Cursor (and similar AI-native editors) are trained to produce code that compiles, passes the obvious test cases, and matches the pattern of the surrounding codebase. None of that requires the code to be secure. A login endpoint with a classic SQL injection bug will still “work” in every test that doesn’t specifically probe for injection.
The real risk isn’t Cursor being “bad”
Cursor frequently produces clean, idiomatic, senior-quality code. That’s actually part of the problem: a single AI-generated file with a hardcoded secret or a missing auth check is easy to miss precisely because the surrounding 95% of the codebase looks trustworthy. Reviewers pattern-match on overall code quality, not on individual files.
Wondering if your code has any of this? Scan a public repo free, no account needed.
Scan a repo →Where Cursor-generated bugs actually show up
- Auth controllers with string-concatenated SQL queries
- Migration and seed files with hardcoded test credentials that ship to production
- New CRUD routes scaffolded without an authentication check
- Webhook handlers using
===instead of constant-time comparison - Config files with a fallback secret for missing environment variables
What actually helps
Code review catches some of this, but reviewers are reviewing for correctness and style far more than for security, and Cursor’s output reads as confident and complete. A scanner built specifically for the vulnerability classes AI tools produce — run on every push — catches what a normal review pass is statistically likely to miss.
See Prbl for Cursor users for what this looks like in practice.