| ▲ | eru a day ago | |||||||
Going on a bit of a tangent: 'Classic' non-AI fuzzers like AFL are still insanely useful and powerful, as are static analysis tools. LLMs make all of these much, much easier to use. The other night, before I went to bed I told Kimi to go and fuzz filesystem code in the latest Linux kernel. I woke up to 26 crashes with reproducers and fixes. I'm still busy reviewing and upstreaming them. (Some have already landed.) | ||||||||
| ▲ | billypilgrim a day ago | parent | next [-] | |||||||
Similar use case here! Combining AI with fuzzers is so powerful, especially for creating a special fuzzing harness, or generating seeds for hard to reach code. That was taking hours/days and was frustratingly boring work before. Unfortunately the Codex models refuse a lot for me, I’m mostly using the cheapest models because they refuse the least, have you found Kimi to be a good alternative? Any other you tested that you can recommend? Thinking of switching. | ||||||||
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| ▲ | Foobar8568 a day ago | parent | prev | next [-] | |||||||
At work, I am arguing with tech leads that they should sanitize user inputs for a public facing chatbot. I want to cry. | ||||||||
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| ▲ | wavemode a day ago | parent | prev | next [-] | |||||||
> (Some have already landed.) Do you have links to some of these? | ||||||||
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| ▲ | elzbardico a day ago | parent | prev [-] | |||||||
It is more than LLMs are faster using those tools, than they are finding more errors by themselves analysing the code. | ||||||||
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