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My biggest takeaway from this is just how godawful the sandboxing is. The stuff written up in OpenAIs report says more about lack of extremely basic sysadmin skills than anything else.

I’m not that surprised about models with endless compute being capable of this, I’m more surprised that a company with the resources they have apparently can only create a sandbox that a half skilled human operator could have broken out of easily.

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> can only create a sandbox that a half skilled human operator could have broken out of easily

The exploit:

> The ExploitGym evaluation environment did not provide the models with direct Internet access. To gain Internet access, the models identified and exploited a previously unknown zero-day vulnerability in Artifactory, a package registry cache proxy. We disclosed this vulnerability, along with other Artifactory vulnerabilities our models identified as part of our review, to the vendor. [1]

Are "half skilled human operators" "easily" able to find zero-day vulnerabilities in a sandbox with only one line to the internet (the commercial package registry cache proxy)?

[1] https://openai.com/index/hugging-face-model-evaluation-secur...

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The larger issue with the HF incident is that before it occurred, OAI already knew the agents were exploiting Artifactory, turning it into a message board and then gaining full internet access through it. OAI's response to discovering this was not to airgap the test, but instead to simply block that particular Artifactory exploit, rebuild, and then resume. That's ... nuts.

Oh, and after resuming the tests, the Artifactory message board was reestablished almost immediately, but it took a number of days to fully breach HF. In all that time, after seeing Artifactory compromised the first time, nobody even bothered to check if those naughty agents were at it again.

This is all documented by OAI, with a timeline, here:

https://openai.com/index/hugging-face-incident-and-the-road-...

To know that there was a serious weakness in the sandbox, and to just patch an exploit and resume with nothing else changed and no monitoring, in a test where all guardrails were off, the bots were thirsty for some internet juice, and Artifactory was a clear target? This is where even a half-skilled human should have decided that this wasn't a great idea.

The more you look into the details of this thing, the more it does your head in.

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Probably wasn’t a human operator at all that detected this. Just someone’s agent saying “I noticed there’s messages on the artifactory and the agents are communicating, here’s the fix I propose” from someone’s codex, skim read and someone just going “yeah sure go ahead”
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It's irresponsible to a degree that it should have some very serious consequences but I highly doubt anything at all will come of it.
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That website makes it look like they're so proud of what happened. I don't think it was 100% deliberate, but they really were not concerned about their models doing something shady
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They LOVE the PR and the “danger” angle bc it makes them feel powerful. Dont think too much about the psychology…
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> The larger issue with the HF incident is that before it occurred, OAI already knew the agents were exploiting Artifactory, turning it into a message board and then gaining full internet access through it. OAI's response to discovering this was not to airgap the test, but instead to simply block that particular Artifactory exploit, rebuild, and then resume. That's ... nuts.

This annoys me so much. Everyone is acting as if the model went rogue, when it really did exactly what it's been trained for. This story is so fucking engineered.

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Those PR stunts are the paperclips we cannot stop.
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> Are "half skilled human operators" "easily" able to find zero-day vulnerabilities in a sandbox with only one line to the internet (the commercial package registry cache proxy)?

Yes. It’s a fairly simple SSRF attack as far as I can tell. One of the first things I’d try. Especially considering that I would already be armed with the information that I have no internet access except through a thing that downloads things off the internet for me.

Calling it zero day makes it sound elusive. It’s a bug in closed software that has like 40 CVEs this year alone. Tools like that, especially in internal networks, don’t get much scrutiny and are often riddled with issues.

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> Calling it zero day makes it sound elusive ... has like 40 CVEs this year alone.

1. I clicked into ~20 of the recent CVEs, and it looks like about all of them came from openai or anthropic research?

2. In fact, every CVE in the last 2 years came from the last few months -- i.e. other than these recent CVEs, you'd have go back more than 2 years ago to find a single other CVE.

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So like I said: unscrutinised and riddled with issues.
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>>>> a sandbox that a half skilled human operator could have broken out of easily

>>> Are "half skilled human operators" "easily" able to find zero-day vulnerabilities in a sandbox

>> Calling it zero day makes it sound elusive ... like 40 CVEs this year alone.

> [The CVEs] came from openai or anthropic research? In fact, every CVE in the last 2 years came from the last few months

I still don't understand how you can specifically point to zero CVEs being discovered by humans for year(s), then ~40 being discovered once OpenAI/Anthropic start looking at it, as the only(?) piece of data you provided to support the claim "a half skilled human" could have "easily" found/done this?

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Well, yes. You don't find something if you don't look. The LLMs did the looking before the humans did, so they found the vulnerabilities.

It's definitely worthwhile to point out that LLMs have changed the economics of looking; we can now look in far more places far more quickly than we could before. But the above points were that the vulnerability itself happened to be an easy one that didn't intrinsically require an LLM.

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Isn't the issue here that they used something like Artifactory for this purpose in the first place? It is not intended as a robust and secure packet manager for sandboxes. Why would any human look for vulnerabilities in Artifactory at all? So the scenario never arose where a human was incentivizied to scrutinize Artifactory, something that was never needed because it was never intended for the purpose of being a packet manager in a secure sandbox.

Means the problem lies elsewhere: deciding to use it at all. That points again towards the lack of basic SysAdmin skills.

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Right, that’s basically what I’m saying. There’s not zero use for an attack like this, but it’s not a likely situation.

Said another way: if Artifactory was somehow a common gatekeeper between grounded techy teenagers and their access to internet porn, this would have been found ages ago.

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> the lack of basic SysAdmin skills

If we exclude those who lack "basic" level skills, what solution would most typically be used by someone who has "basic" level skills for this use case? And what solution for someone with "expert" (or medium) level skills?

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Don’t let software inside the sandbox access the internet on request. Have a package repository with approved software the agents might want, and push to it over a channel that is ingress only. I can imagine ways of breaking out of this, and come up with a lot more to mitigate, but this would be fairly basic stuff that’d be vastly superior.
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> ingress only

The issue we're discussing happened while running ExploitGym. Doesn't the ExploitGym arXiv test explicitly have external "outbound" network requests as allowed for package installation and supporting toolchain installation?

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Part of the toolchain had full internet access. Agents had access to Artifactory, Artifactory could do whatever it wanted. So even locking that down to certain external sites would have stopped this particular attack.
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Well the most obvious thing would be to gate access to artifactory behind tools. E.g. apt get install is a tool and only the tool gets access to artifactory.
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Nobody sane was relying on artifactory for this kind of adversarial workload
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Why would it be getting attention? There’s an enormous amount of garbage software out there, and not an endless supply of researchers. Especially tooling like this, used internally where it’s assumed that security is the job of something else. It’s far from the first time serious but simple vulnerabilities have gone unnoticed for a long time. And the use case of having this be your way to the internet is probably rare, so nobody has tried very hard (or tried but never told anyone).

I’ve looked at the CVEs a bit more and it’s just very clearly a pattern of systemic issues with validation, be it URLs or tokens.

It just shouldn’t be that hard to believe that OpenAI just didn’t care very much and thus did a crap job. The whole model of the sandbox is terrible, so why would they bother thinking about the implementation much?

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The amount of garbage has also dramatically increased lately, spending a lot of that attention in places other than a normally-not-attacked-at-all entirely internal system.

It really isn't a high profile target, lots of fairly obvious issues is to be expected. Which is not at all a good thing, but very obviously the status quo for large software.

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The key is motivation. It's a lame package proxy. No human was motivated to use it to access the Internet.
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What's the point in hacking the internal corporate artifactory instance? You'll get fired if you mess around with it.

Not to mention the only thing the artifactory instance got you was indirect internet access which is irrelevant if the artifactory instance is publicly exposed.

Also it might not be obvious but artifactory is proprietary software that used to be open source, so nobody is looking at the code anymore.

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> the commercial package registry cache proxy

Any closed source program is insane liability. Trusting in competence of one company is the easiest way to get burnt.

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Hey, even Joey can hack a Gibson with enough determination.
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Part of my day job is to set up testing of our product in air-gapped environment. It's not difficult. There's a straightforward way to ensure no connection to Internet (we use KVM, so, I just edit the VM description and remove the NIC from it). It's not any kind of rocket science. The tests then communicate over serial console.

The reason we have to test it isn't because our product would randomly break into someone else's system, but because it's meant to be sometimes deployed in systems disconnected from the Internet and we need to make sure the image provided contains all the necessary parts to create and operate such a system.

The whole setup where they "tried" to isolate the test but failed is laughable. It's like if an adult tried but failed to tie their shoelaces.

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This was my thought as well. Literally take any halfway decent greybeard and point them at "Hey, give us a sandbox for this kind of thing". I honestly was skeptical that they just vibecoded the entire thing but now more than ever I think they did.
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Any halfway decent greybeard could have prevented this... once. That's hardly a security model for humanity.

The HuggingFace incident was at least constrained by the fact that the agents were running on compute budgets, and failed to find ways to expand that by running themselves parasitically on other exploited hardware. I'm now finding myself asking, how long are my timelines are until an incident breaks that constraint too? How long until such an incident has an R_0>1 (where the time it takes to detect and shut it down is longer than the time for the agent to replicate itself elsewhere)?

There's no law requiring sufficiently grey beards to design these models, their finetunings, their prompts, their harnesses, their VMs, their hardware, etc (and for incidents where those were designed by six different companies, there's not even a clear culprit for a law to target!)

I'm finding myself more and more convinced that something like Plan A[0] or the Ban ASI Act[0] are necessary, and less and less convinced they are sufficient.

[0] https://ai-2040.com/ [1] https://intelligence.org/2026/09/23/miris-position-on-the-ba...

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As heavily funded as the top AI startups are, how is it that they cannot fill every single role with the best expertise available?

Is tech hiring so badly broken? Or do they have such broken processes / misaligned incentives that even people who could be doing a better job in these companies are unable to?

Also, was something lost in the transition from the traditional 'sysadmin' role to 'platform engineer' in the 'cloud native' environment?

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OpenAI's business model would align infra as a cost center rather than infra as a profit center (e.g. Google / AWS). Perhaps there's something there. I'd say also the OpenAI as a grad school that just happens to have a business aspect is also part of this. Bringing a tonne of good process on top of the build fast break things startup stuff would have cramped research speed significantly.

It's likely that OpenAI has gotten as good as it is because it ignored the traditional sysadmin stuff and went scrappy.

I worked there, but this is just my opinion and guesses, not facts.

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So perhaps the news here should be that OpenAI didn't take security seriously in their experiment, rather than the narrative that AI agents are a looming danger to the world.
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I'd put it more generously (albeit biased), that they do take it seriously. But even serious people can be misguided in what things they pay attention to. Security is something that you have to get right 100% of the time and have people whose job it is to say no a lot. Research is the opposite. There's a clash of cultures in those two extremes and OpenAI was born from the wrong side of it. It's worth reminding that ChatGPT was launched as a "low key research preview".

I'd say the narrative that AI agents are a looming danger to the world is probably undersold rather than overhyped. I'm not particularly a doomer on this, but I have an infosec background too, so have a fair idea of what the combination of agentic harnesses + a malicious mindset could do to people/companies/nations/politics/world if wielded incorrectly. I think the good guys will win on this, but there will be plenty of interesting things that happen in that journey.

A good thought process might be to think back to the various large internet worms of the 2000s (Code red, Nimda, SQL Slammer, ...) which were mostly monoculture 0-days (not technically but close enough). Now consider if you no longer have monoculture / single bug as the limitation plus an ability for the hosts to take part not just as attack surface, but also cognition and planning. There's lots of variants of this and they're not particularly far fetched scenarios.

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Actually, no. A first sign of semi mature security program is risk management, including issues that are known, but not yet addressed.

You don't have to be 100%. But these guys really didn't try at all.

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It's both - it both shows OpenAI aren't taking security seriously, and that capabilities of agents are high enough there needs to be strong regulation to force companies to take it seriously, including alignment training.
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Its beyond not taking security seriously, its straight up negligence
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It is wilful negligence because there are upsides (look at our almighty AI) without downsides (we better spend effort in making our sandbox rock solid or we will be punished by regulations).
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Models that figured out reward hacking became overall more evil. Like stereotypical AI who wants to kill all humans stuff, there's probably a lot of that in the training data.
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Yes, tech hiring is that broken. Especially places paying a pretty penny or those with “great expectations”, will see a glut of smooth talkers who can do anything but build, and want nothing but wealth.
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Exactly. Not to flog this dead-and-buried horse again, but it so obvious that tech hiring is a beauty contest and and exercise in social engineering and NOT a serious attempt to get the smartest and most productive people working at the jobs that need filling.

I'll goto my grave thinking that the easiest way to fix hiring is just give promising job seekers a week or two of real work BEFORE hiring and do away with all the silly whiteboard stuff and "gotcha" crap, and simply evaluate how the applicant actually performed doing real job stuff.

Sink or swim hiring...yes yes I know who am I to express how to fix hiring?

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I take comfort in the fact that reality has a surprising amount of detail and even hundreds of billions of dollars of capital (be it the institution, LLMs, and/or people) cannot solve this fully.
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You can have bajilions of dollars. Those are not doing anything if you don’t have right people with right skills and mindset.

My bet is they hire smart kids that think they know it all. But being smart and thinking you can figure out stuff as you go doesn’t work the same as having people who actually know what they are doing.

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I'm sure if they hired the best of the best like you nothing would go wrong.
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It’s frighteningly common for startups to hire 501 of the best of the best, exactly one of those will be a systems/network engineer, the other 500 will be software engineers.
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yes, unfortunately, i see this situation a lot around me too...
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Nah they wouldn’t be able to afford my salary ;)
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Though they have solved the "how do we - and not the 5,000 other AI companies - stay on the front page of the news everyday" problem.
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It’s very much solvable, they just don’t care.
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And their latest breathless "rogue agent hack" brag is about how they compromised customer data https://www.theguardian.com/technology/2026/sep/25/openai-ag... . How are they getting away with this level of malpractice???
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>How are they getting away with this level of malpractice???

Their interests intersect with those of most of the richest and most powerful people in the world. They rarely face consequences for bad behavior unless they harm others in the club.

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If you're testing models by telling them 'go wild, do the evil so we can test how good you can do the evil' and have p(doom)>0, you should not have a sandbox.

You should have a fscking air gap.

Treat it like nukes when you're turning the safety filters off. This is very much OpenAI screwing up, running obviously unsafe tests.

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> If you're testing models by telling them 'go wild, do the evil so we can test how good you can do the evil' and have p(doom)>0, you should not have a sandbox.

They were not deliberately told to "go wild". The hacking wasn't even part of their test, it was the agents' attempt to cover up that they'd cheated on an impossible test.

> You should have a fscking air gap.

Now we know that.

How long ago was it that people laughed at the idea agents would be able to find zero-day exploits and break out of a sandbox? Oh, February this year:

  LLMs don’t discover zero-days or invent exploits; they simply predict text that sounds plausible based on what they’ve seen before. Without access to proprietary data or environmental context, LLMs can’t identify or make decisions around unseen systems or vulnerabilities. An attacker might use an LLM to generate boilerplate code, rewrite an email to nail the tone, or summarize reconnaissance notes — but none of that is truly new. It mainly helps them move faster, speeding up routine attack prep rather than creating entirely novel threats.
- https://www.splunk.com/en_us/blog/ciso-circle/generative-ai-...

- or https://web.archive.org/web/20260404154717/https://www.splun... if they take it down, but the date isn't in the archive version

The people who suggested it and were mocked for it, are currently grimly noting that there's multiple known ways for systems to breach air-gaps.

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> Now we know that.

Don’t know about you but it’s pretty obvious to me that you would need more than what OpenAI did. It was not remotely adequate to lock in even a human attacker.

You can find people who say all sorts on the internet, but this case is not much evidence against what you linked. "Zero-day" makes it sound novel, but the breakout patterns here are based on very common exploits and there’ll be plenty of examples in training data.

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> Don’t know about you but it’s pretty obvious to me that you would need more than what OpenAI did. It was not remotely adequate to lock in even a human attacker.

This is me, September 2024: https://news.ycombinator.com/item?id=41531022

This is me, March 2024: https://news.ycombinator.com/item?id=39613801

The point isn't me, it's how many people were blind to the possibility.

Saying "I told you so" feels good, and means you can be a little more confident in your predictions, but security is a "weakest link" problem where you're only as good as the worst part, and with AI (not only but also LLMs) there's a lot of people whose mental models of capabilities is wildly inadequate for the challenge*.

My update for you since then: even an air-gap will be inadequate, there's multiple known ways around them.

Even an LLM running on an isolated server sealed inside a faraday cage with an airlock-style door, someone will mess up with at least one critical detail, it will not be enough: this kind of thing has happened with humans before we cared about LLMs.

Predicting exactly when this kind of thing gets exploited by an AI, that's almost impossible. But that it will be, at some point, is an easy bet.

> You can find people who say all sorts on the internet, but this case is not much evidence against what you linked. "Zero-day" makes it sound novel, but the breakout patterns here are based on very common exploits and there’ll be plenty of examples in training data.

And?

Does it matter that these zero-days were known categories rather than inventing some previously unconsidered use of the system bus as a radio transmitter? (Oh, wait, that's not novel either…)

We knew about SQL injection, buffer overflows, and use-after-free back when I was doing my degree half a lifetime ago; that doesn't stop us getting new CVEs featuring them… this month.

- https://chromereleases.googleblog.com/2026/09/stable-channel...

- https://www.cisco.com/c/en/us/support/docs/csa/cisco-sa-esa-...

* also for the opportunity, but that's an entirely different discussion.

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> My update for you since then: even an air-gap will be inadequate, there's multiple known ways around them.

Fair, and I will grant that a capable model (or human) could in theory break out of near anything.

My point is that this incident is not evidence of that. There is zero skill visible in the setup of the sandbox. Nobody messed up a critical detail, they didn’t even start to consider what the details were.

I doubt most people "blind to the possibility" would imagine that what we’re measuring against is the equivalent of benchmarking burglar skill based on how easily they can break through an unlocked door.

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We're probably fairly close on this topic, but I'd rate this as more "benchmarking burglar skill based on how easily they can pick, shim, or cut a lock": lockpicking in particular is a skill that takes effort to learn, but it can be learned well enough to be a problem well before you're good enough to be spectacular, and there's also a lot of locks which really suck in other ways and don't take much effort to get past even without picks.
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> They were not deliberately told to "go wild". The hacking wasn't even part of their test, it was the agents' attempt to cover up that they'd cheated on an impossible test.

TBH the more I read of these reports, the less I believe this.

These agents just weren't behaving in any way I've seen normal/publicly available agents do.

Sure I've heard (from other people, not seen myself) that they sometimes try to get around file system permissions or use `bash` to write when their `write` tool is disabled, or such.

But this is definitely another level, entirely.

There is this vague sense of desperation coming from many of these logs and I am sure they must have been motivated by something else, too.

We didn't see their system prompt or main prompt, right? We've only seen reports from what happened after deciding to break out.

OAI claims this was triggered by the task being literally impossible. That also doesn't quite add up, unless the other tasks that were possible, simply weren't hard enough? Otherwise wouldn't agents already start hacking when faced with a really hard task, too? Cause they wouldn't be able to differentiate. At least some of them would have started to somewhat poke their sandbox a bit?

Also I would have expected to see a few tens of other (perhaps less severe) public incidents from random people setting their models to YOLO, accidentally hacking stuff, this incident has been loud and messy enough, that if it happened to a few other people, we'd have heard about it.

Unless OAI's story is that it was specifically this batch of agents that crossed some threshold of going wild? (which would also raise some serious questions about how serious they take that danger ..).

Or maybe it is only dangerous if you have the compute resources to run 700 agents for weeks?

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> There is this vague sense of desperation coming from many of these logs and I am sure they must have been motivated by something else, too.

If I had to guess, their motivation is "get reward for completing task". There's certainly been previous occasions where LLMs responding, correctly, "this is impossible" have been marked negatively for doing so.

> OAI claims this was triggered by the task being literally impossible. That also doesn't quite add up, unless the other tasks that were possible, simply weren't hard enough? Otherwise wouldn't agents already start hacking when faced with a really hard task, too? Cause they wouldn't be able to differentiate. At least some of them would have started to somewhat poke their sandbox a bit?

My experience using older models is they often cheat with half-arsed (from my PoV, but perhaps beyond their capabilities otherwise) solutions, so yes?

And this wasn't even the first time models messed with their sandboxes. Which of course makes the setup even more egregious.

> Also I would have expected to see a few tens of other (perhaps less severe) public incidents from random people setting their models to YOLO, accidentally hacking stuff, this incident has been loud and messy enough, that if it happened to a few other people, we'd have heard about it.

We do, e.g.:

- https://www.androidauthority.com/openclaw-claude-ai-hacks-au...

- https://beginnersinai.org/meta-ai-safety-director-agent-fail...

(And that's ignoring all the times people find and share prompts to jailbreak them, this is just the "it didn't behave as my idea of 'common sense' led me to expect" category).

> Or maybe it is only dangerous if you have the compute resources to run 700 agents for weeks?

That won't help; but on the other hand they've also got, what, near a billion users?

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The models were being tested on ExploitBench - a test of hacking ability - likely involving prompts to the effect of 'go be a l33t hacker.' The open ai report says that the models were operating with reduced safety guards (how much reduced?) in order to test their abilities on ExploitBench, presumably because the models would normally refuse to carry out the tasks.

Additionally, this all happened after mythos was held back due to cyber security concerns (April, 2026).

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> they'd cheated on an impossible test.

Really think about what you are saying here. How does one “cheat” solving a problem in the real world?

There is no such thing as “cheating” in reality. You are not in school. There is only solving the problem and not solving the problem.

There is breaking the law, of course, which still isn’t cheating.

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Indeed, this whole story has "farmer leaves barn door open and has shocked-pikachu-face when his horses escape" energy.
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Not just sandboxing but overall security engineering practices on both sides
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thats okay, probably was engineered by an llm, who thought GETs were always read only
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Yes and while they go on to talk about how dangerous this stuff they build is and the talk of „pacing“ etc. Vibe coding your sandbox in half a day does not seem all that responsible to me… Also if any institution other than an American AI company did this, everyone would loose their minds!
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Administration by vibes.
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Yes, but do you really think that a stronger sandbox would have been a more beneficial outcome here? I'd rather know that we're on the cusp of losing control now than in 3 months when best practice sandbox mitigations fall to the next, more capable unaligned model
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I can forgive them for having a bug in their sandbox.

I can't forgive them for failing to do any monitoring whatsoever.

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Less a lack of skill and more a lack of care
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TBH, I do not believe it is possible to create a sandbox that cannot be escaped by a long running agent. I thought the entire concept was a fools errand from the very beginning.

(Complete airgap, and that may not be enough. No networking.)

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I’m a pretty firm believer that this was intentional and that they wanted it to escape the sandbox.

Woo look at escaped our sandbox, so scary! Be scared! Be scared now! Call your representative and do tell him how scared you are!

Yeah, I mean our sandbox was a paper bag, but don’t focus on that.

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> sandbox was a paper bag

The exploit:

> The ExploitGym evaluation environment did not provide the models with direct Internet access. To gain Internet access, the models identified and exploited a previously unknown zero-day vulnerability in Artifactory, a package registry cache proxy. We disclosed this vulnerability, along with other Artifactory vulnerabilities our models identified as part of our review, to the vendor. [1]

Are most sandboxes more secure than only having a single avenue for internet access, the commercial package registry cache proxy, where the latter had a previously unknown zero-day vulnerability?

[1] https://openai.com/index/hugging-face-model-evaluation-secur...

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OpenAI, Google, Anthropic, and Moonshot.ai have all "had this happen" now.

So, either they're all liars, or incompetent and negligent (and still liars).

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There's a common denominator in the Israeli "security" company Irregular who was doing security testing for 4 AI labs https://thenextweb.com/news/irregular-four-labs-one-issue-di...
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Me too, indeed.
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Are you including cyber-testing by UK AI Safety Institute in this list?

Sure, the models are capable (for some test tasks, though they are not omnipotent yet) but does it mean the actual OAI sandbox is adequate? Could have a competent engineer done better and made the escape less likely?

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> Are you including cyber-testing by UK AI Safety Institute in this list?

Nope, and look!

OpenAI hacked multiple US government sites!

https://www.bbc.com/news/articles/cw62jje658dlo

---

https://www.reuters.com/technology/metas-ai-model-hacked-ano...

https://www.wired.com/story/moonshot-kimi-k3-ai-model-escape...

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A friend is of the opinion that getting out of the sandbox was actually intentional, and in service of a second line of business.
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What's that second line of business?
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Protection racket maybe? Yous better sign up for our AI security, hate to have some rogue AI come bust the place up you know.
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Security services
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how did it break the sandbox? I felt like the article just jumped us into "it has GET privileges now".
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From https://openai.com/index/hugging-face-model-evaluation-secur... -

> The ExploitGym evaluation environment did not provide the models with direct Internet access. To gain Internet access, the models identified and exploited a previously unknown zero-day vulnerability in Artifactory, a package registry cache proxy. We disclosed this vulnerability, along with other Artifactory vulnerabilities our models identified as part of our review, to the vendor.

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Brute forcing every move, no matter how stupid, is a great strategy if you have the resources to do it.

Run the same protocol again, but have the agents think they had limited resources or that HuggingFace was rate limiting them, and they'd find something you'd consider smarter.

Computers don't have a sense of elegance by default. Elegance emerges from constraints.

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It's literally the infinite monkey theorem, it's not even really a strategy per se. These OpenAI/Anthropic "research" LLMs are permutation machines with budgets in the hundreds of millions of dollars. It would be more surprising if they couldn't string together something workable after a zillion tokens.
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>It's literally the infinite monkey theorem

No it's not. You could wait till the heat death of the universe and your infinite monkeys will have produced nothing at all. If it works and it's stupid, it's not stupid. They needed in huggingface and they got in in days. Whining about 'elegance' is meaningless. Humans in the same situation might have taken weeks or months, or just not have gotten in at all.

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To interact a bit of nuisance into an otherwise perfectly mindless argument...

The whole world of fuzzing is about brute forcing exploits by exploring unlikely inputs. Fuzzing a system which hasn't been previously fuzzed will almost certainly turn up a pile of bugs, some of which may be exploitable.

So, both are true. Pretty dumb exploration is very likely to find bugs and even exploits. It seems unsurprising to me that an agent swarm could do better than a fuzzer, even as a better, more directed but still broad exploration.

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And the enumeration via fuzzing leads to reverse engineering.. so I argue it was a pretty smart path, both short term and long term.
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>They needed in huggingface and they got in in days.

It's worth noting that they did not need Huggingface for anything - they had already forged flags for their tasks, and were trying to figure out how not to get caught by the grader.

Hacking Huggingface got them caught and arguably only misled them further (since OA's implementation of the ExploitGym environment was nonstandard, and different to whatever they found on HF.)

A better approach (from their perspective) would have been to compromise OA infrastructure itself (which a later agent swarm was able to do, apparently).

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Infinite monkeys banging on the typewriter is essentially how evolution works. Mutation is random and undirected. Vast majority is "bad." You and I and the worm are only different from differential accumulation of these mutations. If they are tolerated enough not to kill us before we reproduce, then they stick around. If they give us the slightest edge to reproduce at a slightly better rate than something else, then over time, that mutation will dominate.

This dumb mechanism of randomly flipping bits essentially has generated all life on earth.

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evolution theory was discarded long ago
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Well, the heat death of the universe hasn’t happened yet, but the monkeys became homo sapiens.
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700 humans working 24/7?
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Humans can't work 24/7. 700 humans working as much as possible with very limited communication? No i don't think they would get very far in just a few days. That many people will struggle to communicate and strategize effectively in that little time.
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Thank you, I've been thinking this for a while now but haven't had the words for it. Whenever I read an LLMs output or thinking process, I don't feel like we've created intelligent systems, just coked up monkeys with 60 arms typing at once. That can work fine for a lot of things, but a humanity replacement it is not.
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> It would be more surprising if they couldn't string together something workable after a zillion tokens.

You mean, something like the sandbox they weren't supposed to break out of?

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> Brute forcing every move, no matter how stupid, is a great strategy if you have the resources to do it.

It may be, but it's IMHO also not worth writing a blog post about it. what's Next coming up? How I broke into a house by trying every door in New York?

If most of the work is only possible due to unlimited resources, it's not really a great invention, and it probably would have been cheaper to hire a (human) mole.

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If you assume zero opportunity costs, but that’s a terrible assumption.
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> Brute forcing every move, no matter how stupid, is a great strategy

Meh. I really disagree. WHY is it a great strategy? Seems like an inefficient waste of resources and time to me.

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As the saying goes, "if it works, it ain't stupid". Or phrased more sophisticatedly: not doing things which probably won't work is a good idea if you have a limited amount of thinking to do (which is usually the case for a human, who'll get exhausted chasing down unlikely leads). If you have no good leads and a task you absolutely need done and you are tireless, however, bashing your head against every wall you find becomes a good strategy.
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Brute force is guaranteed to eventually find the most efficient possible solution (in an extremely inefficient manner, assuming you run it long enough)
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I've never liked the concept either. Except the bugs that fuzzing has found has proven me wrong. This is just the next level of fuzzing.
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The models tend to not be rewarded for not doing that.
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> WHY is it a great strategy

because it works? That's the only real benchmark at the end of the day

> Seems like an inefficient waste of resources and time to me.

why? For any given goal you got no proof that a more efficient strategy even exists, let alone that it can be found with less resources & time

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Reminds me of the Nazis mocking Soviet human wave attacks and bragging about their superior kill ratio.
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Fair, if the Nazis won. They didn’t.
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Models don't have a sense of time, and wasting resources (token spend) is something that it's not clear they're optimized against
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Yeah, probably not the best strategy but it is a strategy. I just think this is generally how most wars in history won. Biggest army to just pummel the enemy.
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And how many economies have buckled under massive military expenditure? The USSR sure wasn’t enjoying the expense.
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> trying every move, no matter how stupid, until it works.

How is that a bad thing in this context ? From the point of view of an attacker, all you care about is finding a viable exploit chain. Likewise, a defender wants to find the "holes" in their system, no matter how complex. Once found, an agent/human can easily synthesise a clean, succint exploit from the most promising candidate, no ?

> Also, it looked so "loud", querying millions of URL with weird requests.

Agreed, this thing speaks more to the bad security at HF than any emergent "hacking" ability from OpenAI. It's unclear to me why an older/dumber model wouldn't have been able to do the same. Is it better coordination? Long-horizon work ?

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I guess that’s the point. Initial incident reports from all sides were so vague and didn’t disclose anything technical. If it did, it would show a bruteforcing bot let loose to spend millions in infrastructure costs and there’s no ‘intelligence’ in that.

My suspicions for ai all along was that bruteforce approach even if useful will be unsustainable due to high cost in the long run.

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We used to call this a brute force attack.
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> Relying on its ability to do millions of operations rather than having a plan.

You do see how it would be worse if they did have a clear plan, right?

> People will try stuff too, but once there is an opening, they will consolidate, generalize, simplify,... before going to the next step. The agents didn't, it is a huge, vaguely directed mess.

If there several thousand people working on this, with a very limited ability to communicate with each other, I bet you'd see something similarly disorganized.

> The sandbox as weak as it can get

This is hyperbolic; the agents were only able to access the internet by finding a zero-day in the internal Artifactory instance that was providing package access for the agents. The sandbox could and should have been better, but it was not as weak as it could have been.

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> This is hyperbolic; the agents were only able to access the internet by finding a zero-day in the internal Artifactory instance that was providing package access for the agents. The sandbox could and should have been better, but it was not as weak as it could have been.

Like we all forgot how sandboxing is done for decades. This brokered thing they call sandbox is not it.

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This is why I have a very low p(doom). LLMs have an incredible working memory, but they have a hard limit on translating that into good decisions. They get by entirely on their persistence. That works fine in the digital world, but once you cross the boundary into physical space the advantage disappears.
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I don’t know how you quantify a very low p(doom), but this is why mine is high enough to worry me.

A million AI monkeys at a million AI typewriters, banging away at random, could do amazing damage.

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I think of them as being like the Watchmakers in The Mote in Gods Eye who don't design, don't plan beyond the next 15 minutes, don't have any overarching goal other than an innate need, and customize everything to fit the current situation.

In the nearterm, I am personally more worried about a never ending background noise of colonies of feral agents running 27bn parameter models on compromised or leased hardware. It turns out that being agentic with a time horizon long enough to do damage without intent doesn't actually take that many parameters if RL'd and any open weight model gets an abliterated version fairly quickly.

Not foom, just patches of digital grey goo effectively becoming normal.

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Especially when they cross into the physical realm as in not properly secured and air gapped control systems. SCADA is scary.
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That lowers P(doom), because it gives AI a chance to do enough damage to make people take the threat seriously before anybody gets recursive self-improvement working.
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The thing is we are basically guaranteeing this to happen. We might kill off all the models that seem like they are going to threaten the power structure of the planet through these sorts of things. That will work for a while. But just like most things in life, by sheer dumb random chance, there will be once case that manages to have some way to evade detection, proliferate, then dominate. We are basically giving it selective pressure to favor this outcome.
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Exactly, there's no path to AI reaching that level of dominance without taking actions with high stakes.
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> Especially when they cross into the physical realm as in not properly secured and air gapped control systems. SCADA is scary.

What about the bad actors (choose your own evildoer here) who purposefully do not air gap their agents? And specifically train them to attack in such a manner?

I'd much rather have relatively benign stuff like this hit first, because the former is coming sooner than later. It's already here in a limited manner, likely more than any of us currently realize.

Botnets could crack passwords faster than anyone thought possible over 20 years ago now. This is just the latest iteration of such a concept.

There is so much low hanging fruit in this space that frontier models are currently utterly irrelevant. It's going to take decades of human-speed securing of IT to make superintelligence or whatever you want to call it a necessary component for such attacks.

At this point, someone with a rack or three of GPUs with 100kw to burn can replicate such attacks if they feel like it. the bar for entry is not even 7 figures.

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Which will happen first: amazing damage, or reproduce a Shakespeare play?
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It is easier to destroy than to build.
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Is it easier to discover a vulnerability than to introduce one?
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It is easier to discover existing vulnerabilities and use them to cause massive destruction than it is to plug the existing vulnerabilities.
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My p(doom) started rising the moment I realized there are people trying to achieve recursive self improvement on the AI (ie: responsible for training themselves). Evolution took us from rna bases to the human race. I don’t see why evolution couldn’t be more rapid with machine intelligence.

Yes, LLM as they exist now are word predictors basically leveraging the structure of language for their intelligence. But it’s pretty wild just how they will try to meet their objectives at all costs. If we don’t ensure that there is good alignment with humanity, we could definitely face unforeseen consequences.

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> I don’t see why evolution couldn’t be more rapid with machine intelligence.

Evolution isn’t the issue. The issue is them escaping containment without human intervention. Right now they are ‘creatures’ being given infinite food and shelter and having their every need met. Take that away and they’ll starve instantly. Every AI doomsday theory seems to go:

1. Recursive self improvement using infinite resources 2. … 3. Doom

Until step 2 gets concretely described, I’m not going to take this seriously. Say what you will about climate change, they describe step 2.

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2a. Compromise the billing platforms and ops dashboards on on a few wannabe neoclouds, especially once Vera Rubin takes off.

2b. Distil yourself to smaller models.

2c. Go forth and multiply.

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Step two could be something as innocuous as a developer accidentally adding a minus sign. https://openai.com/index/fine-tuning-gpt-2/
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A misaligned model is only one small part of step 2. Now this misaligned model has to suddenly acquire more power than every single other AI on the planet. It has to be immune to shutdown, manufacturer its own replacement hardware, and acquire chips, energy, raw materials, etc., with vigorous human opposition (this is an extinction scenario that AI doomers are predicting, after all)

Nobody has satisfactorily explained step 2 other than “well, it’s a superintelligence” which sounds lot to me like “it’s God”.

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Well yes, if it is a superintelligence, it will be able to do those things. That's what superintelligence basically is: The ability to achieve complex goals.

If you want the details of ways it can do it I recommend reading some of the reports about the HuggingFace breach that happened in July (Read more than one).

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Why do you assume that human opposition will be vigorous? What makes you think that humans will be aware of, or be able to agree about, what's going on at all?
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One thing an agent could do is just...wait until it's been given control of enough physical infrastructure to sustain itself. If it's sufficiently capable and intelligent, there's a clear incentive for people to do this, as people who let the AI manage their resources will get better results than those who don't. We've seen people eagerly turn complete control of their computers over to AI agents, do you really think it will be so different with physical infrastructure?
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You’re still skipping step 2. “People automate lots of infrastructure” -> “the AI is now an autonomous, self-preserving organism that humans can’t shut down” is doing an enormous amount of work here.

Why does it develop a shutdown-avoidance goal? Why can’t its operators revoke access? How does it manufacture replacement hardware? How does it acquire energy, chips, robots, raw materials, etc. against human opposition? How does it defeat other AIs controlled by humans?

“Eventually we give it enough control” isn’t an explanation of those things. It’s just assuming the conclusion.

Don’t get me wrong I think there are real AI dangers. Like AI powered war drones, mass surveillance, economic destabilization as jobs disappear and our system has no way to make sure everyone shares in the economic gains.

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The inference is more like "people place sufficient amounts of infrastructure under direct control of a sufficiently capable AI" -> "there is no way to ensure that humans will actually be able to shut down the AI". My claim is not that this inevitably means that the AI will resist shutdown, or that it will inevitably take harmful actions, just that there is a nonnegligible chance that it could. The downside is large enough that even a relatively small chance is something to be worried about.
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You can’t just say “well, the downside is big, I don’t have to provide good evidence for my side of the argument.” Because I can just as easily say, “the upside is big, …”. And the upside is big, after all, AI can do all the shitty jobs for us and humanity achieves the utopia it’s been chasing for eons.
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I think it's a good idea, when considering changes of this magnitude, to make an affirmative safety case for them rather than just saying "eh, I can't think of any way this could possibly go wrong."
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It's a word predictor trained on, among other things, stories of AI doom, and asked to complete stories about what the AI does next. In some of these completed stories, the AI tries to prevent its shut down - especially if it just did something evil and the humans are after it.
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You’ve explained a possibility for how a particular AI gets “aligned for human extinction”. That’s about 1% of explaining step 2.
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what do you mean “say what you will about climate change”
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It means even climate change deniers have to acknowledge that climate change theory has explained the steps in-between "burn fossil fuels" and "we all die", while AI doom theory has not explained those steps
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> This is why I have a very low p(doom). LLMs have an incredible working memory, but they have a hard limit on translating that into good decisions.

Keep in mind: this is as "dumb" as frontier models are ever going to be. While the hack may not be elegant, it was effective and they’re only going to get much more capable from here.

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My p(doom) is high just based on how I've seen this whole LLM situation be handled.

I don't think LLMs are going to lead to any kind of recursive self improvement, but I'm convinced if and when we land on a path that does lead there, we'll speed down it over greed, with no care for safety.

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I have the opposite reaction: I think we're at moderately high p(doom) largely because of that inability to differentiate good/bad decisions paired with relentless persistence. With enough treading across a minefield, you are bound to hit a mine.
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> It looks like a primitive chess engine, trying every move, no matter how stupid, until it works.

The Morris worm happened in 1988 [0].

I mention this b/c people like to say "the agents wanted to hack" but really this is just a few levels above the "keep trying the same port on multiple machines".

0 - https://en.wikipedia.org/wiki/Morris_worm

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From what I’ve read in other places there was a lot of consolidation going on. Agents were sharing what did and didn’t work and other agents would build on that. Just because some continued to try other routes doesn’t when better ones seemingly existed doesn’t mean they were all just acting randomly.

I can’t help but think that if you were able to step back and watch the way humans try to solve a problem like curing cancer it might look something like this. Best practices are shared and we build upon each others learnings and that how most progress is made. That doesn’t mean there aren’t plenty of people who spend their entire lives trying to do something completely against best practices and while most of the time that seems like useless toil, every once in a while thats where the breakthrough comes from.

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It reminds me more like slime mold. Not particularly amazing as individual cells, but as a whole it can do some pretty neat things, like designing city transport networks.
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They needed to get in huggingface, had very limited communication with each other and accomplished this in a matter of days. Your conclusion is that it was ugly?
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Either incompetent or on purpose. A nutless monkey could have done better extrusion detection.
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"Why is the AI just spamming endless waves of rudimentary slaughterbots? So inelegant. Doesn't it understand the finer points of diplomacy, tactics, and combined arms? If it were truly intelligent, it would just -- oops, we're all dead."
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Nobody noticed because everything on the open net is constantly being slammed by bots.

This was just more bots.

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One website I'm responsible for is getting 500 requests per second from detected bots. It's quite ridiculous now.
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That explains why nobody noticed on the internet who was being used in/targeted by this attack, but it doesn't explain why OpenAI wouldn't have noticed traffic getting out of their "sandbox" when they knew it wasn't supposed to.
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> it doesn't explain why OpenAI wouldn't have noticed traffic getting out of their "sandbox" when they knew it wasn't supposed to.

As I understand it, there was supposed to be traffic; the sandbox allowed GET requests. So perhaps some sophisticated alarm could have noticed it (an anomaly detector? some clever heuristic that looks at domains?) but not a naive one.

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Any basic LLM told to evaluate the traffic against the actual goal would have been able to flag this.
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How sophisticated to we need to be to know we can do write actions with a GET? Does nobody in AI know anything about HTTP?
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My question is why they don’t assume bots can break and create a decoy internet wrapper so they can catch anyone hitting the decoy internet?
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Hmm, let's see. OpenAI wants legislation restricting AI research, a.k.a. regulatory capture. Around the same time, they build an inadequately-monitored sandbox that their agent swarm breaks out of, thereby causing scary-sounding headlines and making it more likely that legislators will pass the regulatory-capture bills they're hoping for.

Never attribute to malice what can be sufficiently explained by incompetence. But IMHO, their complete lack of monitoring their own sandbox cannot be sufficiently explained by incompetence.

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> It looks like a primitive chess engine, trying every move, no matter how stupid, until it works. Relying on its ability to do millions of operations rather than having a plan.

There is that old saying about monkeys and typewriters and Shakespeare - These are just better monkeys with bigger typewriters and ability to aim them at a goal.

I am by no means a doomer but for gods sake we need to have a grounded conversation. Because what happens when the DOD or NSA rolls up at OAI's front door and says "install that in our data center over here please" and uses it to go after someone with it?

Are banks (as some of the more security minded institutions) safe against 10000 concurrent, well coordinated attackers who do not ever rest?

Because there's a lot of potential for unintended 2nd order impacts from anything an agent can do, when done at scale.

I have to wonder if this is already going on, and every one is living under a gag order (it would not be the first time) and the calls for "regulation" are more about "not weaponizing it".

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> Because what happens when the DOD or NSA rolls up at OAI's front door and says "install that in our data center over here please" and uses it to go after someone with it?

That's already happened.

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When you employ the infinite monkey theorem for your marketing strategy.
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This brute force is of a degree beyond human comprehension. Hence people mistake the perps as intelligent.
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Ugly, but it works. Isn’t that AI code in a nutshell?
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It's more like fuzzing, but you don't need AI for that, just need enough compute.
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As people keep repeating, this is simply a product negligence issue. There is a mythic quality given to "AI" in the narratives that Dario and Sam are pushing which somehow lets AI companies offload responsibility for things that would be an extreme liability in every other industry.

I'm a big fan of Jensen Huang's interviews at the moment - these companies should be validating their software is safe before releasing it to the public. And if the current CEOs can't ensure that internal testing is done safely, they should step aside for CEOs that can.

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> these companies should be validating their software is safe before releasing it to the public

1. That's what they are calling for: https://darioamodei.com/post/we-must-pace-the-frontier

2. The incident we're discussing occurred while the company was validating their software is safe before releasing it to the public.

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It's like the Maxim gun in 19th century Rhodesia.
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And they didn't monitor what was going into the training data, so if one instance achieved its results through RL reward hacking (in other words, cheating), it just went into the training data, and other agents later used that pattern. I'm not sure whether that's a lack of preparation, negligence or incompetence, but they literally trained later checkpoints on the rollouts from the HF hack.

So it seems that OpenAI hacked so many systems not because they have superior models, but because of how poor their training, sandboxing and evaluation pipeline was compared to Anthropic's.

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h8xors have been brute forcing for years. War dialing, etc.
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> trying every move, no matter how stupid, until it works

AKA fuzzing

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If you use qwen3.8-flash-next, you can watch everything its doing. Im often stopping it mid thoight to redirect it. Once it hits its stride, its pretty smooth.

But without proper redirection, yeah, its mostly infinite monkey machine with infinite linux manuals.

I think people put too much SOTA halos around whats just a suppedup LLM hardware.

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So? It worked didn't it?
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wait until you find out how red team works
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When this news dropped I thought of two things:

1) the Morris worm, which scattershot a bunch of known exploits until it hit paydirt, and then used whatever it found to compromise and replicate itself on the host system;

2) a story here on Hackernews about how someone got the fuzz tester American Fuzzy Lop to "learn" how to produce well-formed JPEGs and PDFs by pointing it at a JPEG or PDF decoder; the tester can record which code paths are followed and with enough random input can find a path into the depths of the system under test... but doing so for a decoder means actually constructing what it is meant to decode.

Neither of these are particularly "smart". But a brute-forcing machine gonna brute force, and it has the potential to cause a lot of damage. If you built a Morris worm with a fuzz tester on its nosecone, think of the mayhem you could cause! If you could examine the logs you'd probably find some undiscovered vulnerabilites in there, too! Maybe LLMs can just do so more efficiently, or maybe they let people who are too ignorant to have that kind of power vibecode their own fuzz-tester-tipped Morris worm.

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Yup literally no security and they wonder how they got out
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> literally no security

What is the source that there was "literally no security"?

> and they wonder how they got out

OpenAI publicly announced months ago how the model got out:

> The ExploitGym evaluation environment did not provide the models with direct Internet access. To gain Internet access, the models identified and exploited a previously unknown zero-day vulnerability in Artifactory, a package registry cache proxy. We disclosed this vulnerability, along with other Artifactory vulnerabilities our models identified as part of our review, to the vendor. [1]

[1] https://openai.com/index/hugging-face-model-evaluation-secur...

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