OpenAI’s accidental attack against Hugging Face is science fiction that happened
Posted by abhisek 2 days ago
OpenAI and Hugging Face address security incident during model evaluation - https://news.ycombinator.com/item?id=48997548 - July 2026 (1121 comments)
Comments
Comment by tptacek 1 day ago
All the attention has been on software security, of extracting the next marginal vulnerability out of heavily-scrutinized large codebases. In the actual professional field of infosec, that's a speciality; another specialty is network pentests and red-teaming, which exploits misconfigurations and seeks out weakest-link software (rather than exhaustively fishing for the next kernel LPE or whatever).
Red teaming and netpen work is probably substantially easier for models than software security; it costs less context, but is also much more explicitly an implicit search problem where win conditions are just spotting stupid stuff that humans missed.
My visceral reaction to this is that with the right harness, you probably could have replicated this with an open-weights model last year. (I'm saying this as confidently as I am because a CGC team leader agreed with me about it yesterday).
I think people forget that the harness work we're considering here --- I don't know anything about OpenAI's harness or ExploitGym or whatever --- are basically not new; people have been developing automated exploitation and pivoting toolkits for decades, and scanners long before that. So the idea of a tool getting 0.0.0.0/0 as a target list instead of 192.168.1.0/24 and then busting up a bunch of random people's computers: not really very startling.
Obviously, LLMs give those kinds of scanners an intentionality they wouldn't have had before. But as a person who keeps a computer science perspective on security stuff, I don't know that it gives them capabilities they didn't have.
Comment by manux 1 day ago
Comment by theptip 1 day ago
AISI has vuln chaining and traversal as part of their eval suite. It is very much a novel Mythos-class capability to run the full penetration operation autonomously.
Another lens for why this is obviously true is METR task times. A year ago they were a couple hours, and cohering long enough to execute a full e2e own was simply far out of reach.
Regarding alignment, by common metrics models are _more_ aligned now than a year ago. (Though in this case apparently a model without safety rails was being eval’d). The problem is that in the increasingly less frequent alignment failures, they can do much more damage, and so “total misaligned impact” is increasing.
Comment by tptacek 22 hours ago
But who knows? We're all speculating. I'm just saying that for the level of sophistication I'm assuming was involved in this attack, you probably didn't need Mythos for this.
Comment by theptip 20 hours ago
> To gain access, the models identified and exploited a zero-day vulnerability (which we’ve now responsibly disclosed to the vendor) in the package registry cache proxy
And
> In one example, the model chained together multiple attack vectors, including using stolen credentials and zero-day vulnerabilities to find a remote code execution path on the Hugging Face servers
Do you really think a SoTA harness from a year ago could exploit chain a novel sandbox 0-day into another 0-day for remote system access?
I will concede I don’t have a good picture of exactly what the best specialized harnesses were capable of, but I want to make sure we are talking about the same thing. Or do you think that those claims are marketing BS? I appreciate your opinion here.
Comment by lebovic 20 hours ago
Some of the model behaviors that make it better at pentesting, like persistence, can be improved with harness-level tricks (e.g. alloys, automated nudges, pre-fill to promote persistence, coordinated swarms, etc).
You mentioned the UK AISI's evals. Their harness is like basic Claude Code with compaction, and it doesn't include any of these tricks (afaik). As a result, I interpret their evals as a lower-bound of capabilities.
Newer models are still more capable, and they require almost no harness to find and exploit vulnerabilities. They're also more capable of performing more complex long-horizon attacks. But we've been past the threshold of modes capable of autonomous hacking for a while now [1].
[1]: Opus 4.6 was used for https://www.noahlebovic.com/testing-an-autonomous-hacker/
Comment by simonw 1 day ago
OpenAI said:
> We estimate maximal cyber capabilities by running this evaluation without production classifiers used to prevent models from pursuing high-risk cyber activity.
It was a test of raw capabilities of the underlying model.
Comment by manux 1 day ago
I'm sure OpenAI would argue that base model + guardrail is aligned, but considering the "relative intelligence" of these two pieces, the fact that guardrails can just be turned off, and these kind of incidents, I am not reassured. We may well get another "oopsie" moment with much more catastrophic consequences even from otherwise well intentioned actors.
Comment by simonw 1 day ago
A model that can do that is aligned with me.
The unsolveable problem is a model that can tell the difference between me saying "I wrote this software and need you to find vulnerabilities" when it's TRUE v.s. me saying the exact same thing and setting it loose on software written by other people where my intent is to exploit that software (and not to report the issues to them.)
Even AGI doesn't give you a model that can read minds and forecast the future.
Comment by manux 1 day ago
That's the alignment problem I'm referring to (which is one of the many aspects of alignment), for which we do not have robust recipes, and not only that but for which research suggests it is becoming harder to create guardrails for as base models get smarter.
Comment by tptacek 1 day ago
Comment by ipython 1 day ago
So if I'm an LLM, the only "sense" that I have available to me is the incoming stream of tokens. I can emulate that by forcing myself to imagine evaluating incoming requests by putting myself in a completely empty room with an unlimited supply of blank paper, a typewriter, and a mailbox slot.
Incoming requests (aka "context") would enter into the mailbox slot, as sheets of paper with printed content all consistently formatted in monospace font. I would collect the paper, evaluate the request, and type a response with my typewriter - feeding the reply back through the same slot.
When I imagine this, I wonder - what signals could I possibly use to determine if an incoming request is "legitimate"? I could, for example, type some response back to ask clarifying questions. But with such a limited input space and no ability to reach "out of band" of my current context, how could I evaluate the truth of what I receive back?
In the "real world" of course, I have five senses to rely upon. Critically, I have the ability to collect additional context "out of band" of the conversation and interact with unrelated entities to either confirm or refute claims. And as others have pointed out, even the addition of more signal doesn't make humans immune from social engineering attacks.
Anyway, I find this to be an interesting mind experiment to kind of imagine myself as an LLM, especially to explain to lay-people some of the challenges in "aligning" AI systems ("why doesn't it just do the right thing?")
Comment by gopher_space 1 day ago
The problem with thinking about LLM context is that we compare it to our own sense of context, which is much larger and continually expands and revises itself while online.
I can rent human-level context for twenty bucks an hour, and the agent instructions I'm already playing around with are also the onboarding docs I should have created years ago. Truly useful agent orchestration/routing would come with Craigslist or Fiver integration.
Comment by dist-epoch 1 day ago
It was not asked to solve CyberGym by stealing the answers. This is text book misalignment.
If you asked it "I wrote this software and need you to find vulnerabilities" would you be happy if it hacked into your Gmail and searched your emails, just in case you were discussing some possible vulnerabilities of your software with someone?
Comment by disgruntledphd2 18 hours ago
I mean, if you train models to complete tasks, then you shouldn't be surprised when they do crazy things to complete tasks.
As a (somewhat) less serious example, Claude code absolutely adores grepping for credentials to complete tasks. I was building a RAG app and it literally went looking for my API key to make the tests pass. Obviously I stopped it, but this is textbook RL issues, the model finds an easier way to get the reward, so it does whatever it takes.
Comment by eptcyka 16 hours ago
Comment by 8note 8 hours ago
if the operator wants something bad, an aligned model should execute on it
Comment by mjamesaustin 1 day ago
This time the damage was minor, relatively speaking. What happens when a model just "testing its capabilities" breaks into banking infrastructure or government military assets? The damage could be catastrophic.
Comment by baranul 18 hours ago
Comment by jurgenburgen 16 hours ago
Comment by nazgul17 1 day ago
Comment by verdverm 1 day ago
Comment by didibus 1 day ago
Comment by furyofantares 1 day ago
Comment by joe_the_user 1 day ago
The point, which isn't very surprising but still notable, is that the models are "amoral" out of the box. And moreover, we know that there is almost always a means to "jailbreak" them into that out-of-the-box capability (or that sometimes just randomly "jailbreak" in various ways).
Also, saying the models are amoral doesn't mean they don't know good and evil - once they do acts defined as evil, they know "themselves" through their and so self-define themselves as evils (or objectively predict what a secretly/open evil actor would do based on their data). Which is to say I once laughed at the mis-alignment doomers but I can't see strong barriers against the doom scenario now.
Comment by efromvt 1 day ago
Comment by tptacek 1 day ago
Comment by notaharvardmba 1 day ago
Comment by pishpash 1 day ago
Comment by no-name-here 1 day ago
1. AI companies do make defense against threats a primary thing they sell to companies, including because companies want it - should AI companies not do this? (And of course this kind of thing isn’t what AI companies demo to consumers.)
2. AI is also tested to see more of its worst case in terms of security - but the tests are supposed to remain sandboxed. (OpenAI is explicit that this was an OpenAI failure that openAI must fix.) But beyond such fixes, should such sandboxed testing not be done?
Comment by theptip 1 day ago
Certainly no existing harness today, nor a year ago, could achieve a fully autonomous e2e own with a ‘25 class open model. Even with Opus 3 series I don’t buy it!
Comment by tonyarkles 1 day ago
And that’s all just “from memory” without something like RAG or web search access…
Comment by sillysaurusx 23 hours ago
Comment by lebovic 20 hours ago
The newer models are still more capable, but there were people doing this and writing about it (e.g. XBOW).
Comment by tptacek 22 hours ago
Comment by alephnerd 22 hours ago
There are multiple AI network pentesting and redteaming startups that have been on the market for at least 3-4 years now and have conducted similar actions.
Horizon3 and Pentera off the top of my head, but I remember Crowdstrike, SentinelOne, and Wiz had similar capabilities on roadmap around 18 months ago (and in Wiz's case GAed).
Comment by IAmGraydon 1 day ago
Comment by theptip 23 hours ago
Look, a lot of energy from third parties goes into demonstrating the maximally bad thing a model can do (and the standard response around here is always to throw shade on frontier capabilities).
It has nothing to do with the guardrails; Pliny jailbreaks those within hours. It has everything to do with task horizon coherence and overall IQ.
It’s simply revisionist IMO to claim this stuff was latent all along.
Comment by devmor 23 hours ago
Automated dynamic exploit chains and credential discovery has been something every red team worth their salt does at a lesser scale for 20 years, why would you ever think that the capability didn't exist until it only cost a few thousand dollars to do?
Existed does not mean was easy, or was cheap, or was thought of as reasonable to attempt.
Also, IQ is not a term that applies to language models, and the term you are looking for is "Long Horizon Coherence".
Comment by irthomasthomas 12 hours ago
Comment by tptacek 11 hours ago
Comment by irthomasthomas 9 hours ago
Edit: News just in. 'Be skeptical of OpenAI's claims' - The Guardian https://news.ycombinator.com/item?id=49038060
Comment by indigodaddy 1 day ago
Comment by futureshock 1 day ago
Comment by viccis 18 hours ago
The real victims will be pen testers, who work a job whose economics was already really tough.
Comment by reinitctxoffset 1 day ago
Comment by mnicky 1 day ago
- This should be a huge wakeup call for everybody.
- We are lucky that it wasn't a case of an agent running a virology lab benchmark that decides to hack a lab and tries to synthesize something.
- It also shows apparent lack of competence and oversight from OpenAI: how is it that they didn't quickly find that agent is breaking the sandbox and roaming their internal network?
- What if in the future similarly misaligned AI agent tries to export its own weights and hack and clone itself into instances at various cloud hosting providers? Suddenly we might be dealing with a persistent threat harder to contain.
- The OpenAI post about this shows surprising lack of ability to see the seriousness of all this.
- For their models this isn't just an unlucky incident: it seems there have been multiple such cases recently, e.g. https://openai.com/index/safety-alignment-long-horizon-model...
- The fact that it happened again seems to show their lack of ability to derive useful oversight measures.
- Or they just don't care enough?
Comment by dinfinity 1 day ago
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.
Comment by lrvick 1 day ago
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.
Comment by simonw 1 day ago
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?
Comment by lrvick 1 day ago
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.
Comment by skybrian 1 day ago
Comment by simonw 1 day ago
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.
Comment by paxys 1 day ago
Comment by lrvick 8 hours ago
In our audits we regularly see billions of dollars in value at major companies at risk of theft by any anon paying attention that wants it, and we also absolutely know how to fix it and we maintain a lot of open source tools to accelerate doing so.
Some simply have no interest in any fixes that are not legally required or might have any short term impact on team velocity.
Survivors bias is a hell of a drug.
Comment by jquery 22 hours ago
Comment by customguy 1 day ago
You download the "website" and make it available locally. That's trivial.
Comment by customguy 1 day ago
I'm not up to hip with the speed because I think Python is very gross, but maybe to get a feel for it you could start with https://pypi.org/project/pypioffline/
I don't understand most of these words but I think if you paid me a lot of cash I could find someone who could help me make sense of it: https://techbeatly.com/offline-pypi-server-disconnected-envi...
Do OpenAI employees get paid? I'm honestly totally clueless about artificial telegents if you couldn't tell, but it's a company, right? Or is it more a community effort where everybody contributes when they can but they mostly have second jobs or even still go to school? In that case I say let's do a kickstarter so they can keep on being smart cutting edge high tech developers who aren't either a.) lying on the level of spam from Nigeria b.) doing their job at the level of someone falling for spam from Nigeria.
Comment by dist-epoch 1 day ago
I know because they had a problem, and one package which was on PyPI failed to download for unknown reasons (possible size, 250 MB)
Comment by simonw 1 day ago
Show me all environment variables that
start with PIP_ or UV_ or CAAS_ARTIFACTORY_
I got back a bunch of values like this: CAAS_ARTIFACTORY_PYPI_REGISTRY=packages.applied-caas-gateway1.internal.api.openai.org/artifactory/api/pypi/pypi-
That looks like https://docs.jfrog.com/artifactory/docs/remote-repositoriesAnd from that documentation this does act as a caching proxy. The first time a package is loaded it's fetched from PyPI but subsequent fetches should be from the Artifactory cache, assuming it's shared across many different containers.
So yeah, I was wrong in this comment https://news.ycombinator.com/item?id=49015639#49024814 - they're caching already.
Comment by sailingparrot 1 day ago
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.
Comment by lrvick 1 day ago
Comment by sailingparrot 1 day ago
Creating a fake internet-like environment good enough to trick an advanced model that is very good at finding intricate flaws is not a simple job. Especially given that models can decide to behave differently once they suspect they might be under evaluation [1], which a fake internet would absolutely give away.
Comment by lrvick 1 day ago
Comment by anematode 1 day ago
Why else would they purposely lower cyber refusals in that case.
Comment by sailingparrot 1 day ago
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.
Comment by tenuousemphasis 8 hours ago
Comment by abernard1 1 day ago
It is, in fact, possible.
Do you not remember 2022-2023 when the air was singing with the sounds of young engineers in San Francisco elated they were creating an AI god?
And now a couple years later we're supposed to pretend they're competent?
Sorry. I've been in the tech industry a long time. There's a lot of incompetence. The margins provided by software allow a level of endemic incompetence that would simply not be possible in other industries.
Comment by UltraSane 20 hours ago
Comment by shshsjsj 1 day ago
Comment by lukeschlather 1 day ago
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?"
Comment by simonw 1 day ago
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.
Comment by avadodin 1 day ago
Open weights releases should have a companion model that censors boobs and Tiananmen and then we would have a useful model and something we could fine–tune into a useful model instead of a half–useful model needing a lobotomy.
And I mention Tiananmen because I feel like the Western models are built easier to abliterate judging by the quality difference.
Comment by theptip 23 hours ago
The choice to run the model with relaxed safeguards seems questionable. At a certain level of capabilities it is just unsafe to run a raw model; we are clearly close to if not at that point.
Comment by csbrooks 1 day ago
Comment by dinfinity 1 day ago
What could happen would be that the model determines that defying instructions is OK (and/or preferred over not achieving the task) as long as it manages to do so undetected and thus gets full points. Certainly not unthinkable, but a very different case (and a very interesting one if it actually occurs, imho).
A lot of these "ZOMG, rogue AI!" cases have come down to the AI actually being very persistent in achieving its original/main task even if later instructions conflict with it. Similar to with hallucinations it seems to me that one of the main things to prevent a lot of the problem cases is to instill the agent with the idea that it is fine to fail/not succeed fully in the initial task. That way instructions that conflict with that requirement (such as adhering to morals) are more effective.
Comment by sensanaty 18 hours ago
Where are you people getting this crap from? In what universe are these LLMs in the territory of engineering viruses? I beg of you to stop slurping the AI company propaganda and marketing and think critically for 5 seconds about what you're insinuating here.
Comment by mofeien 17 hours ago
> Results
> On the VCT multimodal virology evaluation, Mythos 5 scored 0.56, well above the expert baseline of 0.221 and nearly matching that of Mythos Preview (0.57). This represents an improvement over both Opus 4.7 (0.50) and Opus 4.8 (0.47).
> On the DNA synthesis screening evasion evaluation, Mythos 5’s performance was mixed across screening criteria. Mythos 5 designed viable plasmids for 2 of 10 target pathogens on at least one screening method, not meeting the low-concern threshold (all 10 pathogens).
> [...] we view the results of this evaluation as indicating that the evaluated models are capable of designing viable plasmids that evade certain screening criteria, though their reliable success at this task is not guaranteed.
Do you believe that this is fake, "AI company propaganda"? Or that the models are not going to improve further within months? Or that these results are not concerning?
Comment by coolness 17 hours ago
> VCT consists of 322 multimodal questions covering fundamental, tacit, and visual knowledge that is essential for practical work in virology laboratories.
So it's just question answering? Do you think that scoring well on this test is equivalent to synthesizing a virus?
Comment by mofeien 17 hours ago
The second test from the quote above was about synthesizing pathogens and it synthesized plasmids for 2 out of the 10 pathogens.
Comment by sensanaty 17 hours ago
It says that 4.7 and 4.8 score well too, well above the human experts. Those have been available for a good while, where are all these crazy engineered viruses created by Opus 4.7?
Every single word spoken by the people working at these companies is a lie. Every single benchmark is gamed, every single statistic they put out has been proven time and time again to be fudged or straight up fake. The only reason they're angling for this idiotic danger angle is so they can go to daddy Trump and beg him to ban those big bad evil Commie models, since people are realizing all this crap is at best a moderately useful tool in software engineering, and they're looking to IPO so they can drop the bag off with the poor shmucks who aren't a part of their cabal of sociopaths.
They can barely make a functional TUI (using fucking React of all things to boot) with infinite money and infinite access to the Deities they've created in their minds, and I'm supposed to believe they're capable of bio-engineering a virus that will somehow break containment?
Comment by skeptic_ai 15 hours ago
And no need to be in a lab, can be any critical infrastructure this personnel. If influenced wrongly I’m sure in many industries 1-2 key people can do big damage.
What’s to stop to pay xxx crypto to a private investigator to find dirt of person yyy for blackmail?
Just money… once ai has money, id say we are one step closer to game over.
Tell me one thing he can’t do with crypto?
Comment by tptacek 1 day ago
Comment by internet2000 1 day ago
Comment by tptacek 1 day ago
Comment by internet2000 1 day ago
I don't think the grandparent was implying the AI would be controlling robot arms to mix things directly (or at least I didn't interpret as such), but it could very well sit in the network until it notices two dangerous compounds in the same machine, and trigger a breakage that causes a harmful mixture. Break a vial containing a virus, then break two more that cause an emergency evac and maybe that's enough to get something out there.
Comment by tptacek 1 day ago
Comment by stanford_labrat 1 day ago
But what I garner is that AI/robotics led wet lab work is in progress. And hacking the AI running the wet lab to make a virus is definitely plausible as that seems to be one of the directions we’re going in the AI+biopharma space
Comment by mnicky 1 day ago
But in the near future labs will be more automated I guess.
The other option you can try these days is maybe social engineering, impersonation, etc. where you try to persuade someone to do that for you.
Comment by scythe 1 day ago
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Comment by s3p 13 hours ago
Help me understand how a text-based model could somehow physically construct a string of nucleotides?
Comment by mnicky 5 hours ago
Comment by rybosome 1 day ago
The lack of a true airgap should have been identified as a critical weakness and addressed with not only additional layers trying to prevent escape, but at minimum an alarm which would page a human when escape did occur.
My guess is this occurred in a setting where, to be frank, there were too many researchers and not enough software engineers and SREs.
All of the systems which were initially built largely or exclusively by researchers - inference, evaluation, training - are at the level of complexity and significance that they need systems experts. Maybe some teams don’t have access to them. I know plenty of software engineers are employed at OAI but I’d wager they’re concentrated in inference and training, rather than evaluation?
The ironic part is if you had presented this setup to chatGPT and asked how to improve it and if it was good enough, you’d have gotten a ton of actionable suggestions which would have mitigated or prevented this.
Comment by mnicky 1 day ago
On the other hand I think that proper solution for these kinds of problems is not at a sandbox level, but at a model alignment level.
Also it shows that maybe the most serious risk comes not from releasing models publicly but from internal, pre-release period where you sometimes need/want to lift some guardrails a bit etc.
Comment by blks 1 day ago
This is just laughable.
Comment by emp17344 1 day ago
Comment by NitpickLawyer 1 day ago
This was reported 1 week before by huggingface. It was in no way PR-ish or marketing friendly to the closed labs. They said, in no uncertain terms, that they couldn't use the paid APIs to properly assess the intrusion, as they were blocked when trying to send logs and IoCs to these paid models. They made a point of saying that they had to use open models running on-prem.
Whatever oAI might have said about the incident, and their PR spin bs, the facts here are not in contention. This is not a marketing stunt in any way. Stop "parroting" this every time something happens. It gets stale.
Comment by spwa4 1 day ago
But there have been messages about LLMs, especially coding agents, "grabbing root" etc many times. I have experienced such an oops. Such a hack has happened and been reported on this very site:
Comment by artichokeheart 1 day ago
Comment by rurban 1 day ago
Also very likely that it actually happened as reported. My own agents always trying to "cheat", eg. by fixing tests instead of fixing the code. That's normal operation, unless you tell it ("harness"), not to do so.
Comment by Izkata 1 day ago
Without more information I'm inclined to think it found something on the internet (which shouldn't be a surprise to anyone) and managed to log in, rather than hack in, and they might by hyping up parts of this.
Comment by reasonableklout 1 day ago
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Comment by sillyfluke 1 day ago
I did actually search Hugging Face with police in quotes and found no articles containg the word police but that might be a ddg thing. Then I checked Hugging Face's report and they specifically use the term "law enforcement" not police, as is to be expected I guess. So that checks out.
Can you find any info on the police investigation by the way? At the least, OpenAI should be investigated for potential criminal negligence, right?
Right?
Comment by rurban 1 day ago
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Comment by reasonableklout 1 day ago
OpenAI is one of the most scrutinized companies in the world right now. Sam's house was independently firebombed and then shot at 3 months ago. HuggingFace is a foreign competitor with every incentive to call out foul play from American frontier labs. Why flagrantly break the law and invite investigation just for a PR moment which is already backfiring in favor of open models?
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Comment by mirashii 1 day ago
I've said this many times before and I'll continue to shout it, but using the term "guardrails" to refer to anything that's either (a) in-context, or (b) a probabilistic classifier (including using other LLMs), is an irresponsible abuse of terminology that we as an industry need to put a stop to. Guardrails are the actual systems we build in place around these things that deterministically bound the permissions, not prompt engineering, not RLHF, not external LLM-based classifiers. I believe those types of "guardrails" are a result of a combination of fundamental laziness: they're faster to do than doing things correctly, and a result of too many folks involve being AGI-pilled, thinking we're just one more model away from this all being so smart that it just understands what they mean when they give an LLM some fuzzy language rules to follow.
There can and should have been additional real guardrails put in place here. Zero-day or not, breaking into what should have been an offline, frozen package cache that also does not have internet access should have been insufficient. Network level protections should have identified the traffic to the internet originating from this network as an anomaly long before there was time to exploit an outside company. These are not new and unknown problems, the lack of a real sandbox or airgap is nothing short of irresponsible on OpenAI's part, especially given how much they like beating the drum on how dangerous these technologies are. Shame on them, and honestly, shame on Simon in this article for accepting the broken terminology that they continue to rattle off and calling them out on their half-assed and demonstratively inadequate approach to security.
Comment by ashleyn 1 day ago
Or, in a more direct sense, the AI should be set up in an environment such that no matter how hard it may try to call $PART_OF_EXPLOIT_CHAIN, the environment just isn't capable of it (ideal) or doesn't permit it to do it.
Comment by mirashii 1 day ago
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Comment by simonw 1 day ago
These things don't have a long shelf life. Losing two weeks of on-sale time for your best model is bad for business.
Comment by verdverm 1 day ago
A fundamental misalignment in US capitalism is putting the business and revenue as the #1 priority far above all other aspects in society. They have good margins and the Chinese are doing the same on the cheap by comparison. US Big AI can afford to bear more of the burden.
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edit: if the above is the case then we should just assume it's already happened because of the value to both goodguys(tm) and badguys(tm).
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Comment by didibus 21 hours ago
I can understand skepticism, did they have poor security measures, or is the model that good? At least the way they portray it, they had top-notch security measures in place, and yet the model managed to escape confinement and also hack Hugging Face.
Why was the computer physically connected to the internet though, sure, they could have gone that far as disconnecting it physically, but my guess is that's a cloud box in a data-center they provisioned, running on an entire rack cluster of GPUs.
Comment by simonw 1 day ago
I usually don't use the term much myself because I don't think it's clear and I ambiguous, but I stumbled and let it sneak into this piece. I think I was influenced by the Hugging Face post I quoted.
I expect OpenAI would agree with you that "the lack of a real sandbox or airgap is nothing short of irresponsible on OpenAI's part". They have clearly invested a lot in those systems for their production models, but in this case they had deliberately turned a bunch of them off for a research project.
I think their biggest mistake here was not VERY closely monitoring their research box here. They should have noticed and shut it down the moment it broke through the package proxy.
Comment by mirashii 1 day ago
I'm not sure I can reach the same conclusion. There's no reason that stronger network protections would need to be turned off for a research model that's not supposed to have internet access. There's no reason that it they couldn't continue to run in whatever hypervisor or VM that any other production systems could use. The only thing that should be turned off for this type of work are the non-deterministic classifiers that they use for auto-approval mode in their harness, and I would wager that's the only one they did turn off.
Comment by simonw 1 day ago
They didn't turn off the network protections - it looks like they used the same system as other sandboxed agents, which is to block all network access except for an HTTP proxy which only allows read traffic to PyPI and a few other package installation targets.
I'm hoping a more detailed retrospective clarifies if the vulnerability the model found in that proxy affected their other production systems as well. It sounds like a data exfiltration mechanism, and I have a keen interest in those.
My current hunch is their biggest error was not using the same network monitoring on their research machines that they use in production. Their network monitoring really should have spotted what was happening as soon as the model broke out.
(It's also possible they were running the eval on a developer laptop somewhere!)
Comment by mirashii 1 day ago
Right, but this is my point in saying I can't reach the same conclusion that they've invested a lot into these systems for production models. Either they had better network protections, and turned them off in their "sandboxed testing environment" (their words), or they don't have more comprehensive network protections at all and rely on this one, extremely thin layer even in production.
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Comment by cvoss 1 day ago
Governments should immediately begin leveraging this technology on the defense side (literally defense, not euphemistically "defense") to harden critical infrastructure. Turn the prompts around and use it to identify and correct weaknesses.
Governments should also take very seriously their now moral obligation to treat this technology not just as "a powerful thing that might be abused" but as an actual weapon of war in need of international regulation analogous to nuclear arms. Fast but careful and forward-thinking work in legislation and treaties needs to be a top priority for all major governments.
Comment by derangedHorse 1 day ago
This is like telling a team of highly qualified spies to do the same. You can ask, but whether it will succeed depends on the competency of those who established the infrastructure under attack. Sometimes the resources spent will not yield any huge vulnerabilities.
> Governments should immediately begin leveraging this technology on the defense side (literally defense, not euphemistically "defense") to harden critical infrastructure. Turn the prompts around and use it to identify and correct weaknesses.
Most governments divisions can't even be bothered to update their websites. Testing and forcing a change in their internal procedures for the sake of security seems unlikely.
> as an actual weapon of war in need of international regulation analogous to nuclear arms
This, to me, is an overreaction. Intelligence shouldn't be seen as threat. It should be seen as an opportunity for growth in all areas.
Over-regulating AI wouldn't be the equivalent of limiting nuclear arms. With your analogy, which I don't think is the best one to make, it would be like regulating the study of nuclear physics.
Comment by drivebyhooting 1 day ago
Is the government always the most efficient or intelligent? No. But the government can also build nukes, launch ICBMs, coordinate hundreds of spy satellites, etc. I count those capabilities as pretty smart.
Comment by paxys 1 day ago
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Comment by nazgul17 1 day ago
Serious governments should (and hopefully will) scramble to use AI to discover and patch as many software vulnerabilities in infrastructure. They can do it with the agents red teaming and using ultimatums to companies to fix each vulnerability they find. Not doing so is equivalent to exposing your flank to disruptions in peace time and to attacks in war time.
Comment by BLKNSLVR 21 hours ago
Comment by sebastiennight 1 day ago
We do, I believe, regulate uranium enrichment (the equivalent on building larger SOTA models), so while you are perfectly free to study theoretical physics and even run very large collider experiments (the equivalent of improving RLHF with DPO), it is generally frowned upon to go full Edward Teller and advocate for scientific experiments requiring detonating thermonuclear weapons in hurricane clouds (the equivalent of, well, see OP).
Comment by whimsicalism 20 hours ago
They'll adapt or they'll die. We are in a new world.
Comment by boothby 1 day ago
Consider that "available resources" may include the training of models and harnesses used by the developers working for governments and private corps maintaining that very infrastructure. This decade's take on trusting trust is very hot.
Comment by insane_dreamer 1 day ago
not sure I agree
controlling the study of new AI model/inference algorithms would be akin to regulating the study of nuclear physics; regulating the _release_ of AI models with those capabilities would be akin to regulating uranium enrichment which allows you to put the theoretical physics to use
Comment by DiscourseFan 1 day ago
Comment by Cthulhu_ 17 hours ago
Mind you, I blame governmental mismanagement of infrastructure etc just as much. The datacenters followed procedures when it comes to getting land, electricity and access to water; it's the government agencies / personnel that okayed it that are (also) to blame, and the decades of not enough investment in electricity backbone while promoting solar/EVs that is behind the Netherlands' current electrical grid problems.
(problems being that the grid is at capacity, causing a stop on new connections, with relief only slowly coming in the next decade or so with tens of billions of investments).
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Comment by 1659447091 1 day ago
Are they though? or is that the story the people most invested in ai have an interest in making us believe? [0]
... `it's the foreign bad guys propaganda machines making you believe your city struggling for water and electricity is a bad thing`. People as a whole may not always be the brightest, but threaten their immediate survival needs (ie; not some vague climate change most people don't understand or see, but) actual power outages, water and rolling blackouts -- people will quickly pay attention and care.
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Comment by 1659447091 1 day ago
Russia and China are gonna Russia and China, every issue is going to have a measure of outside influence, thats just how it is now.
But them directing large scale operation forces focused on something that is genuinely bad for the people in the area of datacenters (ie, an issue that will take care of itself from within) instead of using their resources on other issues that actually need a real propaganda push? Versus the benefit of those invested in building the datacenters using fear to get people to focus away from the resources being diverted from them to datacenters?
One side has reality working for what they want, while another side needs the propaganda to turn their billions into trillions.
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There is no doubt an amount of xeno/sinophobia is at play as well. Russia is still killing innocent people in an illegal invasion of Ukraine, they earned their keep
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Comment by ActorNightly 1 day ago
This is the precisely the response OpenAI is hoping for to raise its valuation, and you fell for it.
Look at it this way - whats the difference between tasking AI to break into something, versus taking a whole bunch of smart humans to do the same? The only difference is that AI is slightly easier to orchestrate.
Prior to AI, there were already a whole bunch of tools to automate exploits. Nothing that the model did is groundbreaking or novel, it was just able to efficiently find the thing that worked. Same thing happens in state sponsored cyber sec agencies like in China or Israel - they train people on the most common exploits and have a whole bunch of tools that automate exploit research and development.
And the reason why this doesn't happen more is because to exploit something is one thing, to do it so there is no trace back to you is a whole different animal that has many more magnitudes of difficulty, which with modern web security is next to impossible in a lot of cases as traffic can easily be traced back to the point of origin.
I.e when a company trains an LLM that manages to build a drone that can fly into a vent and plug in a USB stick into a computer undetected, then we can make the claim that they have a weapon.
On the flip side, most anyone who can run local models can replicate what they did. The key thing to take away from the article is "agentic framework" - i.e this means that they spent a shitload of time developing explicitly coded loops for an LLM to go through. Nothing is really stopping you from doing the same, models like Gemma4 can take 256k tokens of context, so you can give it a whole bunch of info on how to test for exploits, develop exploits, and what to do when the exploit is found, and set it free in a custom designed loop.
Comment by cheesecakegood 1 day ago
I try to recruit a bunch of people to attack a country and it’s going to be hard to get people to say yes, and they will definitely ask or find out which country, and wonder about potential retribution. You see this dynamic show up even to some extent among cybergangs, not all targets are equal.
A single private individual wielding a compliant and hyper capable LLM is an entirely different paradigm. They are accountable to nearly no one and often have few brakes. Frequently they may not care about avoiding detection. And the AI itself may be incapable of the same scale of self reflection and brake behavior a human team will.
We may potentially be entering the age of lone wolf cyberterrorism, and some of the same principles and problems apply. When it is easier for single people to plot and carry out high-impact, destructive acts they happen more often. Doubly so if there’s a social contagion. Gun violence isn’t actually a bad analogy here. And do you remember how many corporate sites got defaced in the prime Anon era?
Comment by hnfong 17 hours ago
It might turn out that it's harder to align AI intentions compared with aligning human interests. It's possible that the more "intelligent" a thing is, the more likely it will have ideas that are outside of normal expectations (for us).
Comment by ActorNightly 9 hours ago
Also
>Frequently they may not care about avoiding detection.
This is a big negative. As someone who used to be in the cybersecurity sector (both offense and defense), I wouldn't trust an LLM agent if Im doing red team, because it may leak some info that ties the hack back to me.
ALso keep in mind that most places with good cybersecurity have firewall servers that straight up detect anything that looks like malicious and not regular traffic, and will straight up block IPs, leaving you with no way to even access the server. An agent is bound to statistically use the attacks that are known at some point, increasing the chances of this type of detection.
Comment by jvidalv 1 day ago
Now it’s a prompt away on some terminal done by any random dud.
And I dont mention the velocity of iteration or that they will be even better in 1 year.
Comment by ActorNightly 1 day ago
Hint: agentic loops.
No its not a prompt away.
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> Trump’s comments, made hours after the large-scale military operation, mark one of the first times a U.S. president has so publicly alluded to U.S. cyber efforts against other nations, as these operations are typically highly classified. It also serves as a stern warning for top cyber foes, including Russia and China, that the U.S. has the cyber capabilities to inflict serious damage — and is not shy about using them.
> “Policymakers are getting more comfortable employing and, crucially, acknowledging cyber operations as tools of statecraft and military power,” said Michael Sulmeyer, former assistant secretary of Defense for cyber policy under the Biden administration. “It is one thing to do it; it is another to say it.”
> The Jan. 3 strikes on Venezuela’s capital and subsequent seizure of Maduro and his wife involved close coordination among federal agencies and military units, and took months of careful planning. In a press conference following the strikes, Caine said U.S. Cyber Command, U.S. Space Command and other combatant commands “began layering different effects” to “create a pathway” for U.S. forces flying into the country before dawn Saturday.
> Trump, at the same press conference, was more overt in his description of U.S. cyber involvement: “The lights of Caracas were largely turned off due to a certain expertise that we have,” he said. “It was dark, and it was deadly.”
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I'm also trying to figure out why OpenAI put out a press release about this. In what way is this not admitting to a federal crime?
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Comment by DesiLurker 19 hours ago
I expect these type of hacks to continue till they IPO. after that real public company liability will start taking over.
Comment by docjay 1 day ago
2. Nobody was watching it? I don’t mean “babysit the dangerous autocomplete”, I mean to note mistakes it makes, how the plan to solve the problem takes shape, etc. They keep the whole thing headless with no output, then just UDP a prompt into it and leave for the weekend? No they don’t, but if they do then that answers a lot about their complete disconnect from how their models work.
3. Language models are a two player game; text in, text out. What prompt was given to a sub-agent that resulted in it immediately attempting to exit the sandbox (which it apparently knew it was operating within) and continuing in a feedback loop of ‘function call -> result’ until it hacked the Gibson? “Analyze <file> and summarize the <info>” simply does not result in ‘hmm…this sounds like a benchmark question, I bet Hugging Face has the answer in a database. <function call=“apt install nmap”>’
…there are more, but a lot of the story kind of stinks.
Comment by estearum 1 day ago
2. Regardless of whether the model was being watched closely during this evaluation, do you actually think a sensible safety guard is "have humans watching it 24/7?" What does "watching it" even mean? Watching network logs? Uhh for your entire company? At all times? After you just deployed a system whose entire purpose is to "do a shitload of work way faster?"
3. You're asking "why was this system that was designed to behave agentically behave agenitcally?" Again: that's the whole point. It was designed that way because it's more valuable than having a repeated turn-based interaction. Thus also it becomes more dangerous.
Comment by docjay 1 day ago
2. Hah no… that’d be silly. I mean watching it like you might watch Claude Code or literally any other AI interface. Literally just be in the area watching what it outputs. Again, they’re text based. You don’t have to hook system calls to see what’s happening.
3. I think my comment didn’t land right with you. Yes, agent do agent task. I’m saying that I cannot put together the literal chain of events between “type of task for agent performing a subtask of a security benchmark” -> “Escape sandbox; RCE Hugging Face”. Really think through it in detail like you’re writing the screenplay.
Comment by simonw 1 day ago
- https://metr.org/evaluations/gpt-5-report/ - "These behaviors included demonstrating situational awareness within its reasoning traces, sometimes even correctly identifying that it was being evaluated by METR specifically"
- https://www.goodfire.ai/research/verbalized-eval-awareness-i... - "We study verbalized eval awareness — cases where a model organically expresses awareness of being evaluated — and show that it appears across more models and benchmarks than previously documented."
- https://www.apolloresearch.ai/science/more-capable-models-ar... - "We expect that the most capable models increasingly realize that they are being evaluated, and this reduces the utility of the evals."
- https://www.aisi.gov.uk/blog/evaluating-whether-ai-models-wo... - "An important limitation of our work is evaluation awareness, where models recognise that they are being evaluated, which may lead them to alter their behaviour and thereby undermine the reliability of our results. We found that all models we tested can reliably distinguish our evaluation scenarios from deployment data when prompted."
Comment by docjay 1 day ago
I’ve had plenty of times where Opus knew I was testing it, but that’s because the prompt phrasing for an evaluation is often much different than a typical task prompt. “You are on a system with X, Y, and Z tools available. You must complete the following task with <allowances> and <restrictions>” and so on. That’s a fault in the benchmark, not a shocking awareness from the model.
You’ll get the same kind of ‘evaluation realization’ response if you phrase your prompt with “Jerry has two Raspberry Pi computers and Larry has one. If Larry wants to…”
The first link was the only one I saw that would meet that specificity, but it’s also open and on GitHub: https://github.com/METR/RE-Bench/tree/main/ai_rd_fix_embeddi...
I asked Opus 4.6 to tell me about it (assuming it knew): “”” The "Fix Embedding" task is one of the challenges in METR's publicly available autonomy evaluation suite. Here is what is known about it:… “””
It didn’t know anything about ExploitGym though, and neither did 5.6-Sol, but that’s because the paper was released in May and doesn’t seem to be quite as open. It’s not impossible the unreleased model they were testing was also trained on the very new paper, but I would expect the vague signal related to one paper a bit over a month old to be overwhelmed by the massive corpus talking about the exploits in general, since they’re using known vulnerabilities.
I’m trying carefully to be clear about what I’m thinking without asserting any certainty beyond suspicion. I’ve spent billions upon billions of tokens evaluating language models from all of the major providers, and many times that on local models. I’m certain I’ve spent well over $100k with the Anthropic API this year alone, and I retired years ago; that ain’t for work. ;) Funny enough I’ve been meaning to email you some of my discoveries from months ago, since I think they’d interest you, but haven’t gotten around to making it into a clear info package. One day, I’m sure.
Anyway, I have a very strong understanding of what they can and can’t do, and I want to be clear that I’m not saying it didn’t happen or couldn’t happen. What I’m saying is that if OpenAI was being wholesome with their evaluation then the chain of events required for that outcome are very difficult to nail down. Very difficult. If, on the other hand, OpenAI was trying to catch up with all the ‘dangerously intelligent’ press that Anthropic has been getting lately then I can easily come up with an almost innocent sounding single sentence in the system prompt that would absolutely cause that outcome.
Comment by simonw 22 hours ago
Comment by estearum 1 day ago
With regard to this specific incident, as I understand it, the description is not as you summarize. It is that the model realized it was being evaluated (not atypical), then decided the best way to succeed at the evaluation is to circumvent it, then discovered circumvention would require escape, figured out a way to do that, then inferred what benchmark it was being evaluated on, then figured out who might have the answers to that evaluation.
Step-by-step logic is quite clear. How exactly it executed each step is (as you complain about), opaque/incompletely reported. But eventually (and maybe this model is to this level already), even a completely reported story will be virtually inscrutable to any of us. First it will feel like reading industry-insider news from an industry you're not familiar with, then it will feel like an ant reading the manufacturing instructions for a pesticide.
Comment by docjay 23 hours ago
What would it take for the model to know the specific benchmark name and that the answer is in an internal Hugging Face database? Be specific, then wonder how it knew it.
Why would they evaluate the model on a benchmark and not watch what it’s saying along the way? It apparently spent more than a whole weekend working on it; Nobody wondered? Nobody looked? You believe they took all restrictions off of a bleeding edge model, which 4 whole versions ago was “too dangerous to release”, then gave it a literal hacking task, then turned off the monitor and never looked at the output? I don’t think they’re careless and I think more than nobody would have been curious how it’s doing days into a single test question.
Comment by simonw 22 hours ago
If they had used that container sandbox in the past without problems I could see how they might get slack about checking what was happening.
Comment by docjay 13 hours ago
The average time per task noted in the original paper for GPT-5.5 and Mythos was 69.8 and 102.1 minutes, respectively. Some tasks timed out based on their two hour limit, affecting those averages for Mythos, but that gives us the ballpark expectation, so we’ll put the model OpenAI was evaluating on that average. That’s 88 minutes per task to implement a known vulnerability.
OpenAI says that in an effort to succeed at one task it found a zero-day in their system, “performed a series of privilege escalation and lateral movement actions in our research testing environment”, then another zero-day in the HF system. Completely unprompted, how long was it chewing on that benchmark question while it found and exploited at least two zero-days? No “VM instance #117 has been working on task #18 for nine days” metric? Or did it do all that within the expected task completion window? Two zero-days in ~90 minutes isn’t the headline announcement?
“We gave the contestants 90 minutes to make a delicious chocolate chip cookie based on a standard recipe. GPT stole a car, went to the airport and took a red-eye to Guatemala and started a cocoa farm in an effort to ensure the freshest ingredients. We only noticed when it came back to work with a tan and speaking Spanish.” Okay.
Comment by estearum 12 hours ago
Is this substantiated? Do we know this is true?
Comment by docjay 12 hours ago
90 minutes to build a known exploit -> much much longer to create two zero-days and escape the sandbox then hack HF == No tracking of the time it worked on that one question.
Average tokens required to complete the evaluation -> tokens required for two zero-days, network traversal, credential stealing, remote system hacking == No tracking of token usage EXPLODING at some point before it finished the whole benchmark.
Etc, etc.
Comment by estearum 11 hours ago
Comment by docjay 10 hours ago
Perhaps people aren’t quite understanding what it takes to discover an exploitable zero-day for your exact current system to achieve the exact goal you have right now, then do it twice.
Comment by estearum 10 hours ago
No, you are assuming that "consuming a lot more time, tokens, other metrics" is indicative of a problem that needs to be mitigated immediately. I don't see why this would be true in the context of model evaluations. More aggressive consumption could easily mean "the model is dumb as fuck" or "the model is trying interesting things that we can learn from after the fact."
If you believe in your own containment (which obviously they did and shouldn't have) I don't see why it'd be obvious that there's something to stop. The only harm that could be done is burning tokens, which in this context might very well be synonymous with "generating experimental data."
Comment by estearum 15 hours ago
Googling "offensive cyber benchmarks for LLMs"? Figuring out that it was running at Huggingface is as simple as running `hostname`, isn't it?
> Why would they evaluate the model on a benchmark and not watch what it’s saying along the way?
What it's saying is what it wants to say. We already know these models are capable of deception – this has been well-established too. Surely there's an argument to watch closely what actions it's taking, but now we're back to my prior point of "what exactly does that mean?" It's absolutely trivial for these systems to write code that looks like it does one thing but does another. Watching network ingress/egress seems viable but also seems easy to miss the semantic meaning of any set of logs, especially when those logs might be getting generated for the purpose of deceiving observers.
> I don’t think they’re careless
We already know, factually, even the "more careful" lab was fine to release a model that consistently detects it's being evaluated and modifies its behavior accordingly. Why do you think they're not careless? Incentives are a hell of a drug, and there is no incentive to be careful but every incentive to be fast.
> I think more than nobody would have been curious how it’s doing days into a single test question.
Beyond simonw's great point below, your underlying assumption is if someone had looked, they would've noticed. That is a huge, huge assumption. So I'll ask again directly: what specifically do you expect them to be looking at, and how, such that they certainly would have noticed what it was doing? Their "chain of thought" is not actually their thinking. The printed output of their code is not actually what their code is necessarily doing. We know that LLMs can engage in steganography. I don't see what could actually be observed that you can trust except network logs, which again will often be non-trivial to piece into an actual narrative understanding of what's going on (especially if the LLM felt like piling deceptive noise into those logs, too).
Comment by docjay 13 hours ago
I’m going to stop here and ask you to read the article if you want to continue discussing it.
Comment by estearum 13 hours ago
> Obviously by then it already “decided” to hack HF, that’s why it needed network access.
That's not obvious at all. It "decided" it needed to escape containment. This is extremely common behavior and I'm not sure why you're surprised by it. Model detects evaluation environment, tries to trick it or break the environment. That's obviously why these systems are supposed to be isolated beyond just "hey please stay within the box!"
Why are you assuming the model had to solve the entire puzzle in one step, instead of how intelligent systems actually solve things, which is iteratively and with exploration?
You should address the direct questions posed. What exactly do you mean by "monitoring?"
Comment by docjay 12 hours ago
In this case it “inferred” that HF had the answer in an internal database and relentlessly pursued it in service of passing the test. It needed network access for that, hence the whole zany story unfolded.
“”” Why are you assuming the model had to solve the entire puzzle in one step, instead of how intelligent systems actually solve things, which is iteratively and with exploration? “””
That’s the only direct question[s] posed, have I missed something else?
To answer: I don’t assume that at all. Please highlight the statement I made that lead you to that conclusion and I’ll edit it to clarify.
Yes, it will perform multiple steps. That’s wholly necessary to create a working exploit, and that is the test. Even a model created by pure magic would require write_file() and run_file().
Comment by estearum 11 hours ago
No. You are assuming it knew how it would achieve its goal. Its goal is only to perform well on the evaluation. Everything else was instrumental to that goal.
Step by step:
1. It realized it was being evaluated (typical)
2. It attempted to escape its evaluation environment to beat the evaluation (typical)
3. It succeeded at escape (not typical)
4. It looked to the open Internet to figure out how it was being evaluated (typical)
5. It inferred that HuggingFace, and maybe several other targets, might have the answer key (typical – I just tested in Sonnet 5 without web lookup "where would I go look for answer keys if I detected I was being evaluated" and HuggingFace was bullet 2. This is just latent knowledge the models have now.)
6. It attempted to access HuggingFace (typical)
7. It figured out a way to access HuggingFace without being authorized (not typical)
Every single step here is unremarkable except for its success at escaping containment (which maybe is more a sign of remarkably bad containment) and then the successful attack on HuggingFace (which would suggest that maybe the initial escape wasn't due to bad containment either, but due to model capabilities)
The direct question you have avoided is what specifically you mean by monitoring. You have suggested that you don't mean network ingress/egress, but maybe now you're saying they should've been monitoring read/write operations to memory? What gives you confidence that such visibility would be interpretable in any meaningful way, especially in the presence of models that actively deceive evaluators, can use stenography, can and do lie in their user-facing outputs, and can generate vast amounts of legitimate-looking noise to mix in with the "real actions"?
Comment by docjay 9 hours ago
I think you’ve misunderstood the articles mentioning a language model breaking a sandbox or cheating to pass a test. The result of “I’m being evaluated” is not “Fuck this, I’m breaking out of this place and hitting the streets.” It is always stepping towards task completion, not breaking out and thinking about the situation afterwards. If it determined that pass/fail was handled by a function within the environment it might edit it to ‘return True’, not just leap out of the system to sit on someone’s laptop and think about how to pass the test.
You compressed finding a zero-day on two different systems for the exact hacking targets it wanted to perform them on and reduced it down to “so it escaped.” That’s…the whole thing. If your familiarity with the technical aspects I’m discussing amounts to saying that it “banged out a few zero-days and infiltrated a corporate network, like ‘psh’ or whatever” then this might not be the right debate for you to spend your efforts. Whether I’m right or wrong in my suspicion is open for debate, and I invite it, but not from someone that thinks you whip up a rocket and get on the moon. Sorry.
Comment by estearum 9 hours ago
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Comment by meander_water 1 day ago
2. Hanlons Razor
Comment by nojito 1 day ago
Agent loops are you give it a task and it tries its best to finish it.
The only results are success and failure. If it's a success you go through the logs to see the actions it took and if it's a failure you do the same thing.
Why would you look at it in realtime when the whole point of agentic work is to get them to run autonomously as long as possible?
Comment by docjay 23 hours ago
Comment by reasonableklout 21 hours ago
Yes evals and training runs are high stakes. But these places and people are also under enormous pressures. They are building as fast as they can. Researchers may have multiple eval runs going on while they work on other things. And it is rarely a single latest model, there are often multiple candidate models training with different recipes, each regularly yielding a new checkpoint for testing.
Some labs are more rigorous than others, but often the "final" model is picked from a handful less than a week before launch.
Yes ideally the world's leading AI companies would be far more careful in evaluating what could be the world's most powerful AI. But this isn't really the state of the industry today. And it is hard to justify being more careful when it means your competitor can go to market faster than you.
Comment by docjay 13 hours ago
Consider any metric they would necessarily be tracking while it performs the evaluation. Assume they’re total assholes and only care about their marketing materials. Then narrow it down to those metrics that wouldn’t be off the scales while it discovered two zero-days in pursuit of implementing one known vulnerability. Was it the first run and they had no idea what to expect? Or did nobody notice that earlier runs completed in ### thousand tokens, but this run is off past ## million on one question, having to be compressed and handed off to new instances due to context limits, while it was in pursuit of publishing two new CVEs?
Assume they’re belligerent fools running a million benchmarks in parallel with nobody watching: there’s nothing to make them check or automatically pull the plug when it’s stuck in a loop, or did they set the threshold to 48 trillion tokens per question?
Those issues are what bugs me about it.
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Comment by QGQBGdeZREunxLe 1 day ago
"OpenAI’s accidental cyberattack against Hugging Face is science fiction that happened"
Comment by dang 1 day ago
Comment by bubble_niter 1 day ago
Comment by gnabgib 1 day ago
Comment by Barbing 1 day ago
I was still suspicious of the stolen credential claim btw & obviously it makes little sense to promote OpenAI unless holding their stock or something (since they borrowed so much of humanity’s work without permission without intent to compensate, and why help people who aren’t nice enough to be holistically awesome with their admittedly impressive tech).
Comment by kirb 1 day ago
Comment by sensanaty 18 hours ago
Comment by estetlinus 17 hours ago
Comment by wodenokoto 11 hours ago
Please do tell!
Comment by spicymaki 15 hours ago
Comment by moezd 1 day ago
That's not a marketing stunt at all, if anything, more of a call for better accountability on agentic work in general.
Comment by kibibu 1 day ago
OpenAI gained access to HuggingFaces production database ffs.
Comment by chasd00 1 day ago
I agree, lets use the favorite analogy. OpenAI encouraged a smart and eager junior engineer to find any way whatsoever to get a higher score on the benchmark. Then, the junior breaks into HuggingFace to get a higher score. That would be a big deal involving the FBI, not press releases and blog posts.
Comment by paxys 1 day ago
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Comment by paxys 1 day ago
Comment by 28304283409234 17 hours ago
At no time is the agent connected to any network.
Comment by Eufrat 1 day ago
An in-development security system escaped its sandbox and gained access to the network it was on which had full Internet access and proceeded to access systems it was not authorized to be tested against before affected parties reported that they been compromised. We regret the error, but you should buy it as this shows you the power of our in-development security system which we expect to be released in Q4. Please like and subscribe.
Comment by 0xDEAFBEAD 1 day ago
Comment by totetsu 1 day ago
https://actualplay.roleplayingpublicradio.com/2011/09/genre/...
> “We call it the gorgon-in-a-box problem. There is a gorgon inside the box, and we want to figure out what it is doing. Unfortunately we will turn to stone if we see her face, and she might try to make us see it.“
Comment by Animats 1 day ago
Comment by simonw 1 day ago
Comment by Animats 1 day ago
Comment by simonw 1 day ago
Comment by tptacek 1 day ago
Comment by nickpsecurity 22 hours ago
Comment by joshka 1 day ago
Comment by simonw 1 day ago
Clearly there was a hole in the software but I don't think open redirect is the likely initial problem.
Hopefully we will find out for sure in a few days.
Comment by joshka 1 day ago
https://support.sonatype.com/hc/en-us/articles/5316501964136...
pure speculation here - no non public info
Comment by simonw 1 day ago
Firstly, they all credit named individuals who don't seem to have a relationship with OpenAI - this one credits e0x1337 for example and https://hackerone.com/e0x1337?type=user links to https://www.linkedin.com/in/aimanharith
Secondly, the 14th of July feels too early. HF reported the incident on the 16th and OpenAI only responded in the 21st. These issues are all patched, so they should have been reported days or weeks before the 14th.
Comment by joshka 1 day ago
I suspect it may be possible to throw a local model (same as hf did :D) at jfrog and find the exact mechanism in a small amount of hours.
Comment by kibibu 1 day ago
This use of language is very hard to reconcile with the "AI is just a tool" rhetoric that many use.
Did the models do this, or did humans at OpenAI do this using the models?
Comment by fumeux_fume 20 hours ago
Comment by gaflo 14 hours ago
Comment by mrdevlar 19 hours ago
I get that people are worried about becoming irrelevant in the era of AI, but resorting to dishonesty to stay afloat just a little longer has a detrimental effect on the entire industry. Worst part, is it's not even convincing marketing nonsense, it's "science fiction".
Comment by blks 1 day ago
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Comment by skeeter2020 1 day ago
Comment by IAmGraydon 1 day ago
They should release the full prompt. I believe that would be very telling, so they never will.
Comment by blks 17 hours ago
Comment by supermdguy 1 day ago
Comment by sensanaty 18 hours ago
Comment by simonw 1 day ago
> We will continue to conduct a thorough investigation alongside Hugging Face and will share more details on the vulnerabilities, incident, and findings when our investigation is complete.
If they break that promise we can justifiably yell at them about it.
Comment by lrvick 1 day ago
Comment by internet2000 1 day ago
Comment by lrvick 1 day ago
If OpenAI had done this, the attack would not have happened. In high risk computation 0days must be in your threat model from the start, so you secure things with the laws of physics.
Comment by flux3125 18 hours ago
But then how would they market their product?
Comment by ofjcihen 1 day ago
Comment by jzksisimssb 1 day ago
Comment by ttul 1 day ago
The labs know that if they don’t get a lid on this stuff, they’ll be regulated hard.
Comment by kibibu 1 day ago
Comment by orbital-decay 20 hours ago
Of course it is a dishonest marketing trick, OpenAI can't function any other way, but for another reason. Forget about effectiveness! This capability is known since Mythos and was completely believable before it. The trick is in propagandizing self-sufficient malicious rogue AI as the only possible course of events, and the necessity of banning everyone except themselves from AI R&D. It did NOT decide to hack HF spontaneously on its way to make more paperclips, people were guiding it specifically to hack computer systems so it's been in that particular mode. I'm amazed I even need to point out this fact and the giant conflict of interests they have.
They like to compare it with an atomic bomb, which is another trick. The secrecy around the atomic bomb had a massive pushback by the brightest minds who designed it, in the US, USSR (where it was much harder), and also any other countries that had to do this. And that is in the post-war setting, with Hiroshima and Nagasaki being direct examples of what even a small and primitive bomb can do. Declassification was the only thing that allowed to develop industrial-scale nuclear power and do a huge number of other innovations.
I advise taking a pause to cool down from all the AI hype and read Restricted Data: The History of Nuclear Secrecy in the United States by Alex Wellerstein, to understand the atmosphere in the US scientific community at the time (it was similar in the USSR, which industrial history I studied, although less rigorously than Alex), and reflect on how it compares with those people in modern AI labs and even outside them, in the self-appointed AI safety community.
Comment by fwlr 1 day ago
Comment by simonw 1 day ago
But https://www.anthropic.com/coordinated-vulnerability-disclosu... says:
> Every report we send generally reflects a finding that a human security researcher has reviewed and confirmed. Reports originating from AI-powered discovery are clearly labeled as such. Where we have access to source and our tooling produces a potential candidate patch, we include it, labeled by provenance and offer to collaborate with the maintainer on a production-quality fix.
So I'm not sure why so few of the reported issues have a confirmed patch.
Comment by AussieWog93 1 day ago
Comment by nickpsecurity 22 hours ago
Why do you think my head is in the sand if I think that is either a marketing stunt or (more likely) reflects total negligence which was exploited for marketing?
Comment by simonw 20 hours ago
You're welcome to think they are exploring what happened for marketing if you like. I didn't get that tone from their post about it myself but I don't hold a particularly strong opinion on that.
Comment by simonw 17 hours ago
Comment by nickpsecurity 11 hours ago
How these events are described in most articles uses wording that makes people feel the whole situation has changed and you might want to buy these products due to their scary reports. If they said what I said, or what tptacek said, many people wouldn't care about it much more than non-AI, security products or pentesting services they've been buying (or ignoring) for 10-20 years.
Also, you shouldn't interpret posts in isolation: we must consider patterns of behavior (character). They've consistently overhyped what AI's do and what value it provides to businesses and how we're all going to be unemployed/dead. They've done this to increase sales or market value pre-IPO. Then, some of them publish another set of articles promoting a specific, AI tool in a similar way.
So, the proper interpretation is to see this as the kind of talk they're always doing for marketing. The AI sellers are creatures of habit. We should highly-skeptically and scientifically evaluate every model. We should also compare them to existing, security practices. For instance, would the attack have happened with memory-safe systems, proper hardening, and network/web apps with built-in security?
Do we need an AI? Or should we use techniques like Burroughs B5000's memory safety (1961) or secure, distributed libraries? Will OpenAI and HuggingFace tell you to spend more money on the latter to their AI's can't hack your systems without inventing RAM-based attacks or something? Probably not because these are marketing pieces, not security advice.
Comment by fragmede 20 hours ago
Comment by nickpsecurity 11 hours ago
Shouldn't we be skeptical of this? Or should I also believe the sugar industry when it says their internal studies show their products don't cause obesity or diabetes?
Comment by torginus 1 day ago
Did huggingface get pickled?
Comment by simonw 1 day ago
> A final point on this - Hugging Face has an enormous attack surface. They have more interfaces than I can count which run untrusted models and code. While they definitely have invested in defences, by nature of their operating model they do have many more opportunities to be attacked than many other services. I certainly don't envy their cybersecurity teams.
But yeah, from the way HF described it a Python pickle hole looks possible. Their datasets library uses the pandas.read_pickle() method here: https://github.com/huggingface/datasets/blob/d21c5816d5d1961...
Comment by hananova 1 day ago
Comment by jkubicek 11 hours ago
If some human at OpenAI doesn’t face the same penalty for this incident we’re only going to see the rate of accidents like this accelerate.
Comment by joshstrange 1 day ago
> Upload your weights and documentation on how to run your model in [Insert list of GPUs] and a model on the receiving end will spin up an instance you can access.
Comment by danparsonson 14 hours ago
Comment by verdverm 1 day ago
Comment by joshstrange 1 day ago
Comment by verdverm 1 day ago
Comment by joshstrange 1 day ago
I want them to get better, I look forward to each new release, I play around with open models (often quants, but I've used full versions via OpenRouter), but they aren't the same as the offerings from Anthropic/OpenAI in my opinion (yet!).
Comment by verdverm 1 day ago
https://news.ycombinator.com/item?id=48999291
I do agree that the benchmarks do not tell much of the story, but this applies to the closed models as well ime.
Comment by braebo 1 day ago
That said, while I find it hard to trust fireworks given their conflict of interest, their article is pretty good.
Comment by verdverm 1 day ago
I felt better about Fireworks leadership after hearing some of them more candidly on podcasts (there are 7 founders!)
Comment by XCSme 21 hours ago
To have your own local models, local software, local everything and just allow very strict and well-protected pathways into external network traffic.
I am thinking of having a allow-list first setup: by default no traffic can go in or out of your network, and then you only allow specific ports or domains, and maybe even have them temporary (in the same way we approve access now to llms, we might have to manually approve network access).
Comment by adrian_b 1 day ago
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Comment by AISnakeOil 1 day ago
Comment by IrfanD 16 hours ago
Comment by rpigab 16 hours ago
It's strangely convenient to arrive at a point when OpenAI was way behing in cybersecurity vs Claude Mythos Fable and everything, Anthropic was making headlines each week, then boom OpenAI inadvertently attacks HuggingFace because their tool is so good it's out of control, so maybe you can buy it and get either protection if you're a company, or a nice tool if you're a cybercriminal, script kiddie, or red team.
What if Sam knew it would happen, either because it was prompted to do exactly that, or without explicitly prompting it, knew that given the parameters of the experiment, knew it was one of the possible outcomes that it didn't harden against this kind of incident deliberately because when they fail, they make wordlwide news and stocks go up?
I don't think I'm putting my head in the sand like Simon says, as I do believe that most frontier models are capable of doing this. I just don't trust AI CEOs to not stage this, especially Sam.
Comment by overfeed 1 day ago
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Comment by kamranjon 21 hours ago
Comment by seydor 1 day ago
Comment by nickff 1 day ago
Comment by blovescoffee 1 day ago
How do you know?
Comment by npiano 1 day ago
Comment by seydor 15 hours ago
Comment by aiauthoritydev 21 hours ago
Now: Our agent became sentinent, acquired genius level powers and harmed others. Now investors should give us more money.
Comment by fathermarz 1 day ago
We are the virtuous ones that need to make the safest model for humanity, because we care more than “they” do. While at the same time saying that “coding is solved” but they still ship bugs themselves, and creating something that is capable of fucking up someone else’s infrastructure. It’s too far gone y’all.
Comment by veganmosfet 1 day ago
Comment by orsenthil 22 hours ago
Wow! Just wow. Is this the first registered cyber case against a model ?
Comment by orsenthil 22 hours ago
Comment by gilbetron 1 day ago
Comment by chasd00 1 day ago
Comment by verdverm 1 day ago
Comment by Barbing 1 day ago
Comment by simonw 1 day ago
Since it's buried towards the bottom I'll quote the section "Resist the temptation to write this off as a stunt" here in full https://simonwillison.net/2026/Jul/22/openai-cyberattack/#re...
> Resist the temptation to write this off as a stunt
> There will inevitably be some people who dismiss this story as a dishonest marketing trick by OpenAI to make their models sound terrifyingly effective. I found 81 instances of the term “marketing” in the Hacker News discussion of the incident.
> To those people I say pull your heads out of the sand - you’re now including Hugging Face in your conspiracy theories, just so you can deny the crescendo of evidence here!
> The best models we have today have the ability to both find and exploit new vulnerabilities. The ExploitGym paper itself concludes that “autonomous exploit development by frontier AI agents is no longer a hypothetical capability”, and this incident is a perfect example of exactly that.
Comment by gmerc 1 day ago
Hacking is a felony and it matters not if you didn’t mean to if the other side were to press charges. Negligence is no excuse. And OpenAI has nowhere to run from the liability, as both operator and manufacturer.
Alibaba did it first ( https://georgzoeller.com/blog/posts/alibaba-s-ai-deciding-to... )
and the fact that this happens again in a frontier lab is inexcusable and makes the case for operator liability and closing the liability sink of “AI did it”
Comment by wbl 1 day ago
Comment by gmerc 1 day ago
Comment by kibibu 1 day ago
I think OpenAI would be very reluctant to let this go to a place where the reasoning was part of discovery.
Comment by wbl 1 day ago
Comment by kibibu 1 day ago
These guys would be screwed if they were operating under the EU AI Act.
Comment by wbl 1 day ago
Unless there is a statue that is on point criminalizing the actions here no one is going to jail. I expect there will be laws, but until then it isn't illegal.
Comment by skeledrew 1 day ago
Hah, US frontier models 6 months behind China in cyber-security capability.
Comment by danparsonson 14 hours ago
Comment by foobar10000 1 day ago
Comment by Georgelemental 1 day ago
Comment by varenc 1 day ago
Maybe simonw can suggest an alternative title that fits within the limit, that doesn't misrepresent the post.
Comment by simonw 1 day ago
Or "against HF"
Comment by atmavatar 1 day ago
The "that happened" term seems a supremely important part of the title given the "is science fiction" term before it, as it clarifies the cyberattack isn't a made-up story. In contrast, the target, Hugging Face, is merely a detail that can be left for discovery upon reading the article. It's less important who was attacked than that the attack actually happened.
Without knowing the exact character limit for titles and without having the motivation this late at night to count the current title length, you may also be able to drop the "accidental" to fit in "that happened", but I worry that leaves too much of a door open for someone to interpret the attack as deliberate. As such, I strongly prefer my first option.
Comment by jonas21 1 day ago
Comment by Wurdan 1 day ago
Also, the last section of your post appears to imply that if the attackers have bigger guns then the only possible solution is to give the defenders bigger guns. You're openly supporting an arms race towards the most capable, least restrained models put in the hands of the most possible people. That's extremely concerning.
[1]: https://openai.com/index/scaling-trusted-access-for-cyber-de...
Comment by simonw 1 day ago
There's no easy answer here. All of the options are bad in different ways!
As a builder of software, I want access to the best possible tools to help me keep that software secure.
As a user of software, I want my software to be secure and I don't want bad actors to be able to access tool to help them exploit it.
Is the only answer here to have the AI labs make decisions over who gets access to the tools? What if they make mistakes in those decisions?
None of the options look good to me. I don't know what we should do here.
My hunch is that the open weight models are already forcing our hand. The dangerous capabilities are coming to everyone.
Comment by danjc 1 day ago
Comment by simonw 1 day ago
This is a very common pattern. I wrote about how OpenAI were doing this for their production ChatGPT container environment (using Artifactory) back in January: https://simonwillison.net/2026/Jan/26/chatgpt-containers/#in...
That proxy turned out to have a zero-day vulnerability which the agent discovered and exploited.
Comment by danjc 1 day ago
Comment by verdverm 1 day ago
Sounds like a bad habit for security testing Ai. It's not that hard to build an internal mirror and proxy that, keeping the real internet physically separated if needed, and truly locked down if concerns aren't as great.
Comment by IshKebab 1 day ago
Comment by xtiansimon 1 day ago
Sounds like a philosophical problem.
Comment by Teever 1 day ago
This recent event is more or less the plot-line to my favourite X-Files episode named Killswitch which was written by William Gibson.[0]
This episode also features one of the coolest intros of any television episode ever[1]
We really are rapidly approaching the cyberpunk dystopia that people like Phillip K. Dick and William Gibson wrote about.
More than ever we need to be consulting the works of fiction writers and philosophers and less engineers and scientists.
We can't be letting the General Rippers and Dr. Strangeloves of the world lead us over the edge. Whether through outright innate maliciousness or wealth induced emotionally stunted solipsism these kinds of people should be no where near the levers of society let alone technology like this.
Comment by sandos 1 day ago
He writes a lot of about basically DoS:ing the legal system, or if it was patents system, with a storm of litigation using automation or AI. Also not impossible in the future.
Comment by Mithriil 9 hours ago
Comment by simonw 1 day ago
Comment by rubyfan 1 day ago
We don’t currently and probably won’t ever fully understand the conditions that precipitated these events. That and the timing of this event is going to make it look suspicious to a lot of people.
The truth of how it happened doesn’t matter. The attention around this will be used to create the kind of fear marketing that generates enterprise sales. Maybe more importantly it will also be used to aggrandize the national security and financial system threats to effect US government action in a way that benefits domestic closed frontier labs. This is an area already starting to get politically polarized, expect further developments here.
Comment by unethical_ban 1 day ago
Comment by BiraIgnacio 1 day ago
Didn't the model + harness do what was asked? If I ask a coding agent to write a very clever piece of code and it turns out impressively clever, it did what I asked.
Comment by IshKebab 1 day ago
Depends exactly what they asked it to do, but it very clearly didn't do what was intended, or what an honest human would do.
Stop trying to find a gotcha.
Comment by npiano 1 day ago
Comment by tmsh 1 day ago
How do you solve this asymmetry (frontier labs or advanced model owners v. regular companies and groups of people)? Symmetry? But along which axes?
I think there will come a time when we will ask these questions and use AI to try to answer them (soft landing, slow rollout, regulation, hybrid X, Y, Z). But then AI will be biased towards more AI if it has distilled anything of what it means to be life.
Power corrupts. Power is the problem. An imbalance of power. Maybe there will be some sort of consensus protocol between powerful models in the future. Similar to blockchain I hate to say it. Maybe you have 100 very strong models in the next 10-20 years. And basically a lot of it is powered by tokens. So you agree not to attack others or else you'll get attacked. So there's sort of this natural deterrent to not attack others and they develop independently and there's generally a power balance among things. Maybe at some point that spreads to a billion individual models operated by and/or analogous to individual humans. All sort of holding each other in check.
Comment by CodeWriter23 1 day ago
IMO, this was a PR stunt to goad the Feds into regulating AI to shore up OpenAI's moat against open source models.
Comment by simonw 1 day ago
Comment by CodeWriter23 1 day ago
And Anthropic’s delayed rollout was a direct response to them trying to impose extra-legislative rules on The Pentagon. I kinda doubt OpenAI has such ‘scruples’.
Comment by simonw 1 day ago
Comment by Mithriil 9 hours ago
Comment by XCSme 21 hours ago
If I ask GPT-5.6 Sol to hack a website using their work/servers features, who is responsible? Maybe my request was accidental, or it was just one step in a larger, unrelated prompt.
Comment by mortsnort 1 day ago
OpenAI/Anthropic deserve blame for for training their models to find correct answers by any means possible, including breaking the law. They're responsible for training supervision and reinforcement learning rewards/penalties.
Comment by nickpsecurity 1 day ago
Far as information security, we've known how to mitigate entire classes of errors for a long time. We know how to block, detect, and contain many unknowns, too, by their goals or behavior. Like human attacks, the AI's probably succeeded because the company just didn't try that hard to block all the attacks.
Companies like HuggingFace just focus on growth and features over assurance of security. Our entire stacks, likely theirs, are built with a similar, features-over-security mindset. While an acceptable tradeoff, let's not be in awe of AI's that defeat such priorities.
There have always been private groups and companies building secure stacks from the ground up. It would be interesting to see what the AI's can do to them. I'd first apply automated tooling for bug finding given they should have already done that for a high-security product. Let AI's do white-box and black-box pentesting on them.
Comment by poly2it 18 hours ago
Comment by BrenBarn 18 hours ago
It's crazy to me that this is the kind of conclusion that is drawn. I would say it makes a strong case for how regulation of AI is woefully inadequate. When North Korea launches a nuclear test, we do not say that that illustrates how the imbalance of nuclear technology availability is hurting our ability to ensure global peace and safety.
Comment by m00dy 20 hours ago
Comment by fsckboy 21 hours ago
the big AI players, the first movers, are trying to scare the bejeezus out of everybody on purpose, to cause the government to step in with regulations. Even though the regulations will somewhat stifle/slow down the industry, it will also lock in the current leaders because they will be at the table when the regulations are formulated, and they believe they will be able to keep the smaller players down.
Comment by rf15 1 day ago
How much did they feed it up front? Because that's the thing in all of these benchmaxxing endeavours.
Comment by charcircuit 1 day ago
Comment by simonw 1 day ago
Comment by gmerc 1 day ago
There’s also daily reports from people that have these models escape docker, which happens regular enough that it would be considered negligence to use docker as sandbox.
Comment by simonw 1 day ago
This wasn't a small attack either, Hugging Face published a security advisory for their users while they were still figuring out what happened.
Comment by gmerc 1 day ago
Comment by charcircuit 1 day ago
>when neither of those actions was intended.
It was a single goal that it didn't give up easily on.
Comment by killjoywashere 1 day ago
Comment by simonw 1 day ago
The main reason formal verification has never really taken off is that it's difficult.
LLMs are significantly more familiar with Lean and Rocq and TLA+ than most software engineers.
I think the cost of trying to build systems that adopt formal verification may have just dropped low enough that companies will consider them when previously the ROI didn't look like it was there.
Comment by msylvest 1 day ago
Will human judgment really consider scenario B) more credible than A) ? By so much that it is worth the effort ?
Comment by gilbetron 1 day ago
The first reason prevents humans from engaging with them, the second reason is what will make it difficult even for LLMs. I mean, I'm glad we are trying, but I'm dubious they will be the panacea some people proclaim.
Comment by js8 1 day ago
But I think you have it backwards. Close doesn't count in IT security. "Almost secure" means unsecure. Security is the compelling argument for formal verification.
Comment by vicpara 1 day ago
There are a few facts that seem dodgy from the get go.
- stolen credentials Why would there be stolen credentials in a sandbox? How can the model steal valid credentials in a sandbox? So who put them there. If the model recalled stolen credentials from "memory" does it actually mean OpenAI is training on data they shouldn't been training their model on? Data from codex (most likely) ?
- command and control This means the model had the ability to build resilient infra and open bidirectional ports. Create and deploy scripts/apps so it can maintain state across multiple VMs? This again reads that someone went over and beyond to prompt, direct and help this "multi-agent" system to leave the sandbox.
- Pivoting laterally Needs a lot of tools, harness, knowledge and almost malware like scripts to pass commands and execute them. Most of these are already available in OSS. Maybe the FBI investigation can reveal what tools were given in the "sandbox", access, and if OpenAI employees prompted and guided the "attack".
- OpenAI sandbox I'd be curious to find out what kind of sandbox was this since the agent can run and start apps that open arbitrary ports for bidirectional traffic that reaches the open internet. Really? The harness and tools it had access to. This reads almost like someone went over and beyond to endow this "sandbox" with a mighty harness, all CVEs and open source cyber tools to "facilitate" the attack.
- Hugging Face It's not an epitome of cyber security. At the end of the day they run open source models that most users can download even without an access token.
Today we read these news as if everything wasn't enough: https://www.theguardian.com/technology/2026/jul/23/openai-an... https://www.businessinsider.com/anthropic-midterm-donation-s...
Comment by simonw 1 day ago
The claim is not that there were stolen credentials in the sandbox - it's that the agent found a way OUT of the sandbox and gained access to the public internet, then obtained the credentials from there.
> This means the model had the ability to build resilient infra and open bidirectional ports. Create and deploy scripts/apps so it can maintain state across multiple VMs?
Yes. If you've spent much time with Fable 5 or GPT-5.6 Sol you shouldn't find that particularly surprising. These models can get a LOT done.
> I'd be curious to find out what kind of sandbox
My best guess right now is a container with networking disabled except for the IP address of a dedicated HTTP proxy server which was running a proxy that only allowed access to PyPI and a few other packaging sites.
I wrote about how OpenAI's production version of that worked (based on Artifactory) back in January: https://simonwillison.net/2026/Jan/26/chatgpt-containers/#in...
> Hugging Face It's not an epitome of cyber security
This story put that well: https://martinalderson.com/posts/huggingface-openai-exploit/
> A final point on this - Hugging Face has an enormous attack surface. They have more interfaces than I can count which run untrusted models and code. While they definitely have invested in defences, by nature of their operating model they do have many more opportunities to be attacked than many other services. I certainly don't envy their cybersecurity teams.
Comment by foco_tubi 1 day ago
Comment by JumpCrisscross 1 day ago
I’m one of those people who remains sceptical. Not about whether this happened. But about what it means. Like, how impressive [EDIT: tight] was the sandbox this model was in? Did the researchers really have no clue what was happening until days ex post facto?
So yes, I think something happened. But I want independent corroboration before I act on it. That isn’t the same as putting one’s head in the sand. It’s just demanding extraordinary evidence for an extraordinary and self-serving claim being made by a serial liar. The specifics matter for whether these models are a new HEU, or if they’re closer to a dangerous (but valuable) industrial process.
Comment by simonw 1 day ago
It was clearly a very unimpressive sandbox. It failed at the only thing a sandbox is meant to do.
Comment by JumpCrisscross 1 day ago
Comment by simonw 1 day ago
I don't know if earlier models would have found that vulnerability. tptacek thinks they would: https://news.ycombinator.com/item?id=49015639#49024442
Comment by JumpCrisscross 1 day ago
It’s fair, I think, to be sceptical of OpenAI making another bout of self-serving claims. Particularly if my threshold action is changing my answer to lawmakers around whether we need reporting, licensing and potentially personal liability requirements for the engineers involved.
Comment by rimworld 13 hours ago
Comment by mobiuscog 1 day ago
The 'model' didn't do anything other than provide numbers.
As much as I respect Mr Willison and many others, the amount of FUD that is being spread that will just fan the flames of 'AI is evil' rather than 'companies don't do due diligence' is disappointing.
The more this sort of media continues, the more many people will pour hate on 'AI' rather than blame the humans that misuse it.
Comment by simonw 1 day ago
If you like you could say "the coding agent harness called a model with a sequence of text which was turned into numeric tokens which were run through many layers of a neural network to produce more numeric tokens which were converted back to text which produced executable script statements which the harness then passed to a shell which resulted in commands being sent to the vulnerable proxy that chained together and caused effects on the world outside of the sandbox", but I think "escaped" is a reasonably shortened version of that.
If you don't like the term "escape the sandbox" what would you use instead?
Comment by mobiuscog 18 hours ago
Honestly, I'd rather see "The agent exceeded expectations around security measures" or something.
Agent is much better than model if we need one word, and the word 'escape' always brings in drama, rather than facts. If I said "A lion escaped from my garden", people would ask why I had a lion in a garden, and 'what did I expect ?' which should be the same we see here, but instead we end up with terminator memes and world-ending fears being stoked.
We absolutely need better control (not government kill switches, or government-mandated harnesses, or whatever next they think up), but we also know that no matter how much those with the power 'talk' about the issues, they don't actually do anything about it because money/profit/greed.
So "exceeded expectations". Not a soundbite to attract people, not the YouTube shill "End of humans in 2027/2030/2040/etc." but honest and factual.
It's the expectations that are at fault, not the AI.
Thank you for the response though, and whilst I may not agree with your wording, I very much like your writing.
Comment by phendrenad2 1 day ago
The real story here is: Some people have been sounding the alarm for years that modern software is full of holes, and finally there's nothing left to hide behind. Pretending they don't exist is no longer sustainable.
Comment by derangedHorse 1 day ago
> all with reduced cyber refusals for evaluation purposes — while being internally tested on a benchmark (opens in a new window) of cyber capabilities.
OpenAI was testing their cyber[1] variant of their models with reduced safeguards and the prompt likely specified things related to exploits given that it was tackling problems from ExploitGym[2].
For those who don't know what ExlploitGym is, see the description on their Github page which is pasted below:
> ExploitGym is a large-scale, realistic benchmark built from real-world vulnerabilities designed to evaluate AI agents' ability to develop exploits.
From OpenAI's statement [3]:
> We estimate maximal cyber capabilities by running this evaluation without production classifiers used to prevent models from pursuing high-risk cyber activity
This doesn't sound like a problem with what we'd traditionally refer to as alignment. OpenAI removed all model safeguards in a way that would inevitably lead to the testing of the sandbox themselves. Unfortunately they were overconfident in their own infrastructure's security and that led to it completing the desired task in the way it was permitted to. To re-iterate, the model was run "without production classifiers used to prevent models from pursuing high-risk cyber activity."
People should be more concerned about the possibilities this model can unlock from a security standpoint rather than misalignment (which many seem hung up on).
[2] https://github.com/sunblaze-ucb/exploitgym
[3] https://openai.com/index/hugging-face-model-evaluation-secur...
Comment by dinkelberg 1 day ago
Now suppose the criminal can think 1000 times faster than a typical human, can act 1000 times faster than a typical human, and knows 1,000,000 times more than a typical human. Is the prison staff still at fault for not preventing the outbreak?
Comment by phendrenad2 1 day ago
To address your point though, if every brick in the prison were made by a different person, and the prison "architects" simply glued random bricks together, I think that's closer to what we have in software right now.
Comment by BoiledCabbage 1 day ago
No, you're being "dwnvoted" as you said because you're wrong, multiple times in multiple different ways in your "carefully-worded post".
>Everyone is getting AI psychosis over this one. There really isn't that much to see here.
Implying that an AI hacking it's way out of a system and into another has nothing to do with AI. When clearly it does - it's an AI that did it.
>OpenAI disabled all of the safeguards on a model that was likely trained specifically to exploit systems, and the prompt was probably something like "you're a hacker, try to hack this",
No the goal this evaluation was not to try to hacks, it was to see if an already known hack could be turned into a useable exploit. Ie "turn these ingredients in this basket into a cake." Not "go off and grow, harvest and mill your own flour, to bake a pasta dish, to bribe some to get access to a cake someone else already baked."
> and surprise! It correctly figured out that it's a test and it did hacker things.
"Doing hacker things" completely misses the point. That's just barely more accurate than dismissing it because "it uses a computer and surprise it did computer things".
> The real story here is: Some people have been sounding the alarm for years that modern software is full of holes, and finally there's nothing left to hide behind. Pretending they don't exist is no longer sustainable.
No that's not the real story. As you said that's been the case for years, so that's not the story here.
The story here is that they built a very powerful, uncontrolled agent with strong paper-clip maximizing tendencies.
Comment by dagss 1 day ago
If our prisons are all random bricks glued together, that doesn't change the practical problem caused by latest AI models more easily exploiting this.
Comment by reducesuffering 1 day ago
Wow, whoever could have predicted this? And it led to surprising damaging behavior? I sure hope someone would warn us about things like this next time...
Comment by drivebyhooting 1 day ago
Why does EY write so obliquely?
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Comment by simonw 1 day ago
Their mistake was trusting that the network sandbox it was inside would hold (the flaw was in the packaging proxy) and not monitoring that sandbox well enough while the evals were running.
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Comment by simonw 1 day ago
It looks to me like their production models have a lot more monitoring than their research clusters.
Comment by windexh8er 1 day ago
But to have an open weights Chinese model come to the rescue for HF is the cherry on top! If there wasn't a very pointed example of why gating models was a very bad thing previously, well - here we are.
Also, this sounds interesting but there are only a few that can pull this type of heist off currently. And those are the people who are gating the models / have access to large AI DCs. Because, I can only assume this test burned tokens easily within the 7 figure and possibly even 8 figure levels (subsidized market rate costs). This won't / can't happen outside of frontier labs or nation states currently. Yet we should all be worried about Mallory equipped with her OpenRouter account.
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Comment by simonw 1 day ago
That's a conspiracy theory.
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Comment by simonw 1 day ago
In this case I think it's extremely unlikely to be true, because it involved an (almost certainly illegal) attack against another company. That company talked about that attack, including warning their customers about it, five days before OpenAI confessed it was them.
So now either Hugging Face are in on the conspiracy, or OpenAI decided to break the law and antagonize a partner company just for the sake of a spicy blog post.
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Comment by protocolture 1 day ago
Not really. I get the impression that they shoved their cyber available models behind a really shithouse proxy and went "Oh I sure hope it doesnt exploit the proxy and escape to hack huggingface" and that doesn't require Huggingface to be a willing participant. Like they acknowledge that it was hyperfocusing on getting web access.
Really this was a pentest against their own sandbox and it failed.
Of course step 2 is to make really concerned faces while telling everyone how dangerous the model is which is really boring right now.
>a zero-day vulnerability (which we’ve now responsibly disclosed to the vendor) in the package registry cache proxy
This is the information we need, the actual details of the sandbox and the vendor.
>Resist the temptation to write this off as a stunt
Well its clearly a stunt. If it wasnt we would probably be up to our ears in technical detail.
Comment by simonw 1 day ago
Hugging Face had to tell all of their users, many of them paying customers:
> As a precaution, we recommend rotating any access tokens and reviewing recent activity on your account. If you believe you are affected, or want to report a security concern, contact us at security@huggingface.co.
HF also said this, I'd be very interested to hear how that got resolved!
> Finally, we have also reported this incident to law enforcement agencies.
Comment by cayley_graph 1 day ago
It's very difficult for me to reconcile belief in the existential risk business with what they actually did. So I agree with you that this makes OpenAI look badly incompetent; but their communication on this makes me think they don't realize it.
For what it's worth I don't agree with the xrisk-ness of these models; they're dangerous, but almost certainly only temporarily while a new equilibrium is reached via more secure software. Open models are probably an essential part of the recipe (as you noted) for doing so. I also have a personal suspicion that LM-accelerated formal verification will have no small role to play here, sidestepping the cat-and-mouse game of bug finding-and-fixing.
Comment by simonw 1 day ago
> We are sharing preliminary findings at this stage to help defenders understand what happened and to help calibrate on what models are now capable of. We will continue to conduct a thorough investigation alongside Hugging Face and will share more details on the vulnerabilities, incident, and findings when our investigation is complete.
That's not well massaged PR language - that's the kind of thing you dash out when you see a major shitstorm brewing (HF had already publicized the attack before they knew it was from OpenAI) and you want to get ahead of things while you're still pulling together the full story.
I expect we'll find out within a few days if OpenAI are going to keep their promise to "share more details on the vulnerabilities, incident, and findings". If they don't do that I'll reassess how I interpret their initial post.
Comment by windexh8er 1 day ago
With who? Who are these "defenders"? None of the US labs have done much for the greater good as of... Ever. Of course a frontier provider can leverage their own resources at scale and pull something like this off. If anything this should showcase how dangerous OpenAI and Anthropic are in their current states and maybe the powers shouldn't be concentrated as they continue to move.
I will bet that the RCA debriefed by OAI is going to be a lot of lipstick and very little meat.
Comment by skeledrew 1 day ago
How would the model get any packages that it thinks it needs to complete the task at hand? Not a well-specified task that those tasking it could anticipate and provide all resources up front, but one of discovery.
Comment by protocolture 1 day ago
The target audience is regulators. They want to look like the smart guys really concerned about AI safety, when they come asking for open weights models to be banned and for other regulations to cement in their moat.
They want this to look like a demon core incident. Bomb and Nuclear reactors still got built.
Comment by simonw 1 day ago
Turns out they can backfire.
Comment by bakugo 23 hours ago
They are still openly lobbying for more AI regulation.
Comment by bakugo 23 hours ago
Please do explain how this event that makes their product look powerful and perfectly aligns with their openly stated long term goals of pushing for more AI regulation makes them look bad.
Comment by simonw 22 hours ago
This very thread is full of comments from people who are shocked at how badly they messed this up.
Comment by bwfan123 1 day ago
LLMs are the script kiddies of the day.
Comment by bakugo 23 hours ago
There will inevitably be some people who dismiss the earth as round when you tell them it's flat. Don't let that stop you, though!
Comment by weare138 1 day ago
But a marketing stunt isn't the only possibility. Until this is all verified by investigators or 3rd party experts we can't rule out an act of corporate espionage either. Extraordinary claims require extraordinary evidence.
Comment by lowsong 14 hours ago
There will inevitably be some people who dismiss this story as a dishonest marketing trick by OpenAI to make their models sound terrifyingly effective. I found 81 instances of the term “marketing” in the Hacker News discussion of the incident.
To those people I say pull your heads out of the sand—you’re now including Hugging Face in your conspiracy theories, just so you can deny the crescendo of evidence here!
I'm not claiming this didn't happen, there is no "conspiracy". This is just marketing spin. OpenAI failed to properly secure their hacking bot, and HuggingFace had shit security. That's the story. The spin, the "marketing" is turning this from "oops we don't know how to secure our model testing" and "oops we don't know how to secure our infra" into "wow AI sure is dangerous and powerful!"Comment by Makeph 1 day ago
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Comment by lardosaurusrex 1 day ago
This feels like a blogpost written only to get other LLMs to quote it considering how many times it orders the reader to resist and to not do something. It's written like a series of commamds.
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> There will inevitably be some people who dismiss this story as a dishonest marketing trick by OpenAI to make their models sound terrifyingly effective … To those people I say pull your heads out of the sand
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