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33% Positive
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#llms#bugs#bug#zero#more#finding#code#security#easy#human

Discussion (36 Comments)Read Original on HackerNews
We wont stop using AI.
We will use AI to check AI.
Of course this is crazy, but it will also unlock pretty insane scaling and productivity and ultimately we will manage it on either end via requirements and tests.
From that standpoint, it's not a crazy setup security-wise. Maybe still crazy for development.
The only thing left for you to do should be directional decisions. The LLMs should pause and rope you in if the fix involves directional/invariant changes.
No big deal? It’s not like it’s free… tokens cost money.
A.I. could also be used to port C/C++ codebases to Rust, which isn't economically feasible at the moment.
There are also non security bugs that don't have exploits but just make the user experience worse.
I guess sometimes developers think they "know" some variable won't be zero, but unless it checked explicitly or by the compiler, that shouldn't be trusted.
If you’re accepting large false positives rates: yes.
If you want users to take your warnings serious: no.
(Nitpick: you certainly don’t want to flag _all_ of them. Divisions by non-zero constants definitely should be excluded, for example (integer division by -1 can lead to overflow, but that would be a different warning))
Generating correct input to get deep into the call stack and then finding something is the hard part.
They only suggested a basic guard, chich can be useless if this case never happens
https://code.ffmpeg.org/FFmpeg/FFmpeg/commit/8eda3c7f91e1a5b...