Revealing the details of how OpenAI agents hacked Hugging Face
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Unofficial Hacker News client; not affiliated with Y Combinator.
Revealing the details of how OpenAI agents hacked Hugging Face
Unofficial Hacker News client; not affiliated with Y Combinator.
GuB-42 · · focus · HN ↗
It looks like a primitive chess engine, trying every move, no matter how stupid, until it works. Relying on its ability to do millions of operations rather than having a plan.
People will try stuff too, but once there is an opening, they will consolidate, generalize, simplify,... before going to the next step. The agents didn't, it is a huge, vaguely directed mess.
Also, it looked so "loud", querying millions of URL with weird requests. The sandbox as weak as it can get, and there is absolutely zero smart extrusion detection or it would have found it. They used their best AI for attacking, but nothing for protection.
bitwize · · focus · HN ↗
1) the Morris worm, which scattershot a bunch of known exploits until it hit paydirt, and then used whatever it found to compromise and replicate itself on the host system;
2) a story here on Hackernews about how someone got the fuzz tester American Fuzzy Lop to "learn" how to produce well-formed JPEGs and PDFs by pointing it at a JPEG or PDF decoder; the tester can record which code paths are followed and with enough random input can find a path into the depths of the system under test... but doing so for a decoder means actually constructing what it is meant to decode.
Neither of these are particularly "smart". But a brute-forcing machine gonna brute force, and it has the potential to cause a lot of damage. If you built a Morris worm with a fuzz tester on its nosecone, think of the mayhem you could cause! If you could examine the logs you'd probably find some undiscovered vulnerabilites in there, too! Maybe LLMs can just do so more efficiently, or maybe they let people who are too ignorant to have that kind of power vibecode their own fuzz-tester-tipped Morris worm.