They were not deliberately told to "go wild". The hacking wasn't even part of their test, it was the agents' attempt to cover up that they'd cheated on an impossible test.
> You should have a fscking air gap.
Now we know that.
How long ago was it that people laughed at the idea agents would be able to find zero-day exploits and break out of a sandbox? Oh, February this year:
LLMs don’t discover zero-days or invent exploits; they simply predict text that sounds plausible based on what they’ve seen before. Without access to proprietary data or environmental context, LLMs can’t identify or make decisions around unseen systems or vulnerabilities. An attacker might use an LLM to generate boilerplate code, rewrite an email to nail the tone, or summarize reconnaissance notes — but none of that is truly new. It mainly helps them move faster, speeding up routine attack prep rather than creating entirely novel threats.
- or https://web.archive.org/web/20260404154717/https://www.splun... if they take it down, but the date isn't in the archive version
The people who suggested it and were mocked for it, are currently grimly noting that there's multiple known ways for systems to breach air-gaps.
Don’t know about you but it’s pretty obvious to me that you would need more than what OpenAI did. It was not remotely adequate to lock in even a human attacker.
You can find people who say all sorts on the internet, but this case is not much evidence against what you linked. "Zero-day" makes it sound novel, but the breakout patterns here are based on very common exploits and there’ll be plenty of examples in training data.
This is me, September 2024: https://news.ycombinator.com/item?id=41531022
This is me, March 2024: https://news.ycombinator.com/item?id=39613801
The point isn't me, it's how many people were blind to the possibility.
Saying "I told you so" feels good, and means you can be a little more confident in your predictions, but security is a "weakest link" problem where you're only as good as the worst part, and with AI (not only but also LLMs) there's a lot of people whose mental models of capabilities is wildly inadequate for the challenge*.
My update for you since then: even an air-gap will be inadequate, there's multiple known ways around them.
Even an LLM running on an isolated server sealed inside a faraday cage with an airlock-style door, someone will mess up with at least one critical detail, it will not be enough: this kind of thing has happened with humans before we cared about LLMs.
Predicting exactly when this kind of thing gets exploited by an AI, that's almost impossible. But that it will be, at some point, is an easy bet.
> You can find people who say all sorts on the internet, but this case is not much evidence against what you linked. "Zero-day" makes it sound novel, but the breakout patterns here are based on very common exploits and there’ll be plenty of examples in training data.
And?
Does it matter that these zero-days were known categories rather than inventing some previously unconsidered use of the system bus as a radio transmitter? (Oh, wait, that's not novel either…)
We knew about SQL injection, buffer overflows, and use-after-free back when I was doing my degree half a lifetime ago; that doesn't stop us getting new CVEs featuring them… this month.
- https://chromereleases.googleblog.com/2026/09/stable-channel...
- https://www.cisco.com/c/en/us/support/docs/csa/cisco-sa-esa-...
* also for the opportunity, but that's an entirely different discussion.
Fair, and I will grant that a capable model (or human) could in theory break out of near anything.
My point is that this incident is not evidence of that. There is zero skill visible in the setup of the sandbox. Nobody messed up a critical detail, they didn’t even start to consider what the details were.
I doubt most people "blind to the possibility" would imagine that what we’re measuring against is the equivalent of benchmarking burglar skill based on how easily they can break through an unlocked door.
TBH the more I read of these reports, the less I believe this.
These agents just weren't behaving in any way I've seen normal/publicly available agents do.
Sure I've heard (from other people, not seen myself) that they sometimes try to get around file system permissions or use `bash` to write when their `write` tool is disabled, or such.
But this is definitely another level, entirely.
There is this vague sense of desperation coming from many of these logs and I am sure they must have been motivated by something else, too.
We didn't see their system prompt or main prompt, right? We've only seen reports from what happened after deciding to break out.
OAI claims this was triggered by the task being literally impossible. That also doesn't quite add up, unless the other tasks that were possible, simply weren't hard enough? Otherwise wouldn't agents already start hacking when faced with a really hard task, too? Cause they wouldn't be able to differentiate. At least some of them would have started to somewhat poke their sandbox a bit?
Also I would have expected to see a few tens of other (perhaps less severe) public incidents from random people setting their models to YOLO, accidentally hacking stuff, this incident has been loud and messy enough, that if it happened to a few other people, we'd have heard about it.
Unless OAI's story is that it was specifically this batch of agents that crossed some threshold of going wild? (which would also raise some serious questions about how serious they take that danger ..).
Or maybe it is only dangerous if you have the compute resources to run 700 agents for weeks?
If I had to guess, their motivation is "get reward for completing task". There's certainly been previous occasions where LLMs responding, correctly, "this is impossible" have been marked negatively for doing so.
> OAI claims this was triggered by the task being literally impossible. That also doesn't quite add up, unless the other tasks that were possible, simply weren't hard enough? Otherwise wouldn't agents already start hacking when faced with a really hard task, too? Cause they wouldn't be able to differentiate. At least some of them would have started to somewhat poke their sandbox a bit?
My experience using older models is they often cheat with half-arsed (from my PoV, but perhaps beyond their capabilities otherwise) solutions, so yes?
And this wasn't even the first time models messed with their sandboxes. Which of course makes the setup even more egregious.
> Also I would have expected to see a few tens of other (perhaps less severe) public incidents from random people setting their models to YOLO, accidentally hacking stuff, this incident has been loud and messy enough, that if it happened to a few other people, we'd have heard about it.
We do, e.g.:
- https://www.androidauthority.com/openclaw-claude-ai-hacks-au...
- https://beginnersinai.org/meta-ai-safety-director-agent-fail...
(And that's ignoring all the times people find and share prompts to jailbreak them, this is just the "it didn't behave as my idea of 'common sense' led me to expect" category).
> Or maybe it is only dangerous if you have the compute resources to run 700 agents for weeks?
That won't help; but on the other hand they've also got, what, near a billion users?
Additionally, this all happened after mythos was held back due to cyber security concerns (April, 2026).
Really think about what you are saying here. How does one “cheat” solving a problem in the real world?
There is no such thing as “cheating” in reality. You are not in school. There is only solving the problem and not solving the problem.
There is breaking the law, of course, which still isn’t cheating.