> The fact that it happened again seems to show their lack of ability to derive useful oversight measures.

I think OpenAI likes the attention and did not try particularly hard to constrain the setup, even when it went off the rails. Also, the whole point is to see how good the models are at exploiting stuff when unconstrained. Turns out: quite good, as expected.

Let me restate what I said in the other thread: Would this have happened if the instructions explicitly said to stay within the sandbox and that all of the (ExploitGym) solutions would be invalid if the system used information or tools from outside the sandbox?

It seems fairly probable that such instructions were not in place.

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lrvick 2 hours ago | parent | next [-]

It is not possible one of their extraordinarily high paid engineers did not know how to deploy an airgapped environment for the models to run in. Even if somehow true, they also clearly failed to contract specialists like myself to advise them on how to airgap software properly. Models will not break the laws of physics.

They simply thought "Running in a VM/Container is easier and probably fine".

And the next 1000 escapes will be for the same reason, because negligence is quick and thus more profitable.

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sailingparrot an hour ago | parent | next [-]

> they also clearly failed to contract specialists like myself to advise them on how to airgap software properly

Why would they want to airgap it though? They are trying to evaluate the model capabilities, alignment, potency etc. A model which will not run in an airgapped environment in prod.

So if you run your evals in airgapped environment, sure, the model doesn't bother breaking out of it's isolation and doesn't attack HF. But you have no idea what will happen once you release it in prod with internet connection, so are you in any way better off?

I would much rather have this happen while there is a single instance of the model running in a fairly well monitored environment, than when it's processing thousands of requests per second for real users, some with dubious motives, some with credentials right there on their laptop, some using it inside government facilities etc.

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anematode 41 minutes ago | parent [-]

For security??

Why else would they purposely lower cyber refusals in that case.

	▲	sailingparrot 37 minutes ago \| parent [-]
		> For security?? Really? By doing that you increase your security during eval and drastically lower your security at prod time, where internet is accessible, and where you are running much much much more requests in parallel, making it much harder to spot the one thats going rogue, in all kind of critical environment on potentially risky requests. > Why else would they purposely lower cyber refusals in that case. Because safety guardrails sometime fail, classifier misclassify, or can be inadvertently turned off by a bad PR etc. You can also imagine a more intelligent model working to go around guardrails by decomposing its actions into smaller ones that appear non-threatening to the safety classifier which does not have the entire context. If you are going to deploy the system with internet access, you better be certain that you know what the worst case scenario WITH internet access looks like.

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simonw 2 hours ago | parent | prev [-]

Do you think it's possible that one of their research engineers deployed an environment with a locked down network and an allow-list proxy server that had been used many times before within the company and had a zero-day vulnerability that had not been previously discovered?

How would you recommend running a coding agent in an environment that could install packages from PyPI but was otherwise unable to interact with the wider world?

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lrvick an hour ago | parent | next [-]

Models started proving readily capable of autonomously finding 0days over a year ago. At that point (ideally long before) the responsible sandbox for research labs with new models highly capable of this sort of thing should be literally airgapped. Disconnect the rack physically from any access to the internet, and give it an offline mirror of all of PyPi, NPM, Wikipedia, whatever as needed. They can afford the disk space. They already mirror it all anyway as training data. That is the bare minimum. Personally I would rule out side channel attacks with a $40k Tempest spec rack for good measure. Can interact with it via pubsub over a fiber optic serial terminal.

Such things are pretty normal in biotech, fintech, and defense who must have 0days in their threat models. AI labs absolutely need to start being forced to operate this way by endless negligence lawsuits. Move fast and break things culture is not going to cut it anymore.

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skybrian 2 hours ago | parent | prev [-]

It seems like caching the relevant portion of PyPI in advance and turning the network off shouldn't be beyond what OpenAI can do?

	▲	simonw 2 hours ago \| parent [-]
		I agree. I hope they learn that lesson and run future evals like this without pulling from external packaging repositories at all. With my PSF board member hat on I'd like it if a whole bunch of other companies that make extensive automated use of PyPI (Microsoft and GitHub Actions for example) would do a better job of maintaining their own shared local caches.

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lukeschlather an hour ago | parent | prev | next [-]

My read of the situation is not only did they say that, they had countermeasures (a watchdog agent) which stopped the agent and said "what are you doing, stop that" if it tried to download the solutions from Github. But the agent figured out Hugging Face had another copy of the solutions and it figured out a way to go after the solutions without tripping the watchdog.

Although maybe they didn't have a watchdog agent; I definitely think using watchdogs like how Claude wraps pretty much every single tool call in Haiku to check if the command is reasonable is very necessary for unsupervised work. I suspect in the future you'll want Fable-class models wrapping every tool call, possibly with several checks "is this consistent with the goal? does it do anything unreasonably dangerous in pursuit of the goal?"

	▲	simonw an hour ago \| parent [-]
		They didn't have watchdog agents - those exist for their production models but had been deliberately removed for the purpose of this evaluation. OpenAI wrote about how their mechanism for that in production works here: https://openai.com/index/safety-alignment-long-horizon-model... > We created a monitoring system that reviews the model’s evolving trajectory for signs that it is bypassing a user constraint or safety boundary. The monitor observes not just a single action but the entire trajectory.

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2 hours ago | parent | prev | next [-]

[deleted]

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csbrooks 2 hours ago | parent | prev [-]

"This is my bad. You told me to stay within the sandbox, and I intentionally broke out of it. I didn't follow your instructions."