AI writes confident, insecure code
AI models are trained to produce working code. "Working" and "secure" are different things. The model has no incentive to add security measures you didn't ask for — it just solves the stated problem.
1. SQL injection in raw queries
When you ask AI to "query the database for users matching this name", it sometimes writes raw string interpolation instead of parameterized queries. This is a classic SQL injection vulnerability. Always look for string template literals in database calls.
2. Missing CSRF protection
AI builds API endpoints that accept POST requests without CSRF tokens. If you have any state-changing actions on your frontend, this is exploitable. Framework defaults usually protect you, but custom endpoints often don't.
3. Exposed environment variables
AI sometimes puts secrets in places they can leak — console.logs, error messages, API responses. It also occasionally hardcodes test credentials and forgets to replace them.
4. Overly permissive CORS
When asked to "fix the CORS error", AI often adds `Access-Control-Allow-Origin: *`. This works but exposes your API to requests from any origin. Fine for public APIs, dangerous for authenticated ones.
5. Missing rate limiting on auth endpoints
AI builds login endpoints without rate limiting. Your `/api/auth/login` endpoint is wide open to brute force attacks. Add rate limiting before you go public.
How to catch these in production
ProdFix's security module monitors for CSP violations, suspicious request patterns, and known attack signatures. It won't catch everything, but it will alert you when something looks wrong in production — before it becomes a breach.
Stop flying blind in production.
ProdFix gives you error monitoring, performance tracking, security alerts, and AI-powered fixes — built for solo founders and vibe coders. One SDK, 2-minute setup.