {
  match /databases/{database}/documents {
    match /users/{userId} {
      allow read, write: if request.auth != null && request.auth.uid == userId;
    }
  }
}

Step 7: Audit NPM Dependencies for CVEs

AI tools often install the latest package versions without checking for known vulnerabilities.

What to do:

Example output:

npm audit
# found 5 vulnerabilities (2 high, 1 critical)
# Run npm audit fix to fix them.

Step 8: Add Security Headers and HTTPS

Ensure your app uses HTTPS and sends proper security headers.

Checklist:

Example (Next.js next.config.js):

module.exports = {
  async headers() {
    return [
      {
        source: '/(.*)',
        headers: [
          { key: 'X-Frame-Options', value: 'DENY' },
          { key: 'X-Content-Type-Options', value: 'nosniff' },
          { key: 'Content-Security-Policy', value: "default-src 'self'" },
        ],
      },
    ];
  },
};

Automate Your Pre-Launch Security Checklist

Manually checking everything is tedious. Tools like OverMCP can scan your entire app — including client-side JavaScript, server endpoints, and environment variables — and give you a prioritized list of vulnerabilities. In a single scan, it checks for leaked secrets, hardcoded keys, XSS, CORS misconfigurations, and more. It's designed for vibe-coded apps and integrates directly with your CI/CD pipeline.

Conclusion

Following this pre-launch security checklist MVP will catch 90% of the common vulnerabilities in AI-built apps. Spend an hour before launch to avoid a crisis later. Remember: security is not a one-time check — revisit it after every major update.

FAQ

What is the most common vulnerability in AI-built MVPs?

The most common vulnerability is hardcoded secrets (API keys, database passwords) in client-side or server code. AI tools often generate example keys that go into production.

How long does it take to run this pre-launch security checklist?

For a typical MVP, each step takes 5–15 minutes, so the full checklist can be completed in 1–2 hours. Automated tools can cut that to minutes.

Do I need a dedicated security tool for my MVP?

Yes, automated scanning like OverMCP helps catch issues you might miss manually. It's especially useful for non-security experts who built their app with AI.