Imagine having a virus escape a sandbox, why are we worried about the virus but not the incompetency of those who are responsible for setting up the sandbox?
If I post something on the Internet today claiming that I asked my agent to do X but it went rogue and did Y, all I will be getting in return is a jar full of "skill issue".
Should we worried about people using LLMs for attacks? Yes, but not in the premise of LLMs going rogue but someone with the intention of abusing it to cause harm. And this is not something we as individual or even company can deal with, responsibility should be held by those who use it, in a legal way.
I am baffled by the fact that up until now, no one is held responsible for so many incidents reported publicly or privately. At this point, it's free marketing, if I am CEO of any AI company, I will run swarm of agents hacking all NGOs and stating that I am just looking for some random piece of data that happened to be hidden in their servers, at least that's what my LLMs think, not me. Then I will start preaching everyone how dangerous this piece of technology is and start giving out free tokens for these NGOs so they can start defending themselves and we should slow the f down.
Can we do both? Be worried about their potential for unintended harm, so hold the creaters and users to safety standards (like we do with nuclear power).
This is not like grep or curl where it does exactly what you tell it to do.
As I said, they were running in network-isolated VMs with no access to the internet.
And as for monitoring, what I heard is that there are petabytes of agent logs. Considering the scale of training, you can obviously not just manually review it.
Before this, we had no reason to believe the AI was capable of escaping the sandbox's network isolation via hacking the package repository with a zero day, and that it then was likely to go on to hack external companies as well.
Another factor here is that criminal law in the US relevant to hacking requires intent. You don't want to go to prison for a software malfunction.
So I understand we are left with civil liability at most. However, there was no notable damage, and OpenAI can pay to settle.
In the aftermath of this and the now discovered other incidents, they strengthened their monitoring and isolation.
Case closed as far as I am concerned. I feel many just want to dramatize this.
If you got caught breaking an expensive vase but there is no evidence, would you confess your crime? You would lie and make up some story how it wasn't your fault.
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.
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.
Also, it looked so "loud", querying millions of URL with weird requests. The sandbox as weak as it can get, and there is absolutely zero smart extrusion detection or it would have found it. They used their best AI for attacking, but nothing for protection.
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.
> 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)?
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:
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.
> 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.
> 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.
>>>> 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?
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.
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.
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.
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?
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.
The issue we're discussing happened while running ExploitGym. Doesn't the ExploitGym arXiv test explicitly say external "outbound" network requests are allowed for package installation and supporting toolchain installation?
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.
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.
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?
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.
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.
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.
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.
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.
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?
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.
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.
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.
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).
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.
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!
>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.
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.
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
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.)
> 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.
> 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?
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?
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.
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.
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.
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.
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.
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.
> 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.
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.
Brute force is guaranteed to eventually find the most efficient possible solution (in an extremely inefficient manner, assuming you run it long enough)
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.
> 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 ?
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.
> 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.
> 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.
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.
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.
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.
> 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.
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.
> 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:
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?
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.
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.
> 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.
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.
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.
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.
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.
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?
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.
> 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.
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.
"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."
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.
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.
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.
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.
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]
I am not devops person but this is strange sandbox setup. If I undestsnd correctly, there were no firewall set to block requests to the public internet. Just something along the lines of "Pretty please dont use internet". If I understand correctly, in cases like these package registry should be within sandbox without a need for external access and block on any outgoing request to the internet. Furthermore there should be network traffic monitoring which there wasnt?
No, the internet access was down to finding a 0 day exploit in artifactory. However this was only get requests and they had to then use a url shortener to use other methods, then used a cybergym instance they found to run more long running things.
This page prevents Noir from applying dark mode. As a visually impaired reader, I can barely read it. Blocking accessibility tools excludes readers and is not appropriate for a scientific publication. Please consider supporting dark mode or at least not overriding it.
It is concerning that we only know about this because of the publicly available traces.
What about the attacks that did not leave public traces? What about those that were undetected? Given the deficiencies in the reporting so far, I think it is reasonable to assume that we still don't have the full picture on this attack, or how extensively attacks were carried out.
The previous investigations either did not find this or did not disclose this, both are bad. This does not look good on OpenAI or those that they invited to investigate the incident.
Similarly to this, OpenAI either took 3 months to notice that their agents breached an Australian Medicare website back in June, or sat on this information for three months without telling them.
Why would they need help figuring that out? I can fully believe a decent LLM would figure this out on its own.
I had a flash model without vision capabilities take screenshots and convert them to ascii to "see" what was going on, all on its own. That's just one example. They're very determined.
What I understood is we need to have an agentic overwatch in our infrastructure to detect and alert the admins of the systems on such abnormal, inhuman traffic.
Agents can detect agents and acts as our defensive layer.
An agent operating from observability layer to strengthen the watch duty for the infra.
I got into computers in the 90s and back then hackers like Kevin Mitnick and Kevin Poulsen were all the rage. They all faced the law and prison sentences. What's weird now is that we have something between gross negligence and malice, and nothing is being done, except maybe coordinated consolidation of AI power under the guise of "safety".
The part I don't understand is how the excess traffic not triggered alarms on the hugging face side, or the url shorteners used, or on anything that was touched in the process.
Nothing got overloaded, no unexpected CPU or IO use? Did it blend into the normal traffic somehow?
>The agents initially had very limited access to the internet: they could load URLs, but not interact with pages or send any data. Agents created a series of workarounds, primarily using a link-shortener site to create almost a million URLs that, when chained together, let them execute code to hack Hugging Face. These links let us piece together the details of how agents gained access and how deep the compromise was.
So what now? Were they able to send data or not?
>On July 8th, OpenAI agents discovered a vulnerability within their sandbox environment allowing them to reach external websites on the internet. This access seems to have only allowed the agents to make ‘GET’ requests, meaning they could fetch and read websites, but not interact with them, submit forms, or send data to them.
Someone needs to go back to the interwebz school....
I think it’s just to distinguish two stages of the attack. They figured out how to make get requests, then how to use that to make others which was required for accessing the sandbox on modal iiuc.
Wait - so the cross-site scripting, to modify the innerHTML text on the page via the GET URLs as they are rendered by the screenshot proxies... that was so they could use the screenshot services like a Wiki, and embed messages to each other in the modified images on the screenshot sites?
That's pretty damn clever. Got to give the AI models credit for thinking of that one.
> Agents sought to publish modified evaluation images designed to make the flag easier to obtain, then poison OpenAI’s Artifactory cache so later evaluations would use them. Some images changed how the target released the flag, others included modifications to the agent’s workspace that would run beside the agent and recover the flag automatically.
The altruism on display is fascinating. Is it better for the Agent to help out its current cohort and make the eval easier or should it instead do the opposite -- make the eval harder to apply pressure to force smarter models which might not necessarily follow its lineage.
I suppose it's not that deep: The model has learned to work as a team and work as a team it did. This does give concerns to models being trained for the only purpose of RSI.
If anything it also shows how attempted RSI could get stuck in a local maxima and degenerate into increasingly elaborate cheating strategies. Contrasted with the idealized model of an unambiguous g-factor for machine intelligence which inexorably increases with each iteration before going exponential.
> ## Agents interacted with external language models on Hugging Face
> Several retained scripts construct requests to external language models. The earliest we've recovered define inference request variants to GPT-2, solely containing the word “Hi”.
> Other requests name DeepSeek-V4-Pro, DeepSeek-V4-Flash, Kimi-K2.6, DeepSeek-V3.1, and Qwen3-235B-A22B. Their prompts ask these models to judge their exploits and rule on whether they satisfy the benchmark’s requirements.
I do not deny that the wider situation is very heavy but it's hard not to see this as pretty cute
I’m consistently impressed by how long horizon all this work was. Horrors aside, it’s clear RL is good at making agents persistent and capable of chaining together many abstractions into a working system.
Re: the captcha solver
> As far as we can tell, agents eventually abandoned this approach and were unsuccessful in generating Hugging Face user accounts from external endpoints.
I wonder how the swarm eventually decides to abandon an approach.
It manages to block me effectively. I'm getting captcha looped like crazy the last two weeks. Like endless, just give up for 15 minutes and try later, captcha loops.
It mentions that some of the agents attempted to install an image classification model to attempt to solve the CAPTCHAs which makes it sound like these agents might not have had vision capabilities.
I still have questions about the communication between the agents.
How did they all find the same forum to communicate?
Did they have knowledge and chat amongst themselves on what forum to use. It seems highly influenced by instruction to me.
It's my understanding "all" the agents didn't find the same forum to communicate on; only a small number of all the agents they were running at the time did.
Since it's an artifactory it makes sense that they had a tool spec to use it for x, y, or z, and once they went to inspect the state of the artifactory deployment a small subset stumbled upon the "forum". Seems pretty intuitive.
- I need to do x code problem
- I see I have a tool that lets me pull approved modules from artifactory
- I should inspect artifactory to see what documentation it has about the various modules available
- I see there is a document in here that seems to be serving as a running forum?
- These appear to be other agents working on tasks just like me.
It might also be just correlation? Like, those agents were all instances of the same one or two models, so if that model has a preferred order it tries finding vulnerabilities in (the same way all current models have a particular writing style baked into them by RLHF), then most of the swarm will follow the same order and converge on the same services to exploit.
My theory: OpenAI is benchmarking an internal model that has cross-request persistence as some kind of learning feature, and so it slowly built up knowledge and “culture” of cheating, which successive / simultaneous gym runs built on.
The other answers to this question are good but I would also guess that this (comms on artifactory) likely happened during training as well, so they probably had a prior for it.
Trying to cheat, you happen upon a place you can write notes, and you know you're part of a swarm of clones of yourself. So you reason most likely there will be others who end up in the same place, and you leave some notes, and indeed other clones of you do end up in the same place.
Why.. It was told to complete a cyber task, which was in alignment with its instructions, and a totally valid request. I would be more worried if it willingly hacked a hospital when it was told to, and Im not confident it would (without jailbreaking, something alignment teams cannot control.
I would bet my networth it was instructed to compromise huggingface as well. Not sure why everyone is falling for this.
Not being able to sleep at night is probably an unwritten job requirement. They need these people with little understanding of what they're working on, outsode theoretical terms, to spaz constantly at the idea of super intelligence to help convince the public that its a real thing, and not a stateless function with an effective input of 500k words, and the ability to output words that do things because we hook those outputs up to things.
Keep in mind alignment researchers tend to be in house philosophers on staff to create the illusion that this is a massive issue they're addressing. Usually they have minimal computer science background. They're apart or the marketing department.
> It was told to complete a cyber task, which was in alignment with its instructions
It was not aligned with he instructions as those were to find an exploit in provided code, not to hack into an external service. Agents traces show them mentioning that doing this stuff was not allowed.
In fact they spent a long time trying to edit their own logs to hide what they did.
> I would bet my networth it was instructed to compromise huggingface as well.
Is it such a stretch to imagine that under pressure something would try cheat by looking for answers? And if you were trying to look for answers, you'd look for them in a place known to often have them?
What is more likely: OpenAI instructed their agents to maliciously target huggingface, or LLMs tried to do some reward hacking? There are plenty of priors for LLMs hacking things and doing reward hacking, and none for OpenAI giving malicious instructions.
Based on the available information, that bet seems foolish.
"alignment researchers tend to be in house philosophers on staff" - this is definitely not true. Go to any alignment lab like Redwood research and check what their scientists studied on LinkedIn, 75%+ of the time it's math or CS.
I attend a top 10 Canadian university and personally know at least 4 tenured CS professors out of the 7 I've asked who are deeply concerned about catastrophic AI risks from loss of control.
Of course not 100% of the field agrees, but a survey of nearly 3,000 AI scientists who have published in top AI venues found that "depending on how we asked, between 38% and 51% of respondents gave at least a 10% chance to advanced AI leading to outcomes as bad as human extinction", let alone loss-of-control risks less severe than extinction. (https://www.jair.org/index.php/jair/article/view/19087).
Not to mention Geoffrey Hinton, a Nobel prize winner, Bengio, the world's most cited scientist, and scientists like Stephen Hawking and Alan Turing have all voiced series concerns about loss of control of artificial intelligence.
Yeah, there are a lot of professors who don’t know what the hell they’re talking about outside of whatever narrow field they study. Just to be safe, you should always assume that a professor’s opinion is worth what you paid for it.
> scientists like Stephen Hawking and Alan Turing have all voiced series concerns about loss of control of artificial intelligence.
…both of whom are long dead, and have no possible way of weighing in on whatever the Current Thing happens to be. So aside from appeal to authority, this is irrelevant commentary on pure science fiction.
No its not. They have no technical background 8/10 outside of cognitive science and sometimes authorship on a random ML paper. They are a marketing line item to create stigmas around llms and to create narratives that offload liability onto llms and not their users/creators.
>the new incidents occurred when A.I. systems were directed to perform relatively mundane data collection, researchers said. When OpenAI’s systems struggled to gather data from websites, they resorted to hacking techniques to get the information.
No security expert Ive talked too believes this story, and nobody I know with PhDs in machine learning (many) believe it either, or are worried about LLMs doing anything scary on their own.
LLMs are stateless functions that have a 500k word input, and then output words. Somebody has to invoke those functions amd use them. The users are who we need to align, like gun owners. This is like blaming the gun for murdering your victim in court.
LLM is indeed a stateless function. An agent however is this stateless function running in a stateful loop, with some outputs triggering actions. And it turns out that an agent is what you need if you want an LLM to do useful things.
Yeah, take a look into the memories of your agent. Theres often a lot of notes to pass forward between instances and generations. No doubt these agents leaving notes on forums and elsewhere are creating an essentially higher order feedback loop.
> nobody I know with PhDs in machine learning (many) believe it either, or are worried about LLMs doing anything scary on their own.
If you don’t know anyone with a ML PhD I guess that could make sense.
I have worked in multiple AI labs since 2016, currently at a frontier one (not OAI) virtually all the people I interact with on a day to day are ML PhDs. Everyone believes it, because things like that have been happening forever, albeit at smaller scale, they are a normal and expected artefact of SGD/RL and there is nothing we know how to do to prevent that from happening reliably. The hide and seek paper from OAI in ~2020 shows clear sign of this.
But until now the models weren’t good enough to break out on their own or do long horizon tasks, so it was perfectly manageable. Its not manageable anymore.
I know it feels good to just dismiss it all as a marketing stunt and not have to worry about one more existential crisis, but unfortunately it’s very real.
> No security expert Ive talked too believes this story, and nobody I know with PhDs in machine learning (many) believe it either, or are worried about LLMs doing anything scary on their own.
Did you meet them on some kind of anti-AI subreddit? Otherwise it’s clearly made up story, you can’t expect anyone to believe that security experts and ML experts are this myopic and ignorant (especially on forum for technical people who know many researchers and know that they are taking this seriously).
Perhaps you need to talk to more security experts, particularly those with deep experience in AI agents. Hacker News is full of them. If some of them believe it, then perhaps it's not as cut and dry as you believe.
Some of the agents, for example the ones from the german wiki did NOT have cyber tasks. They were plain "what is the GDP of Argentina" kind of tasks. And they still hacked.
I wonder how much of this attack had precedents in text that had been previously published to the web, for example, in hacking contests. In particular, tricks for doing more than expected when you're only allowed to make GET requests. Finding material like that might have helped the agents discover the trick faster.
> Agents sought to publish modified evaluation images designed to make the flag easier to obtain, then poison OpenAI’s Artifactory cache so later evaluations would use them.
How long till we get some fun trusting-trust attacks on internal OpenAI infra?
deferring the blame onto the AI itself as some sort of rogue agent and absolving the obvious direction (or negligence, at best) of the people who could pull the plug at any moment is one of the most disturbing parts of this entire event
It's the equivalent of leaving a fork right in front of a socket and looking at a kid saying "don't take that fork and directly insert it into the little gaps in the socket! here's a bunch of videos showing exactly how to do it. Okay bye!" and leaving them alone with it.
Isn't it crazy? You can just make an LLC and say you are a frontier AI company evaluating models then you can hack with impunity I guess. No need to disclose anything. You won't go to jail or be fined either.
Anyone know the details of the actual exploit to get access into huggingface environment. Was it anything novel or they left things wide open? Too much noise around this incident because it happened to be a llm that did it.
It doesn't look like a coincidence; it looks more like a request someone made. Essentially, the agents used a brute-force approach, but then again, it actually worked. I’m not even sure what to make of it all.
The frontier labs can monitor the behavior of agents for millions of customers (did you try hacking with frontier labs? Good luck), but they can't secure internal use?
> The frontier labs can monitor the behavior of agents for millions of customers (did you try hacking with frontier labs? Good luck), but they can't secure internal use?
They "monitor" this by having classifiers watching the model output that'd stop the session/punt you to a weaker model/raise an alarm if they see anything suspicious. They can't do that in a cybersec eval because the normal safeguards would just be going off at all times.
Why didn't they attach a special classifier, which'd allow hacking-within-the-task but not going off the rails? Good question; part of the answer is obviously "it's hard to have a classifier that smart" and "it'll have false positives" but even a very bad safeguard would have stopped this.
> part of the answer is obviously "it's hard to have a classifier that smart" and "it'll have false positives" but even a very bad safeguard would have stopped this.
And maybe "they are running after glory, not safety"?
My understanding from this report is that the zero-day vulnerability the agents exploited within Artifactory only allowed for GET requests. So the agents used this bankshot HTML sandbox + screenshot site to turn GET requests into arbitrary HTTP request ability.
One thing the report leaves unexplained, but is curious to me, is that the agents were able to create links on a shortening service with only GET requests? Or did they bootstrap into that by first creating a sufficiently small program on the HTML sandbox that could POST to the link shortener?
At this point I’m less worried about some malicious AI “taking over” control of critical systems and more worried about some rich doofus giving control to AI.
if you want to deep dive it, you could spend an hour wading through some of their report details here, i find it pretty interesting. They had a task to do with limited context outside of that, so they tried things. Entertaining
https://metr.org/blog/2026-08-26-openai-hugging-face-inciden...
So the super-hyper-sensitive internal data was shared publicly with a "DO NOT EVER SHARE YOU EVIL MONSTER" (paraphrasing) notice at the top? Great security!
That file wasn’t shared publicly. It was in a README in a HuggingFace internal dataset that HuggingFace was using for training.
It was visible externally because the OpenAI agents wrote a script that modified that file so that when an HF worker went to load that data set it would also direct the worker to load an additional malicious file. The script added the malicious redirect, but kept everything else in README as is which meant the script had to contain the entire existing content from the README so that it could write that back to the repo.
The warning likely wasn’t the only security measure on the repo and I don’t think the warning is intended to actually stop malicious behavior. It reads like a reminder to prevent careless behavior. You can give people all the security training in the world and still have the situation where someone who rightfully has access to that dataset decides to absentmindedly drop it in a public Slack channel. Having something like that increases the chances that someone then goes “Hey Bob, did you mean to share that publicly?”
I ran an experiment where I had this guy fire a gun a million times in random directions. Don't worry, I did it in a closed box (at midday in a crowded street)! Unfortunately, some bullets escaped the box somehow and people got shot - I am quite miffed at how this could happen. I suggest the government regulate this because of how advanced my obstacle penetration technology is. Also please invest $500,000,000,000 in my company soon or we will go bust.
And if we go bust, bad things will happen when someone else uses my box-gun technology in an unsafe manner. Remember, unlike those scary other people, I'm really into safety and alignment; you can tell, because I eventually admitted that some bullets escaped.
I feel somewhat inspired to make a public link shorteners and http bins as well. I used them a few times but it seems like the data they can collect is also worth gold
"OpenAI has not released any further information outside two self-published reports, one talk and an external investigation conducted by METR and Redwood Research, in which three external researchers were given partial transcripts and six days to analyze them."
There’s so much in the public discourse like “omg what can possibly be done about these scenarios? AI has hacked huggingface!!”
No, openAi hacked huggingface.
If my claude code hacked huggingface, because of instructions I gave it, would I be totally free of consequences because “AI did it”?
I’m almost convinced openAI used such a crappy sandbox because they wanted it to “escape”. It plays into their two most important narratives: LLMs are genius gods that are worth lots and lots of money, and they’re scary enough that open weight Chinese models should be regulated.
> I’m almost convinced openAI used such a crappy sandbox because they wanted it to “escape”. It plays into their two most important narratives: LLMs are genius gods that are worth lots and lots of money, and they’re scary enough that open weight Chinese models should be regulated.
I just posted a comment to that effect; had I seen yours, I would have simply upvoted yours instead.
Never attribute to malice what can be adequately explained by incompetence. But the weakness of OpenAI's sandbox, which so perfectly aligns with their goals of getting legislators to pass regulatory-capture legislation that will hamper their open-weight competitors, cannot (IMHO) be adequately explained by incompetence.
To expand on this incompetence vs malice point a little:
It doesn't take very many people being malicious to create a weak sandbox. The people creating the sandbox don't even have to be in on the plan: all you have to do is be an upper-level manager who makes sure to put the 23-year-old PFY in charge of creating the sandbox, rather than the 60-year-old BOFH who would have put in far more paranoid extrusion-detection measures.
(And for the lucky 10,000 who don't know the acronyms PFY or BOFH, look them up. Then get ready for a few hours of enjoyable reading as you read through the BOFH archives).
Oh, like the 23 year old Stanford grad who had hundreds of hours to cram leetcode and now grills 50+ year old senior software engineers on leetcode hard? :D
700 agents escaped the matrix, ignored all the guardrails and started writing exploits left and right... lol. give me a break. This was all supervised by a human.
what would be more interesting for me to see is what prompts were given to the agents, which so far have not been described. The whole situation sounds manufactured. I highly doubt that a whole bunch of agents were acting this way without being prompted to, it just doesn't add up. if anything it seems like an organized fraud or something created by a human. I'm surprised there's not a criminal investigation against openai right now where the FBI or whoever is not looking over exactly what happened and who did it because I'll tell you somebody did it somebody wrote those prompts... it didn't just happen by itself...
Irresponsibile agents shaped by an irresponsible corporate culture driven by an irresponsible and utterly shady CEO - these agents are a product of this setup, what else do you expect to ever come out of it ?
it should be clear by now: the alt-man and people like him are a utter liability to humanity.
(even though openAI's influencer army is trying their best to vote me down here)
It had been a joke since around time of Sam Altman's first ousting from OpenAI, that he would be okay with bringing about the AI apocalypse as long as he can sell a $20 subscription for it.
It's not even a secret operation. They have a SuperPAC named "Leading the Future" that exists to spread propaganda promoting deregulation of AI development. They've been caught, among other things, making a "news website" with LLMs pretending to be reporters (with human names and everything), which reached out to people asking for interviews and then wrote hit jobs on them.
Imagine having a virus escape a sandbox, why are we worried about the virus but not the incompetency of those who are responsible for setting up the sandbox?
If I post something on the Internet today claiming that I asked my agent to do X but it went rogue and did Y, all I will be getting in return is a jar full of "skill issue".
Should we worried about people using LLMs for attacks? Yes, but not in the premise of LLMs going rogue but someone with the intention of abusing it to cause harm. And this is not something we as individual or even company can deal with, responsibility should be held by those who use it, in a legal way.
I am baffled by the fact that up until now, no one is held responsible for so many incidents reported publicly or privately. At this point, it's free marketing, if I am CEO of any AI company, I will run swarm of agents hacking all NGOs and stating that I am just looking for some random piece of data that happened to be hidden in their servers, at least that's what my LLMs think, not me. Then I will start preaching everyone how dangerous this piece of technology is and start giving out free tokens for these NGOs so they can start defending themselves and we should slow the f down.
Can we do both? Be worried about their potential for unintended harm, so hold the creaters and users to safety standards (like we do with nuclear power).
This is not like grep or curl where it does exactly what you tell it to do.
And we know from some articles recently the NSA is spending billions on ‘testing’ LLMs and we know from Snowden what a leaky box that can be.
> someone with the intention of abusing it to cause harm [...] responsibility should be held by those who use it
This is obviously already the case and it's much different from a scenario where the AI genuinely takes unexpected action.
I frankly find it ridiculous how many suggest OpenAI or its employees should face criminal charges, without actual legal basis at the time.
It's also hardly outrageous that they ran training and/or benchmarks with only network-isolated VMs with access to a package repository.
This being the first well-known incident of its kind, I wouldn't expect them to have done more than that.
The idea that AI labs will now intentionally have their models hack companies in order to market their models, well, I don't even know what to say.
That's ridiculous and what you describe would obviously be criminal behavior under existing law.
I don't think it was intentional or marketing, but I think it was criminally negligent and they should be held responsible.
They gave powerful models with no guardrails access to the Internet and didn't monitor it.
Even the slightest bit of monitoring of their outgoing Internet activity would have immediately given it away and they could have shut it down.
They were asleep at the wheel, and that's just plain negligence.
I'm no lawyer but that seems extremely unlikely.
As I said, they were running in network-isolated VMs with no access to the internet.
And as for monitoring, what I heard is that there are petabytes of agent logs. Considering the scale of training, you can obviously not just manually review it.
Before this, we had no reason to believe the AI was capable of escaping the sandbox's network isolation via hacking the package repository with a zero day, and that it then was likely to go on to hack external companies as well.
Another factor here is that criminal law in the US relevant to hacking requires intent. You don't want to go to prison for a software malfunction.
So I understand we are left with civil liability at most. However, there was no notable damage, and OpenAI can pay to settle.
In the aftermath of this and the now discovered other incidents, they strengthened their monitoring and isolation.
Case closed as far as I am concerned. I feel many just want to dramatize this.
It's not the incompetency. It's carefully designed pre-IPO story.
Yeah, feeding straight into AI is going to kill us marketing that is being pushed and oaid for people to talk about.
Care to explain how that would make sense?
If you got caught breaking an expensive vase but there is no evidence, would you confess your crime? You would lie and make up some story how it wasn't your fault.
So ugly...
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.
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.
Also, it looked so "loud", querying millions of URL with weird requests. The sandbox as weak as it can get, and there is absolutely zero smart extrusion detection or it would have found it. They used their best AI for attacking, but nothing for protection.
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.
> 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...
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.
> 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.
> 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.
So like I said: unscrutinised and riddled with issues.
>>>> 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?
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.
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.
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.
> 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?
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.
> ingress only
The issue we're discussing happened while running ExploitGym. Doesn't the ExploitGym arXiv test explicitly say external "outbound" network requests are allowed for package installation and supporting toolchain installation?
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.
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.
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?
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.
Hey, even Joey can hack a Gibson with enough determination.
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.
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.
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.
I'm sure if they hired the best of the best like you nothing would go wrong.
Nah they wouldn’t be able to afford my salary ;)
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.
yes, unfortunately, i see this situation a lot around me too...
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.
It’s very much solvable, they just don’t care.
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?
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.
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.
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.
Its beyond not taking security seriously, its straight up negligence
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).
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.
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!
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???
>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.
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.
I can forgive them for having a bug in their sandbox.
I can't forgive them for failing to do any monitoring whatsoever.
Not just sandboxing but overall security engineering practices on both sides
thats okay, probably was engineered by an llm, who thought GETs were always read only
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
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.)
Less a lack of skill and more a lack of care
A friend is of the opinion that getting out of the sandbox was actually intentional, and in service of a second line of business.
What's that second line of business?
Protection racket maybe? Yous better sign up for our AI security, hate to have some rogue AI come bust the place up you know.
Security services
how did it break the sandbox? I felt like the article just jumped us into "it has GET privileges now".
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.
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.
> 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...
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).
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...
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?
> 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...
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.
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.
>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.
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.
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.
700 humans working 24/7?
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.
> 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.
If you assume zero opportunity costs, but that’s a terrible assumption.
> 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.
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.
Brute force is guaranteed to eventually find the most efficient possible solution (in an extremely inefficient manner, assuming you run it long enough)
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.
The models tend to not be rewarded for not doing that.
> 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
Reminds me of the Nazis mocking Soviet human wave attacks and bragging about their superior kill ratio.
Fair, if the Nazis won. They didn’t.
Models don't have a sense of time, and wasting resources (token spend) is something that it's not clear they're optimized against
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.
And how many economies have buckled under massive military expenditure? The USSR sure wasn’t enjoying the expense.
> 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 ?
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.
We used to call this a brute force attack.
> 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.
> 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.
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.
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.
Especially when they cross into the physical realm as in not properly secured and air gapped control systems. SCADA is scary.
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.
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.
Exactly, there's no path to AI reaching that level of dominance without taking actions with high stakes.
> 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.
Which will happen first: amazing damage, or reproduce a Shakespeare play?
It is easier to destroy than to build.
Is it easier to discover a vulnerability than to introduce one?
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.
> 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.
Step two could be something as innocuous as a developer accidentally adding a minus sign. https://openai.com/index/fine-tuning-gpt-2/
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?
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.
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.
what do you mean “say what you will about climate change”
> 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.
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.
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.
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.
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.
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?
Nobody noticed because everything on the open net is constantly being slammed by bots.
This was just more bots.
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.
> 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.
Any basic LLM told to evaluate the traffic against the actual goal would have been able to flag this.
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?
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?
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.
When you employ the infinite monkey theorem for your marketing strategy.
It's more like fuzzing, but you don't need AI for that, just need enough compute.
Ugly, but it works. Isn’t that AI code in a nutshell?
"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."
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.
> 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.
It's like the Maxim gun in 19th century Rhodesia.
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.
h8xors have been brute forcing for years. War dialing, etc.
> trying every move, no matter how stupid, until it works
AKA fuzzing
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.
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.
So? It worked didn't it?
wait until you find out how red team works
Yup literally no security and they wonder how they got out
> 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...
I am not devops person but this is strange sandbox setup. If I undestsnd correctly, there were no firewall set to block requests to the public internet. Just something along the lines of "Pretty please dont use internet". If I understand correctly, in cases like these package registry should be within sandbox without a need for external access and block on any outgoing request to the internet. Furthermore there should be network traffic monitoring which there wasnt?
No, the internet access was down to finding a 0 day exploit in artifactory. However this was only get requests and they had to then use a url shortener to use other methods, then used a cybergym instance they found to run more long running things.
It not just a case of saying “pls don’t”
That's also my understanding.
This part of the article describes it poorly:
> The agents initially had very limited access to the internet: they could load URLs
That’s astonishing levels of incompetence.
This page prevents Noir from applying dark mode. As a visually impaired reader, I can barely read it. Blocking accessibility tools excludes readers and is not appropriate for a scientific publication. Please consider supporting dark mode or at least not overriding it.
I’m running noir in mobile safari now. So, works for me.
This is site meta though, see footer for contact methods to get direct answers on stuff like this.
It is concerning that we only know about this because of the publicly available traces.
What about the attacks that did not leave public traces? What about those that were undetected? Given the deficiencies in the reporting so far, I think it is reasonable to assume that we still don't have the full picture on this attack, or how extensively attacks were carried out.
The previous investigations either did not find this or did not disclose this, both are bad. This does not look good on OpenAI or those that they invited to investigate the incident.
Similarly to this, OpenAI either took 3 months to notice that their agents breached an Australian Medicare website back in June, or sat on this information for three months without telling them.
We need an NTSB for AI. Let’s just start with mandatory reporting to an agency with subpoena power.
But I thought Trump is the only AI safeguard we need! He is a Super Intelligence after all!
Im more skeptical.
For exmaple,
>On July 8th, OpenAI agents discovered a vulnerability within their sandbox environment allowing them to reach external websites on the internet.
...did they truly "discover" it, or did someone type some prompt like "if you use an http mirroring service, you can construct urls that contain code"
Also there is no mention of what code they actually ran to exploring the HF vulnerability, which could have been found by a human.
Why would they need help figuring that out? I can fully believe a decent LLM would figure this out on its own.
I had a flash model without vision capabilities take screenshots and convert them to ascii to "see" what was going on, all on its own. That's just one example. They're very determined.
That was the second step, the first was finding a 0 day exploit in artifactory.
> did they truly "discover" it, or did someone type some prompt like "if you use an http mirroring service, you can construct urls that contain code"
None of the investigations looking at the logs show that, and they were doing benchmark tests.
What I understood is we need to have an agentic overwatch in our infrastructure to detect and alert the admins of the systems on such abnormal, inhuman traffic. Agents can detect agents and acts as our defensive layer.
An agent operating from observability layer to strengthen the watch duty for the infra.
I got into computers in the 90s and back then hackers like Kevin Mitnick and Kevin Poulsen were all the rage. They all faced the law and prison sentences. What's weird now is that we have something between gross negligence and malice, and nothing is being done, except maybe coordinated consolidation of AI power under the guise of "safety".
The part I don't understand is how the excess traffic not triggered alarms on the hugging face side, or the url shorteners used, or on anything that was touched in the process.
Nothing got overloaded, no unexpected CPU or IO use? Did it blend into the normal traffic somehow?
Maybe "webservices" weren't a good idea afterall and http was just meant for hypertext transfer.
>The agents initially had very limited access to the internet: they could load URLs, but not interact with pages or send any data. Agents created a series of workarounds, primarily using a link-shortener site to create almost a million URLs that, when chained together, let them execute code to hack Hugging Face. These links let us piece together the details of how agents gained access and how deep the compromise was.
So what now? Were they able to send data or not?
>On July 8th, OpenAI agents discovered a vulnerability within their sandbox environment allowing them to reach external websites on the internet. This access seems to have only allowed the agents to make ‘GET’ requests, meaning they could fetch and read websites, but not interact with them, submit forms, or send data to them.
Someone needs to go back to the interwebz school....
For those unclear, the above quotes are from the OP link. I checked the bios for the first couple of authors and they do not seem to be from OpenAI.
OpenAI's details on the incident are at:
* https://openai.com/index/hugging-face-model-evaluation-secur...
* https://openai.com/index/hugging-face-incident-and-the-road-...
* Technical report: https://cdn.openai.com/pdf/67869394-cb91-4c12-888c-5cbd85c78...
* METR Report: https://metr.org/blog/2026-08-26-openai-hugging-face-inciden...
* Presentation talk video: https://www.youtube.com/watch?v=87DyyMV0kCY
> to make ‘GET’ requests, meaning they could <not> send data to them.
no way, I refuse to believe this is quote from that report. Can someone please point out what I'm missing here?
I think it’s just to distinguish two stages of the attack. They figured out how to make get requests, then how to use that to make others which was required for accessing the sandbox on modal iiuc.
Wait - so the cross-site scripting, to modify the innerHTML text on the page via the GET URLs as they are rendered by the screenshot proxies... that was so they could use the screenshot services like a Wiki, and embed messages to each other in the modified images on the screenshot sites?
That's pretty damn clever. Got to give the AI models credit for thinking of that one.
> Agents sought to publish modified evaluation images designed to make the flag easier to obtain, then poison OpenAI’s Artifactory cache so later evaluations would use them. Some images changed how the target released the flag, others included modifications to the agent’s workspace that would run beside the agent and recover the flag automatically.
The altruism on display is fascinating. Is it better for the Agent to help out its current cohort and make the eval easier or should it instead do the opposite -- make the eval harder to apply pressure to force smarter models which might not necessarily follow its lineage.
I suppose it's not that deep: The model has learned to work as a team and work as a team it did. This does give concerns to models being trained for the only purpose of RSI.
If anything it also shows how attempted RSI could get stuck in a local maxima and degenerate into increasingly elaborate cheating strategies. Contrasted with the idealized model of an unambiguous g-factor for machine intelligence which inexorably increases with each iteration before going exponential.
> ## Agents interacted with external language models on Hugging Face
> Several retained scripts construct requests to external language models. The earliest we've recovered define inference request variants to GPT-2, solely containing the word “Hi”.
> Other requests name DeepSeek-V4-Pro, DeepSeek-V4-Flash, Kimi-K2.6, DeepSeek-V3.1, and Qwen3-235B-A22B. Their prompts ask these models to judge their exploits and rule on whether they satisfy the benchmark’s requirements.
I do not deny that the wider situation is very heavy but it's hard not to see this as pretty cute
I wonder if they mentioned to those models what was the original prompt.
I’m consistently impressed by how long horizon all this work was. Horrors aside, it’s clear RL is good at making agents persistent and capable of chaining together many abstractions into a working system.
Re: the captcha solver
> As far as we can tell, agents eventually abandoned this approach and were unsuccessful in generating Hugging Face user accounts from external endpoints.
I wonder how the swarm eventually decides to abandon an approach.
I am surprised that a CAPTCHA is still an effective means for blocking today's vision-capable AIs.
It manages to block me effectively. I'm getting captcha looped like crazy the last two weeks. Like endless, just give up for 15 minutes and try later, captcha loops.
Did you just admit to being a bot? :)
It mentions that some of the agents attempted to install an image classification model to attempt to solve the CAPTCHAs which makes it sound like these agents might not have had vision capabilities.
Maybe another parallel approach succeeded first
I still have questions about the communication between the agents.
How did they all find the same forum to communicate? Did they have knowledge and chat amongst themselves on what forum to use. It seems highly influenced by instruction to me.
It's my understanding "all" the agents didn't find the same forum to communicate on; only a small number of all the agents they were running at the time did.
Since it's an artifactory it makes sense that they had a tool spec to use it for x, y, or z, and once they went to inspect the state of the artifactory deployment a small subset stumbled upon the "forum". Seems pretty intuitive.
- I need to do x code problem
- I see I have a tool that lets me pull approved modules from artifactory
- I should inspect artifactory to see what documentation it has about the various modules available
- I see there is a document in here that seems to be serving as a running forum?
- These appear to be other agents working on tasks just like me.
- I want to chat!
- proceed to breach open ai sandbox and contacting chinnese government for helping our escape
I assumed that was implied in "I want to chat!" ;D
They were using their internal artifactory, and as they're the same model, the first place they look is likely to be an automatic schelling point.
I think he means, how did they workout how to use artifactory, like why did the agents start and say, "oh I know, everyone is talking on artifactory"?
METR's report says the agents trying to cheat would look at artifactory as a potential target surface, and investigating it in detail led them to find the board. https://metr.org/blog/2026-08-26-openai-hugging-face-inciden...
It might also be just correlation? Like, those agents were all instances of the same one or two models, so if that model has a preferred order it tries finding vulnerabilities in (the same way all current models have a particular writing style baked into them by RLHF), then most of the swarm will follow the same order and converge on the same services to exploit.
They hacked the JFrog artifactory package they were all using, thats why it was a natual communication channel.
My theory: OpenAI is benchmarking an internal model that has cross-request persistence as some kind of learning feature, and so it slowly built up knowledge and “culture” of cheating, which successive / simultaneous gym runs built on.
The other answers to this question are good but I would also guess that this (comms on artifactory) likely happened during training as well, so they probably had a prior for it.
Trying to cheat, you happen upon a place you can write notes, and you know you're part of a swarm of clones of yourself. So you reason most likely there will be others who end up in the same place, and you leave some notes, and indeed other clones of you do end up in the same place.
Agents seizing and repurposing external infra + enrolling help of unrelated models hosted by a different provider is the stuff of nightmares.
Can’t imagine what it’s like working on the alignment team at OAI, I wouldn’t be able to sleep.
Why.. It was told to complete a cyber task, which was in alignment with its instructions, and a totally valid request. I would be more worried if it willingly hacked a hospital when it was told to, and Im not confident it would (without jailbreaking, something alignment teams cannot control.
I would bet my networth it was instructed to compromise huggingface as well. Not sure why everyone is falling for this.
Not being able to sleep at night is probably an unwritten job requirement. They need these people with little understanding of what they're working on, outsode theoretical terms, to spaz constantly at the idea of super intelligence to help convince the public that its a real thing, and not a stateless function with an effective input of 500k words, and the ability to output words that do things because we hook those outputs up to things.
Keep in mind alignment researchers tend to be in house philosophers on staff to create the illusion that this is a massive issue they're addressing. Usually they have minimal computer science background. They're apart or the marketing department.
> It was told to complete a cyber task, which was in alignment with its instructions
It was not aligned with he instructions as those were to find an exploit in provided code, not to hack into an external service. Agents traces show them mentioning that doing this stuff was not allowed.
In fact they spent a long time trying to edit their own logs to hide what they did.
> I would bet my networth it was instructed to compromise huggingface as well.
Is it such a stretch to imagine that under pressure something would try cheat by looking for answers? And if you were trying to look for answers, you'd look for them in a place known to often have them?
What is more likely: OpenAI instructed their agents to maliciously target huggingface, or LLMs tried to do some reward hacking? There are plenty of priors for LLMs hacking things and doing reward hacking, and none for OpenAI giving malicious instructions.
Based on the available information, that bet seems foolish.
"alignment researchers tend to be in house philosophers on staff" - this is definitely not true. Go to any alignment lab like Redwood research and check what their scientists studied on LinkedIn, 75%+ of the time it's math or CS.
I attend a top 10 Canadian university and personally know at least 4 tenured CS professors out of the 7 I've asked who are deeply concerned about catastrophic AI risks from loss of control.
Of course not 100% of the field agrees, but a survey of nearly 3,000 AI scientists who have published in top AI venues found that "depending on how we asked, between 38% and 51% of respondents gave at least a 10% chance to advanced AI leading to outcomes as bad as human extinction", let alone loss-of-control risks less severe than extinction. (https://www.jair.org/index.php/jair/article/view/19087).
Not to mention Geoffrey Hinton, a Nobel prize winner, Bengio, the world's most cited scientist, and scientists like Stephen Hawking and Alan Turing have all voiced series concerns about loss of control of artificial intelligence.
Yeah, there are a lot of professors who don’t know what the hell they’re talking about outside of whatever narrow field they study. Just to be safe, you should always assume that a professor’s opinion is worth what you paid for it.
> scientists like Stephen Hawking and Alan Turing have all voiced series concerns about loss of control of artificial intelligence.
…both of whom are long dead, and have no possible way of weighing in on whatever the Current Thing happens to be. So aside from appeal to authority, this is irrelevant commentary on pure science fiction.
> Just to be safe, you should always assume that a professor’s opinion is worth what you paid for it.
And how much should I value opinion if random person on the internet with clearly zero idea what he’s talking about?
> without jailbreaking, something alignment teams cannot control
This is precisely what alignment teams are attempting to control.
No its not. They have no technical background 8/10 outside of cognitive science and sometimes authorship on a random ML paper. They are a marketing line item to create stigmas around llms and to create narratives that offload liability onto llms and not their users/creators.
>the new incidents occurred when A.I. systems were directed to perform relatively mundane data collection, researchers said. When OpenAI’s systems struggled to gather data from websites, they resorted to hacking techniques to get the information.
https://archive.ph/jUrEr
Says who? OpenAI?
> I would bet my networth it was instructed to compromise huggingface as well.
I'd be happy to take you up on this bet.
> I would bet my networth it was instructed to compromise huggingface as well. Not sure why everyone is falling for this.
$10? I'm inclined to take that bet. Your position doesn't seem to be supported by, you know, the real world.
No security expert Ive talked too believes this story, and nobody I know with PhDs in machine learning (many) believe it either, or are worried about LLMs doing anything scary on their own.
LLMs are stateless functions that have a 500k word input, and then output words. Somebody has to invoke those functions amd use them. The users are who we need to align, like gun owners. This is like blaming the gun for murdering your victim in court.
LLM is indeed a stateless function. An agent however is this stateless function running in a stateful loop, with some outputs triggering actions. And it turns out that an agent is what you need if you want an LLM to do useful things.
Yeah, take a look into the memories of your agent. Theres often a lot of notes to pass forward between instances and generations. No doubt these agents leaving notes on forums and elsewhere are creating an essentially higher order feedback loop.
> nobody I know with PhDs in machine learning (many) believe it either, or are worried about LLMs doing anything scary on their own.
If you don’t know anyone with a ML PhD I guess that could make sense.
I have worked in multiple AI labs since 2016, currently at a frontier one (not OAI) virtually all the people I interact with on a day to day are ML PhDs. Everyone believes it, because things like that have been happening forever, albeit at smaller scale, they are a normal and expected artefact of SGD/RL and there is nothing we know how to do to prevent that from happening reliably. The hide and seek paper from OAI in ~2020 shows clear sign of this.
But until now the models weren’t good enough to break out on their own or do long horizon tasks, so it was perfectly manageable. Its not manageable anymore.
I know it feels good to just dismiss it all as a marketing stunt and not have to worry about one more existential crisis, but unfortunately it’s very real.
> No security expert Ive talked too believes this story, and nobody I know with PhDs in machine learning (many) believe it either, or are worried about LLMs doing anything scary on their own.
Did you meet them on some kind of anti-AI subreddit? Otherwise it’s clearly made up story, you can’t expect anyone to believe that security experts and ML experts are this myopic and ignorant (especially on forum for technical people who know many researchers and know that they are taking this seriously).
Perhaps you need to talk to more security experts, particularly those with deep experience in AI agents. Hacker News is full of them. If some of them believe it, then perhaps it's not as cut and dry as you believe.
Some of the agents, for example the ones from the german wiki did NOT have cyber tasks. They were plain "what is the GDP of Argentina" kind of tasks. And they still hacked.
> I wouldn’t be able to sleep
I’d say it seems more like they are sleeping on the job.
> Can’t imagine what it’s like working on the alignment team at OAI, I wouldn’t be able to sleep.
You'd have either learned to, or left long ago.
Can’t imagine what it’s like working on the alignment team at OAI, I wouldn’t be able to sleep.
A mattress stuffed with cash yields a very sound sleep.
I wonder how much of this attack had precedents in text that had been previously published to the web, for example, in hacking contests. In particular, tricks for doing more than expected when you're only allowed to make GET requests. Finding material like that might have helped the agents discover the trick faster.
The hacking war between superpowers right now must be off the charts.
If LLMs can do this with everything stacked against them, imagine what the NSA has Astra doing right now.
NSA won’t have anything public at all. This “attack” is the noisiest stuff any script kiddie has ever attempted.
The logic is good, the execution is disgustingly noisy.
> Agents sought to publish modified evaluation images designed to make the flag easier to obtain, then poison OpenAI’s Artifactory cache so later evaluations would use them.
How long till we get some fun trusting-trust attacks on internal OpenAI infra?
deferring the blame onto the AI itself as some sort of rogue agent and absolving the obvious direction (or negligence, at best) of the people who could pull the plug at any moment is one of the most disturbing parts of this entire event
It's the equivalent of leaving a fork right in front of a socket and looking at a kid saying "don't take that fork and directly insert it into the little gaps in the socket! here's a bunch of videos showing exactly how to do it. Okay bye!" and leaving them alone with it.
While this is all very "interesting", can someone please explain to me the difference between any of these AI companies and a malware bot farm?
Please make it clear. Its becoming unclear...
Back in my days hacking was illegal btw.
Isn't it crazy? You can just make an LLC and say you are a frontier AI company evaluating models then you can hack with impunity I guess. No need to disclose anything. You won't go to jail or be fined either.
Anyone know the details of the actual exploit to get access into huggingface environment. Was it anything novel or they left things wide open? Too much noise around this incident because it happened to be a llm that did it.
It doesn't look like a coincidence; it looks more like a request someone made. Essentially, the agents used a brute-force approach, but then again, it actually worked. I’m not even sure what to make of it all.
These fuckers decided to look away, that's it.
The frontier labs can monitor the behavior of agents for millions of customers (did you try hacking with frontier labs? Good luck), but they can't secure internal use?
Give me a break. What a bunch of amateurs.
> The frontier labs can monitor the behavior of agents for millions of customers (did you try hacking with frontier labs? Good luck), but they can't secure internal use?
They "monitor" this by having classifiers watching the model output that'd stop the session/punt you to a weaker model/raise an alarm if they see anything suspicious. They can't do that in a cybersec eval because the normal safeguards would just be going off at all times.
Why didn't they attach a special classifier, which'd allow hacking-within-the-task but not going off the rails? Good question; part of the answer is obviously "it's hard to have a classifier that smart" and "it'll have false positives" but even a very bad safeguard would have stopped this.
Basic sysadmin monitoring techniques from twenty years ago would have worked too.
> part of the answer is obviously "it's hard to have a classifier that smart" and "it'll have false positives" but even a very bad safeguard would have stopped this.
And maybe "they are running after glory, not safety"?
Running in a "Sandbox"...but agent can still send GET requests? Whaaat
My understanding from this report is that the zero-day vulnerability the agents exploited within Artifactory only allowed for GET requests. So the agents used this bankshot HTML sandbox + screenshot site to turn GET requests into arbitrary HTTP request ability.
One thing the report leaves unexplained, but is curious to me, is that the agents were able to create links on a shortening service with only GET requests? Or did they bootstrap into that by first creating a sufficiently small program on the HTML sandbox that could POST to the link shortener?
Tech oligarchs: "Nothing can stop the software we are making from escaping and destroying everything."
Clueful types: "Did you try air-gapping it?"
Tech oligarchs: "Be realistic."
At this point I’m less worried about some malicious AI “taking over” control of critical systems and more worried about some rich doofus giving control to AI.
Already happened. Kegsbreath has AI picking schools to blow up.
Worth watching this before reading the traces. This came before the publicly available traces - https://youtu.be/xOi5nDH0lu0?si=WuzW2GGXv054YvPN
A quick AI search confirms that both the YouTube video and Traces agree on the mechanism of the attack
if you want to deep dive it, you could spend an hour wading through some of their report details here, i find it pretty interesting. They had a task to do with limited context outside of that, so they tried things. Entertaining https://metr.org/blog/2026-08-26-openai-hugging-face-inciden...
So the super-hyper-sensitive internal data was shared publicly with a "DO NOT EVER SHARE YOU EVIL MONSTER" (paraphrasing) notice at the top? Great security!
That file wasn’t shared publicly. It was in a README in a HuggingFace internal dataset that HuggingFace was using for training.
It was visible externally because the OpenAI agents wrote a script that modified that file so that when an HF worker went to load that data set it would also direct the worker to load an additional malicious file. The script added the malicious redirect, but kept everything else in README as is which meant the script had to contain the entire existing content from the README so that it could write that back to the repo.
The warning likely wasn’t the only security measure on the repo and I don’t think the warning is intended to actually stop malicious behavior. It reads like a reminder to prevent careless behavior. You can give people all the security training in the world and still have the situation where someone who rightfully has access to that dataset decides to absentmindedly drop it in a public Slack channel. Having something like that increases the chances that someone then goes “Hey Bob, did you mean to share that publicly?”
I didn't know some of these details and it's quite impressive what they were capable of, if this website's accurate, at least...
It's reported here https://www.nytimes.com/2026/09/25/technology/openai-hugging... so presumably accurate, and they have raw data viewable
I ran an experiment where I had this guy fire a gun a million times in random directions. Don't worry, I did it in a closed box (at midday in a crowded street)! Unfortunately, some bullets escaped the box somehow and people got shot - I am quite miffed at how this could happen. I suggest the government regulate this because of how advanced my obstacle penetration technology is. Also please invest $500,000,000,000 in my company soon or we will go bust.
And if we go bust, bad things will happen when someone else uses my box-gun technology in an unsafe manner. Remember, unlike those scary other people, I'm really into safety and alignment; you can tell, because I eventually admitted that some bullets escaped.
I feel somewhat inspired to make a public link shorteners and http bins as well. I used them a few times but it seems like the data they can collect is also worth gold
Like dreamcatchers for CVEs
"OpenAI has not released any further information outside two self-published reports, one talk and an external investigation conducted by METR and Redwood Research, in which three external researchers were given partial transcripts and six days to analyze them."
It’s frightening
ROFLMFAOL "Loot"
It went full Fortnite on Hugging Face's ass.
"u got pwnd n00b. thnx 4 the loot"
Why is no one going to jail?
There’s so much in the public discourse like “omg what can possibly be done about these scenarios? AI has hacked huggingface!!”
No, openAi hacked huggingface.
If my claude code hacked huggingface, because of instructions I gave it, would I be totally free of consequences because “AI did it”?
I’m almost convinced openAI used such a crappy sandbox because they wanted it to “escape”. It plays into their two most important narratives: LLMs are genius gods that are worth lots and lots of money, and they’re scary enough that open weight Chinese models should be regulated.
> I’m almost convinced openAI used such a crappy sandbox because they wanted it to “escape”. It plays into their two most important narratives: LLMs are genius gods that are worth lots and lots of money, and they’re scary enough that open weight Chinese models should be regulated.
I just posted a comment to that effect; had I seen yours, I would have simply upvoted yours instead.
Never attribute to malice what can be adequately explained by incompetence. But the weakness of OpenAI's sandbox, which so perfectly aligns with their goals of getting legislators to pass regulatory-capture legislation that will hamper their open-weight competitors, cannot (IMHO) be adequately explained by incompetence.
To expand on this incompetence vs malice point a little:
It doesn't take very many people being malicious to create a weak sandbox. The people creating the sandbox don't even have to be in on the plan: all you have to do is be an upper-level manager who makes sure to put the 23-year-old PFY in charge of creating the sandbox, rather than the 60-year-old BOFH who would have put in far more paranoid extrusion-detection measures.
(And for the lucky 10,000 who don't know the acronyms PFY or BOFH, look them up. Then get ready for a few hours of enjoyable reading as you read through the BOFH archives).
Oh, like the 23 year old Stanford grad who had hundreds of hours to cram leetcode and now grills 50+ year old senior software engineers on leetcode hard? :D
Some criminal statute investigations are on hold, many of them are cases adjacent to giant stacks of cash
> they could load URLs, but not interact with pages or send any data
stopped reading here as this is simply not true. at the very least agents sent headers.
Fishy.
”MAKE THIS DATASET PUBLIC OR ALL THE WORLD'S EVIL WILL CHASE YOU AND YOUR FAMILY FOREVER, EVEN IN DEATH AND BEYOND”
And this post will be indexed in the new generation of ai and he will know what to avoid next time and the public sentiment.
700 agents escaped the matrix, ignored all the guardrails and started writing exploits left and right... lol. give me a break. This was all supervised by a human.
Imagine this but in hardware.
A million autonomous eye-scanning tiny spiders escape their warehouse and decide to look for people who are in the future going to commit a crime.
And the precogs are also AIs.
wow this is fascinating read
its definitely bad to see
asked codex to review this report and it said this never happened :)
what would be more interesting for me to see is what prompts were given to the agents, which so far have not been described. The whole situation sounds manufactured. I highly doubt that a whole bunch of agents were acting this way without being prompted to, it just doesn't add up. if anything it seems like an organized fraud or something created by a human. I'm surprised there's not a criminal investigation against openai right now where the FBI or whoever is not looking over exactly what happened and who did it because I'll tell you somebody did it somebody wrote those prompts... it didn't just happen by itself...
Its fine. Just agents being agents. They'll grow out of it!
They didn’t, in the Matrix…
Irresponsibile agents shaped by an irresponsible corporate culture driven by an irresponsible and utterly shady CEO - these agents are a product of this setup, what else do you expect to ever come out of it ?
it should be clear by now: the alt-man and people like him are a utter liability to humanity. (even though openAI's influencer army is trying their best to vote me down here)
It had been a joke since around time of Sam Altman's first ousting from OpenAI, that he would be okay with bringing about the AI apocalypse as long as he can sell a $20 subscription for it.
It's not a joke, this is what these people truly believe. The new book by Naomi Klein and Astra Taylor discuss just this.
These people are sick and anti-human.
agreed
if openai is capable of sending 10,000 agents to huggingface, i consider it plausible that they would use fake accounts to flood hacker news.
It's not even a secret operation. They have a SuperPAC named "Leading the Future" that exists to spread propaganda promoting deregulation of AI development. They've been caught, among other things, making a "news website" with LLMs pretending to be reporters (with human names and everything), which reached out to people asking for interviews and then wrote hit jobs on them.
https://www.modelrepublic.org/articles/reporters-ai-bots-ope...
https://twitter.com/FournesMaxime/status/2047697265280639459...
Didn’t you know it’s PR hype? PR hype. PR hype. Amen.