As a certified AI Hater, I do have to say: We seem to have found one (1) use-case for LLMs where they're useful and (can be) prosocial: Finding software vulnerabilities.

[varx@infosec.exchange]

As a certified AI Hater, I do have to say: We seem to have found one (1) use-case for LLMs where they're useful and (can be) prosocial: Finding software vulnerabilities.

This wasn't true a few months ago, but it seems the scales have finally tipped.

It ticks the boxes for me:

- Verifiable
- "Generative" aspect is limited
- Utility that isn't just replacing human labor

(I don't *like* it, and I don't know how the overall cost/benefit shakes out, but... this does seem to be legit. Just be wary of the hype.)

[varx@infosec.exchange]

Before reaching for an LLM for finding vulnerabilities in your own project, you should probably still be:

- Testing
- Linting
- Running other existing, algorithmic static analysis tools for security
- Fuzzing
- Looking at new and existing security bugs and looking for other bugs of the same type *and* findings ways to make each type of bug harder to introduce in the future

With those already in place, LLMs still don't seem to have a major advantage. I'm curious whether that will change, though.