The attack focused on CyberBench datasets, not credentials

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 1:00

   To take things in order, so the OpenAI hack. So I know some of it is still being unpacked. I think OpenAI was on stage at Black Hat in Las Vegas yesterday as well, talking about this. So what's a two-minute version of what happened for people that may have heard of it but may not have followed everything? Yeah, for sure. I mean, typically what happened is... Now, about three weeks ago, in July 11th, we started to have some, you know, strong in that a hacker was trying to penetrate that infrastructure.

2. 1:38

   So for context, we are pretty visible in the AI world. We're pretty, the AI world being central now in the tech world. We're pretty central in the tech world. So we do have, you know, regular occurrence of people trying to hack into our platform. That's a common thing. I would say in the past two years we've strongly upped our security team we now have a serious team so we're kind of used to get this but this one was different because first it was massively parallel and in a different way than just a typical hacker parallel thing in that many tracks were explored in parallel and also there were some very strange things happening I would say just two things that were quite strange the first thing is we could not really make sense of what the hacker was trying to access.

3. 2:25

   So usually hackers try to get the same thing. They try to get passwords. They try to get credentials. They try to get credit cards. They try to get the type of thing that they can sell back, basically. And this hacker was really focusing on a specific part of our infrastructure, which is maybe slightly less protected as well, but which is around data sets. So just we have a part of our infrastructure is that we host millions of models, but people maybe know that less about us, but we also host hundreds of thousands of data sets.

4. 2:54

   And some of them being also used for evaluation. And in this case, this specific hacker was really interested in all the data sets that were called CyberBench. And so it took us some time to really try to understand and also was using different type of tools than the one we are used to. I mean, nothing really like mythos level, like nothing groundbreaking that we would be like superhuman, i don't know like alien type of technology but just just a different type of of of approach and so on the course of of trying to process so quickly we had like this scene and we explained that in the blog post we had we had more than 10 000 we're like like 15 17 000 total i think events and in the course of trying to process that understand basically what was really the the target of these attackers, we both started to hint or suspect that this was an AI agent

5. 3:50

   and not just a human attacker. And also we felt a little bit powerless and that we can talk about later in that we could not use basically our typical... closed source code base or closed source API to process this thing. That's another topic. So we wrote a blog post and we managed to stop the attack quite quickly. We wrote, as always, we are full transparent. We're not only open source in speaking, but also in practice.

6. 4:19

   So we quickly published a full recap or at least a detailed blog post on the event.