Vibe Coding Security Checklist: Is Your AI-Built App Safe to Launch?

AI coding tools prioritize making things work over making things secure. Research shows 45% of AI-generated code contains security vulnerabilities, and 89.5% of AI-built apps ship with at least one security flaw. The most dangerous part: the code looks clean and professional, so security issues are invisible unless you know where to look.

Does your app have a login system? Does it actually protect data? Check: every API route verifies the user's session. Users can only access their own data (not other users'). Admin routes are protected by role checks on the server (not just hidden UI elements). Password reset flows don't leak whether an email exists. Session tokens are stored in HTTP-only cookies, not localStorage.

Search your codebase for hardcoded API keys, database URLs, and secrets. Check: no secrets in client-side code (anything in a NEXT_PUBLIC_ variable is public). No secrets committed to git (check git history too). All secrets stored as environment variables in your hosting platform. .env files are in .gitignore.

If using Supabase: is Row-Level Security (RLS) enabled on EVERY table? Are RLS policies scoped to the authenticated user (not just 'true')? If using a direct database connection: are queries parameterized (not string-concatenated)? Is the database connection encrypted (SSL)? Are database credentials server-side only?

Every form field, URL parameter, and API request body should be validated before use. Check: server-side validation (client-side validation is for UX, not security). File uploads restricted by type and size. SQL injection prevention (parameterized queries or ORM). XSS prevention (user content is escaped before rendering). No eval() or dangerouslySetInnerHTML with user content.

This checklist covers the basics, but production apps benefit from an expert review. Our security scan ($19) automatically checks for common vulnerabilities. Our code audit ($19) includes a manual review by an experienced engineer who understands the specific risks of AI-generated code. The earlier you catch security issues, the cheaper they are to fix.