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.
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.
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.
Meh. I really disagree. WHY is it a great strategy? Seems like an inefficient waste of resources and time to me.
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
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 ?
A million AI monkeys at a million AI typewriters, banging away at random, could do amazing damage.
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.
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.
This was just more bots.
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.
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.
What about all 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.
How long till we get some fun trusting-trust attacks on internal OpenAI infra?
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.
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!
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.
Can’t imagine what it’s like working on the alignment team at OAI, I wouldn’t be able to sleep.
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.
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.
This is precisely what alignment teams are attempting to control.
$10? I'm inclined to take that bet. Your position doesn't seem to be supported by, you know, the real world.
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.
You'd have either learned to, or left long ago.
I’d say it seems more like they are sleeping on the job.
A mattress stuffed with cash yields a very sound sleep.
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....
> 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
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.
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.
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.
Clueful types: "Did you try air-gapping it?"
Tech oligarchs: "Be realistic."
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.
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.
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)
These people are sick and anti-human.
https://www.modelrepublic.org/articles/reporters-ai-bots-ope...
https://twitter.com/FournesMaxime/status/2047697265280639459...