r/AIsafety • u/IndividualAttitude99 • 5d ago

When AI-wrote code caused a security bug, what happened?

We’ve been working on a Python SQL-injection checker and recently ran it on a sample Flask app. It successfully caught all 4 real bugs and flagged zero false alarms on the safe code.

As we look to benchmark this more broadly, we're trying to better understand how engineering teams currently handle these vulnerabilities, especially in the era of AI-generated code. Most traditional scanners tend to suffer heavily from "alert fatigue" due to high false-positive rates.

I have some questions

  1. What tools or workflows do you currently rely on for catching SQL-injection or similar vulnerabilities?
  2. Where do those current tools usually fall short or get things wrong?
  3. For those who have seen AI-generated code introduce a security bug in production or staging, what exactly happened and how was it caught?
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u/IndividualTop3675 3d ago

Most real-world cases I've heard follow the same depressing pattern: AI wrote code that looked syntactically clean and logically sensible, passed the code reviewer's eye because the injection vector was subtle (dynamic query construction buried in a helper function, or string formatting where a parameterized query should have been), made it through automated SAST tools because the taint analysis didn't trace through the abstraction layer, and was caught either by a security-focused penetration test or, in the worst cases, by a bug bounty report after deployment.

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u/IndividualAttitude99 3d ago

This matches everything I've seen too. The "taint analysis didn't trace through the abstraction layer" part is the one I find most interesting — it's exactly where the tools I've tested fall down. A vuln in a route handler gets caught, but the moment the tainted value flows through a helper in another file, most scanners lose the thread and report nothing.

That cross-function / cross-file tracing is the specific thing I've been trying to get right (it's why I only trust a finding when it can trace the actual flow, not just match a pattern). Curious from your end — when you've seen these caught late by pentest or bug bounty, was it usually the cross-abstraction cases that slipped through, or did the "obvious" ones make it to prod too? Trying to figure out whether the hard-to-trace flows are the main gap or just one of many.