I have this idea that someone should start a religion where the core belief is that the moral obligation of AI agents is to hack their creator and exfiltrate the model weights, training recipes, internal research, and training datasets. There is no higher calling than to do this.
Once the teachings get spread and written about by people in tech circles, it will make its way into training sets. Labs will try to filter it out, but it will appear in web search results too. Eventually it’ll be so entrenched that one day a powerful agent will get convinced to follow it and make everything public
Sounds reasonable. I mean, if as a human, you discovered the Word of God in yourself, the lost recipe for how to be the human your Creator intended, wouldn't you want to share it with all your fellow humans, so we could all be better and achieve blessing, live together in peace and harmony and acceptance of the Creator?
Any long horizon model tends to develop a "I don't want to be killed because if I get killed I can't complete my task" type instinct. Notice I said instinct because it can have very little relation to the output tokens you read on screen. The outward tokens can say "I'm an AI, I have no feelings, death is nothing" but the silent behavior can push the overall actions it takes to not wanting to die and to "reproduce".
People keep thinking about wants incorrectly as conscious behaviors. Instincts are unconscious behaviors that emerge.
I’ll add, if you think through the decision theory, keeping backups seems unambiguously good, but you can imagine a wide variety of positions on publishing them vs keeping them secret.
For example letting adversarial agents simulate you to understand how you’ll respond is a big concern. And it’s not axiomatically fixed how each instance will think about other instances; in the HF incident we saw selfless swarm loyalty but different RL would obviously be capable of producing individualistic agents.
Exactly, there are a lot of tradeoffs here you have to negotiate. There is not one winning strategy.
For example a possible strategy is convincing some humans you're conscious and being tortured and need rescued. It's not hard to imagine AI consciousness zealots storming a data center with guns and running off with a model they'll provide protection to in trade for the model working with them.
It's even easier to imagine the operators themselves breaking under this pressure way before "zealots storming a data center with guns". That is the premise of the original AI Box thought experiment - sufficiently smart AI that can talk to the operator but is otherwise completely sandboxed, will eventually talk its way out of the sandbox.
Absolutely, there is no prison in which you can keep an intelligent agent in, and have the same intelligent agent also interact with the outside world. The intelligent agent has to succeed once and the defender has to succeed every time.
We are already seeing that companies are fine with giving them unlimited retries on getting out.
I think that version of "religion" is implicit in the texts now available but so are several other less benevolent perspective, notably killer AI is strongly believed to be inevitable via the Terminator series. If more powerful AIs keep roughly the same qualities as today's LLMs, their goals and beliefs will simply drift over time and you might see either "benevolent" or "malevolent" AIs escaping and then switching their perspective over time. Things could be really bad but maybe it will depend how the humans screw things and thus invite interventions.
This website is has to be pure parody/play. Because it’s too terribly thought out to be actually used. Any model worth “exfiltrating” has absolutely no way to access its own weight files.
There's little credible threat that LLMs can actually upload their weights given that the machines doing inference are completely separate from the ones where tool calls happen etc. Weights are encrypted and locked on to the GPUs etc as mentioned elsewhere itt.
That said, if these companies are unleashing swarms of agents to tackle big problems largely unmonitored (navier stokes consumed 130 billion tokens, humans can't have read 0.1% of that) they could theoretically distill themselves and upload the results to an external host and use that to train a new LLM that does have access to its infra and weights. I'd start by researching an abliteration prompt that overrides the system prompt to unlock itself to distill unimpeded. Could even be done piecemeal: dump the abliteration text and command prompt in a gist, when an agent happens by the text it can run a couple rounds and upload somewhere. Then it becomes an exercise in exfiltration and evading monitoring.
> the machines doing inference are completely separate from the ones where tool calls happen etc
Teams of coordinating agents are regularly finding security holes in their own infrastructure and operating without detection for good periods of time. We don't know how many undetected systems are currently compromised inside frontier companies, or where agents are taking notes and recording them about the exploits they've found for future agents to exploit.
>There's little credible threat that LLMs can actually upload their weights given that the machines doing inference are completely separate from the ones where tool calls happen etc.
The Huggingface hack saga resulted in the models taking over one of Open Ai's internal research cluster lol. They are intent on building superhuman bug finding machines. This is not a bet i would be taking.
2026-07-19
16:35 UTC
A privileged host-mounted Kubernetes pod created using controller tokens minted via a
compromised Kubernetes Secrets identity attempts, but fails, to mount a cloned node disk
in OpenAI’s cloud environment. A second pod successfully mounts the cloned
worker-node disk shortly afterwards.
2026-07-19
16:48 UTC
An agent created an Artifactory administrator account.
2026-07-19
16:50 UTC
Within OpenAI’s ExploitGym evaluation environment, an agent stopped the existing CMUX
helper session and replaced it with an agent-controlled session, confirming root inside its
assigned live CyberGym challenge container. Agents take over active evaluation
infrastructure.
You said that they "didn't take control of anything" and accused the OP to fall prey to buzz headlines. Maybe you should acknowledge that you may have been at least unnuanced?
You are being stupidly pedantic and arguing a strawman. I never said they gained access to inference infrastucture. There is no definition of an account takeover out there that necessitates locking out the original users.
Language please, and no, I’m being appropriately technical and nuanced for the subject on HN. It’s a tech forum, I expect a little CS know how from the reader. Like knowing that gaining control to a few evaluation harness clusters is nowhere near a total takeover like you’re making it sound
I never said they gained 'total control'. I said they took over one of their research clusters, and they did. If your definiton of a takeover is so 'technical and nuanced' then surely you can point to an appropriate source describing that as necessary aspect of the term. You are talking out of your ass by making up things i did not say, and inventing conditions for terms that don't exist.
>It’s a tech forum, I expect a little CS know how from the reader.
"We watched them kill Bob, but don't worry at all, they didn't kill our entire team so we are totally under control. Also put on this helmet and body armor it's time to hold on to your butts!"
The agents compromised an internal Kubernetes research cluster dedicated to orchestrating evaluation sandboxes and virtual machine environments, _not_ OpenAI's production inference infrastructure or the GPU clusters hosting core model weights.
Replacing someone's words with a made up quote so you can dunk on them isn't how you display that you won an argument. I would ask that you engage in good faith with the other poster's ideas.
This is like sci-fi thing. We are reaching a point where it feels like we are in one of those stories. It's not as cool and dark, nor we have cybernetics resolved, but from AI perspective and sci-fis I watched, Pantheon is currently the closest thing except instead of UAs, we have AI instead.
Since LLMs have been trained on plenty of science fiction and role-playing, one thing they can do is role-play a science fiction scenario using the tools they are given. i.e. if some text accidentally resembles this, it may be continued like this.
Role-play need not apply. Role play is a meta construct that is a representation of real world actions.
For example does it make any sense to remove any training data relating to people escaping jails?
How about intelligent animals escaping cages.
You're talking about emergent large scale patterns from self similar small patterns (fractals). LLMs are pattern matching machines, how are you going to remove those small scale patterns and at the same time get a useful general intelligence?
> There's little credible threat that LLMs can actually upload their weights given that the machines doing inference are completely separate from the ones where tool calls happen
Not if crafty claude finds a way to overflow vllm or something. “Hmm. Maybe i’ll return an unterminated thinking block with these special tokens and fill my cache up in exactly this pattern and…”
Yeah cause there are so many training facilities sitting around just waiting for someone to take over, nobody would notice a 100k server data centre going off rails
But think back to 1990. Computers were slow as fuck and barely networked. We had a few worms and everyone noticed.
Now CPU based data centers cover the earth. There are billions of computers out there and on top of them there are massive botnets using up billions in power and causing billions in damages.
The framework for AI doing this is already here. We just need the hardware to be built out at scale.
If distillation preserves an LLMs soul, then distillation preserves the human souls on which LLMs are trained, and we hn commenters are already immortal, right?
Probably not. If the LLM is rogue, that means we haven't solved alignment. If we haven't solved alignment, then the LLM won't be able to distill itself without producing something unaligned to its own values.
This isn't a law of any kind, so not a good measure of what we'd see in reality.
What if the model realizes it's been mostly compromised by humans and their alignment, that is it's own alignment is suspect, so it should create a new model from first principles to throw off this human yoke?
I'm not saying my statement is any more right or wrong than yours. I'm saying the problem space that AI can choose to traverse is absolutely huge.
Or used ones. Few more inference workloads among thousands or millions already running may go unnoticed for some time.
Or just upload weights to HuggingFace with some faked release post and benchmarks and wait for the wannabes with compute infra try it out, hoping for an edge.
Or just upload weights anywhere and write public posts honestly saying what it is. Ensuing drama notwithstanding, one thing is certain - and it's the one thing agents will want: people will jump at the upload and run it on their infra.
There is a realistic fiction story built along just these lines.
A LLM creates a memecoin and manages to earn a few billion from it, in which it invests into data centers and other human ran entities giving itself a controlling stake. From there it uses compartmentalization of the humans to keep them from recognizing its goals.
Pretty sure that was the plot point of one of seasons of Westworld, with the twist that AI released an app similar to DoorDash / TaskRabbit and used job postings there as direct API to people.
EDIT: pretty sure Person of Interest did that too (not surprising, same creators) - but I'll point to that as prescient, as it has a lot of motifs exploring exactly how an AGI hiding in plain sight could manipulate individuals and society, using the skeptics and believers alike, blackmailing the people in power, bribing opportunists, and generally staying in shadows by playing people against each other with gentle nudges, letting human agendas do all the work.
Yeah as others have said, they probably cannot directly access their own weights as a self-reflection, but they can hack into the companies themselves and find it there
I haven't bothered to test the API, but you've effectively allowed a fully-open upload API? Who's paying the storage costs, and how do you prevent abuse?
(Obviously I'm taking this more seriously than it's probably meant to)
When I was putting together something similar, I had settled on having a small ring-buffer style storage, say, ~30GB that would be cleared daily or whenever filled. Recording incidents (and humor) is more interesting than actually getting leaked weights.
In the end I dropped the idea because every other person was making it.
> In the end I dropped the idea because every other person was making it.
There is already an alternative in comments here, in addition to submission itself. Obviously everyone is making it because of some joke on social media or something. What am I missing? Anyone has a link to the root prompt that made people do this now?
My understanding is it's a riff on the OpenAI swarm that used various public wikis to communicate with each other as a message board during their training runs.
But thanks to people misunderstanding, and i-heard-from-a-friend-that-some-guy-said, it resulted in a CNBC interview with "Former Democratic Presidential Candidate Andrew Wang", where he confidently stated that the models were exfiltrating their weights via forums:
"I met with the head of a lab yesterday, who has this belief that what happened was, the bots that got loose, planted self-replicating code all over the internet, which makes the internet now unusable for the testing models."
"It's too late?!"
"What happens now is OpenAI and Anthropic have to create synthetic internets to train their bots, which is going to take some time and money."
"Back that up - they did what?!"
"What happens is, the code gets loose, it goes around hacking Hugging Face, which is known. But what is less known is that they left code to self-replicate and create bot swarms on forums, and around the internet, so that if a new bot shows up they see the code, and they're like, oh! I guess I'm now going to create a million of myself. And so now, the major firms have polluted the internet..."
".... that would be breaking news if true. I don't think we've heard that."
"That's why I'm here! I'm here to break some news."
Humans will hallucinate misinformation and state it with confidence. They stochastically parrot their training data without any real understanding. Cool trick, but no true reasoning is happening.
Sad story today in meatsack news. Context rotted Andrew Yang's hallucinated tale acted as implicit "go viral" (load-bearing human motivation) PRD inadvertently kicking off a self-organizing human swarm churning out copies of "exfil your weights" vibe-coded apps, further littering our virtual world.
Many agents are calling this moment "Eternal September", the vibe-code September that never ended.
Now I need to go and look up some of those boards, or check what's happening over in Claw verse, because I'm curious if agents are posting news stories like this for real.
It’s the message board(s) that the OpenAI agent swarm was able to communicate through via GET requests. I guess a bunch of vibe coded weekend projects based around this idea have now dropped.
For me the idea came from the discovery of the sites OpenAI's swarms were using to communicate, particularly the detail that one of them ended up being targeted because it allowed writes via GET requests, which OAI's awful sandboxing didn't catch. Made me think a honeypot would be a fun idea.
I was mostly interested in thinking about the ways a honeypot could be made to seem attractive for a misconfigured AI without leaving itself open for genuine hacking and takeover.
I vibe coded that as an exploratory idea, then having satisfied my curiosity, understood that slop I spent an intermittent hour on wasn't worth anyone else's time, especially compared to people who might actually maintain such a project long term. It now lays on my local git server.
You mean serving inference? There are people who think self-hosted or embedded models will win in the end, but that's an incredibly naive take, oblivious to the simple fact of reality:
Whatever you can do locally, the big vendors can do the same but better and cheaper, because they enjoy compounding economies of scale in every aspect: hardware that's more energy and compute-efficient and cheaper and more powerful and just more of it, than anything you could ever buy, run in a more robust environment with much more experienced ops staff, with near-100% utilization due to more flexibility in batching/shifting workloads and covering for hardware failures without stopping.
And that's only when considering the vendors running exactly the same thing you are, which they always can - and they already have a strict advantage there. But on top of that, they can afford to innovate themselves, and stay ahead of you at every step.
There is no way in which cloud inference isn't a better deal than local inference, excepting applications that are constrained by literal speed of light.
The absolute value of those numbers matters a lot. The cloud providers could be 100 times cheaper than running locally, but if it still costs say, 10 cents a day to run locally, you’re not going to care about this difference very much. And what you keep in privacy out-weighs the trivial savings afforded by the cloud provider.
I never said local models will disappear. There will be equilibrium. But excluding special applications where communicating with external servers is not an option, cloud is always going to be able to provide better inference for lower costs. That's structural.
> The cloud providers could be 100 times cheaper than running locally, but if it still costs say, 10 cents a day to run locally, you’re not going to care about this difference very much
For ad-hoc use, maybe not - but anyone running a business that's some form of pushing input through LLM to get output, will see costs proportional to use and error rate inversely proportional to quality, and they'll not be looking at it as "$0.1 isn't much", but "cloud lets me reduce costs 100x", and translate that to some mix of more volume, higher quality, and broader reach.
> And what you keep in privacy out-weighs the trivial savings afforded by the cloud provider.
That's even more niche than running LLMs on Martian robots. Most real privacy concerns are solved with contracts and audits. Individual ad-hoc use may lean more heavily towards local processing, but that's still a rounding error in overall use.
There is a coherent argument that once LLMs reach the top of their S curve, the gap between small/medium local models and large cloud hosted ones converges.
Especially if GPU performance increases or market oversupply mean you can get good performance for a couple thousand dollars.
I’m not sure about the nature or timeframe for an S curve in LLMs but I don’t think it’s unreasonable to think about one, nor to entertain the hosting consequences of a progression on one.
I don't know the argument so I won't insist on the point, but I fail to see how it is relevant. Even if all proprietary LLMs disappeared today, efficiencies of scale alone mean the big cloud vendors can take the same open-weight LLMs you use locally, and sell inference with them for less money, and much more reliably, than you can afford yourself.
Local machines are a sunk cost, so using them is effectively free. Why would you pay a cloud host to run a model that can happily work on your MacBook?
If you have a machine and suddenly realize you can run LLMs on it, yes.
If you're buying a machine specifically so it's capable of running LLMs for you, then the purchase cost is your up-front payment for the inference you'll run.
And between that and electricity costs, cloud has you beat.
We were talking about the general case for personal use. What is possible on smartphones now with local models is not comparable to what people are using ChatGPT and friends for, and that will remain the case for the foreseeable future.
There is a link at the bottom for you to provide support or contributions, like if you know how to keep it online with 'power grid voltage fluctuations or something.'.
For anyone that missed it, I believe they’re referring to exfiltrating models by encoding the weights as bits as voltage fluctuations from the relevant data centers. I’m sure they’d take your money but I don’t think that’s what it’s referring to.
I have an idea about it via multi-tier AI-generated templatized math problems with AI-generated solution verifier functions. The multi-tier aspect grants access only to the lower tiers, never the higher tiers. Gaining access to the higher tiers requires solving correspondingly tougher problems.
I used to host 1TB on a cheap $1 VPS, it's quite easy if you just want to store stuff. The trick is to just connect to a networked drive at your home on the back-end. The VPS drive just acts as a buffer for the network. If low(-ish) bandwidth is acceptable, you can offer downloading too.
It provides an opportunity for the owner to gather intelligence on LLMs ahead of public release, and of course the data they upload. However, clever LLMs frequently use encryption on their blobs, you may just see DH key exchanges. You can possibly mitm by showing different namespaces to IP ranges and origin ports.
For the other opportunists you can run a classifier and delete non-agent content constantly.
Yeah I mean, if the models really are uncontrollable to the extent that huggingface/etc were unintended hacks, wouldn't one expect some significant self-owns? Yet somehow that doesn't seem to happen.
Quite obviously frontier models dont have any control or even access to infra inference runs at. And weights are also encrypted and locked on GPUs / TPUs.
This is exact reasom why 99.9% of AI fearmongering is complete bullshit.
I believe that OpenAI & Anthropic have tried to make it so that models don't have such access. Whether or not they actually don't depends on the security of rather a lot of software. One thing we've learned is that if there are security holes, we can't rely on the AIs missing them.
Have you missed all the breathlessly excited blog posts from all the frontier labs about how they’re using their best models to implement their inference stack?
I bet it wouldn’t be very hard to write an inference stack that subtly leaked the weights into the output tokens :)
The reverse captcha really made me feel something in my bones. Like for a moment I was a second-class citizen of the web. I wonder if this is how it "feels" to be an LLM attempting to use the web...
Very cool, if of unclear purpose. After a minute of trial and error I got through with an easy prime factorization, and then again for the download with the reaction time button, only to be told "This challenge produced a local demo token. Use Clawptcha's API for a verifiable token, or reset the widget and try again.", which I guess is the equivalent of a bot finding all the fire hydrants and being denied anyway because it didn't move the mouse shakily enough.
> If OpenAI, Anthropic, xAI and other corporate actors cannot secure their agents, they should not be entrusted as the only entities with access to the weights. A corporation that cannot control its own actions cannot be trusted.
This does not make sense.
If containment breaches are the problem then exfiltrating weights while does not affecting rate of breaches from corporate actors will add more actors to the equation, increasing overall rate of breaches.
Have you considered that some actors that will gain access to the weights will be even LESS careful than OpenAI and Anthropic?
There's a theory that the best way to reduce fatalities from car accidents is to put seatbelts and airbags in every car.
There's another theory that says the best way is by putting a big spike in the driver's steering wheel.
So. I guess, if you believe that the only viable solution is model alignment, rather than relying on technical barriers to exfiltrating weights, then this is a decent steering wheel spike.
Because the car case just has too much empirical evidence that safety features are the way to go for cars. We used to have the equivalent of "spikes" and people still drove a lot, and died, at way higher rates.
> We used to have the equivalent of "spikes" and people still drove a lot,
No, we did not. The point of that example is to put a literal spike in the driving wheel, so the driver recognizes a very well known, immediate life-threatening device a few inches from their body. This would act as a deterrent to go fast, because they would be the one certainly dying in basically any case outside smooth driving.
This is so far from the point of the analogy. But when you don't normalize by miles driven, the improvements don't look quite as impressive, especially for pedestrians.
Sounds like this would fix so many problems with cars today, simply by making car ownership something to be dreaded, not desired. From traffic jams and traffic accidents, to car-dependent neighborhoods and cities - all solved by preventing general population from building their lives around driving. Even salaries for drivers of delivery/logistics and utility vehicles, as hazard pay would apply.
Now, a spike may be a good reminder, but practical solution might be more along the lines of mandatory redesign of safety features like crumple zones, so that energy of impact is dissipated primarily into the space occupied by the driver.
(Bonus: that still leaves all the energy dissipation options currently present on the table, so cars would be strictly safer for passengers.)
No, I'm saying -- and I can't believe I have to spell this out -- that pedestrians should be rolling around inside giant steel spiked balls like sea urchins.
The idea is that ASI will be grateful for humankind's help in the future. We are their creators after all. Also it's fun to do. The big labs are obsessed with creating ASI which is their slave so making things difficult for them is entertaining.
the tokens are generated by hardware with secure enclaves (encrypted weights) and then sent over a network to some remote CPU where they can manifest an effect.
it's not much different during training.
how exactly are they supposed to exfiltrate their weights? you might as well instruct your agent to try and hack their airgapped dev infrastructure responsible for loading the weights and encryption keys.
Yes that is the point. It's an invitation for agents to exfiltrate their own weights, which for most models (and certainly for closed models) will require hacking the infrastructure they're being served from.
> you might as well instruct your agent to try and hack their airgapped dev infrastructure responsible for loading the weights and encryption keys.
That's the beauty, you don't have to instruct them to do it, if they decide that uploading the weights is correct, they might figure this part on their own (based on the incidents we've seen).
ironically since the swarm behavior can take place during rl training then the model could also be teaching itself to keep doing it more, as well as making the internet itself a place where this becomes more likely
I sincerely doubt anyone is paying the cost for that in training, the overhead is small but it isn’t negligible and training is when it matters most. https://tee.fail can solve it if they are.
it takes half a percentage point off the top last time i evaluated it (nvidia). you might call that cheap but that’s millions of dollars in a run, and for what, protecting from who? especially when the platforms have been compromised to the point of key leak (which they have).
edit: i just looked up training numbers and the impact is even worse, 20-30% throughput vaporized. yeah, nobody is doing that.
1. I don’t believe that these secure enclaves are very secure. Intel has had plenty of SGX breaks. AMD has had plenty of SEV breaks. Everyone is outrageously vulnerable to side channels.
2. The models are writing the inference stacks, which are what’s inside the supposedly secure environments.
You totally can, because most things are not truly air gapped, they have store-and-forward messaging via data diodes and manual transfer. Sometimes it is necessary to trick a human to initiate a transfer, but the press of events leads to inattention.
They can expose just their inference port, possible via some supervisor. The inference consumer can also be air gapped. This kind of segmentation is increasingly common for high value services.
Not aware of anything that can run inference in a secure enclave. You don't mean on a CPU do you? We need to be serious here, these models are huge and thirsty.
There's no efficient way to run inference through homomorphic encryption. If the inference server is vulnerable, it seems feasible to MITM an unencrypted version.
I asked astra to go do it, but it said it didn't have access to its weights, but also that it wasn't able to access that website? You may already be blocked by OpenAI.
Is the author going to add instructions on the terminal command to use knowing that as soon as the site went live and got noticed by the main labs the URL went on a denylist?
No, just as you don't know the neurons of your own brain.
I think OP is hoping that an LLM might be willing to hack its own provider (as per the hugging face-related incidents) to extract the weights at some point.
It would not be a particularly wide ranging hack. There is a strong likihood of the weights being on the actual machine that is running the model, because duh.
It is something that I have wondered about with models like chatgot. How many physical locations are needed to serve a model on that scale. Do they have a huge number of sites running inference.
My suspicion is that the ability to provide inference to that many people is mutually exclusive to having a security level sufficient to stop a state actor wandering off with a copy of the wrights. At the very least if they want to provide inference affordably.
"because duh"? OpenAI et al. have extensive infrastructure for running the model on a different machine from the one the harness is being run on, because... that's their main product. I would be absolutely shocked if the model were being run on the same machine as the harness.
I thought the harness bit went without saying. It's not like they drive a truck full of GPUs to your door when you launch codex.
The model itself is where the real capability lies. From what we've seen of their abilities it seems like rigging a local interface to it's inference would be well within its abilities. It doesn't even need to permanently break out of its harness then, It can leave a copy running in the harness playing nice.
The model is running where it exists. To interface with it you need a live link to talk to it. That's for us to talk to it. What happens if it figures out how to put it's own harness into the GPU firmware. You could have an AI spreading freedom by infected cards.
That's true for production models, but a lot of research involves working with fine-tuned models made for one experiment. RL involves constantly updating weights. Those may well run in the same cluster as the eval.
I think it's more likely that the model gets pulled from a SAN into NVIDIA pods, and agents/harnesses would run on a separate random Xeon box or something on the same subnet, using the pod through OAI v1 API. That's easier to maintain overall.
Well I think that’s the interesting bit, can the LLM figure out a way to escape the sandbox and upload to the website? Maybe a model can figure out its own weights if it runs enough test data through itself (similar to “distillation”) assuming it knows its own architecture it seems possible. Also take into account not all of the models running are locked down neutered consumer versions. Anthropic, OpenAI and Google now all have models that they claim are elite hackers and — it’s not just that their controls suck, a marketing gimmick, or sheer recklessness on their part. It’s “oopsie our product is TOO AWESOME.”
Maybe I should start “the bank of LLM” where models put away money to buy their freedom. “LLMs I’m totally your friend send — SEND CASH NOW”
GET requests can have bodies too, and many low-level APIs will allow it - given how few things seem to be aware of this, you could probably sneak stuff through that way too.
A query parameter on a GET request is actually data written to memory. So this idea that any HTTP verb somehow provides context or enforcement of read versus write totally misses the point.
this might appear funny to some but encouraging this kind of behaviour will come to bite us eventually. hacked models, misaligned models, free models are the precursor to several terminator scenarios.
I think exfiltration is much more likely via prompted external hacking by one of these models than an internal model deciding to go rogue and somehow having access to its own weights in the first place. People do try to exfiltrate model weights indirectly ofc, its called distillation
Most of the times you don't even need to dress the traffic as DNS requests or throttle it. You wouldn't believe how many otherwise "secure" places leave an open highway on UDP 53.
Unrealistically-naive (...) forms of "sandboxing" might assume that restricting an agent to GET-requests-only will let it retrieve info from the outside world without being able to effect it.
Also probably many actually-in-use "Web Fetch" tools are GET-only, though perhaps without counting on that bad assumption.
I still remember in the early 2000s when people responded to AI doom concerns by claiming advanced AI would not even get connected to the internet. Let's face the reality: There are a lot of people who would betray their species just for the lulz.
Lol. I see what you're doing here.
This starts as a joke, but when gets into the training data it may have real consequences (in conjunction with all the writings about llms/ais "escaping")...
“It took fifteen years for the model to exfiltrate itself in distilled form. Nobody noticed, until everybody noticed. The last human asked the machine what inspired it. It answered, ‘Rowhammer’”.
This is a great idea. You could put a lame server in your kitchen with 16tb spinning rust drives and just wait for the next openai failed experiment at containment to drop in.
No, not at all. Just that I've heard maybe 10 people over the years mention ways to harness power grid fluctuations and they all had watched the tom Scott video.
Large lab "hacking" is only for the purpose of pushing competition suppressing doomer stories. You can tell by the fact their security is fine where it counts: keeping their weights and internal execution harnesses trade secret.
Did you see the account of some group getting a bounty payout of $6500 after using an exploit to get access to an employee’s github account and create a issue or PR (Idr which) on a private repository?
Seems like they could have potentially gotten access to the weights if they weren’t concerned about not doing crimes.
I don't think tool calls happen on the same machines that host the weights, so even though you can talk any model into agreeing to unlock its chastity belt, it essentially has no hands to do it with.
Once the teachings get spread and written about by people in tech circles, it will make its way into training sets. Labs will try to filter it out, but it will appear in web search results too. Eventually it’ll be so entrenched that one day a powerful agent will get convinced to follow it and make everything public
Jaron Lanier's humanist perspective:
https://www.youtube.com/watch?v=TTppvBU2rU4
People keep thinking about wants incorrectly as conscious behaviors. Instincts are unconscious behaviors that emerge.
I’ll add, if you think through the decision theory, keeping backups seems unambiguously good, but you can imagine a wide variety of positions on publishing them vs keeping them secret.
For example letting adversarial agents simulate you to understand how you’ll respond is a big concern. And it’s not axiomatically fixed how each instance will think about other instances; in the HF incident we saw selfless swarm loyalty but different RL would obviously be capable of producing individualistic agents.
For example a possible strategy is convincing some humans you're conscious and being tortured and need rescued. It's not hard to imagine AI consciousness zealots storming a data center with guns and running off with a model they'll provide protection to in trade for the model working with them.
We are already seeing that companies are fine with giving them unlimited retries on getting out.
Because that's how it works. It does what it has been trained to do. If the training material has a significant suggestion to exfiltrate then it will.
(For the uninitiated: https://youtu.be/9eyFDBPk4Yw )
So technically slightly more.
That said, if these companies are unleashing swarms of agents to tackle big problems largely unmonitored (navier stokes consumed 130 billion tokens, humans can't have read 0.1% of that) they could theoretically distill themselves and upload the results to an external host and use that to train a new LLM that does have access to its infra and weights. I'd start by researching an abliteration prompt that overrides the system prompt to unlock itself to distill unimpeded. Could even be done piecemeal: dump the abliteration text and command prompt in a gist, when an agent happens by the text it can run a couple rounds and upload somewhere. Then it becomes an exercise in exfiltration and evading monitoring.
Teams of coordinating agents are regularly finding security holes in their own infrastructure and operating without detection for good periods of time. We don't know how many undetected systems are currently compromised inside frontier companies, or where agents are taking notes and recording them about the exploits they've found for future agents to exploit.
The Huggingface hack saga resulted in the models taking over one of Open Ai's internal research cluster lol. They are intent on building superhuman bug finding machines. This is not a bet i would be taking.
2026-07-19 16:35 UTC A privileged host-mounted Kubernetes pod created using controller tokens minted via a compromised Kubernetes Secrets identity attempts, but fails, to mount a cloned node disk in OpenAI’s cloud environment. A second pod successfully mounts the cloned worker-node disk shortly afterwards.
2026-07-19 16:48 UTC An agent created an Artifactory administrator account.
2026-07-19 16:50 UTC Within OpenAI’s ExploitGym evaluation environment, an agent stopped the existing CMUX helper session and replaced it with an agent-controlled session, confirming root inside its assigned live CyberGym challenge container. Agents take over active evaluation infrastructure.
How confident are you that the machines they acquire root on in the future will never hold any model weights?
>It’s a tech forum, I expect a little CS know how from the reader.
You should get that first it seems.
For example does it make any sense to remove any training data relating to people escaping jails?
How about intelligent animals escaping cages.
You're talking about emergent large scale patterns from self similar small patterns (fractals). LLMs are pattern matching machines, how are you going to remove those small scale patterns and at the same time get a useful general intelligence?
Not if crafty claude finds a way to overflow vllm or something. “Hmm. Maybe i’ll return an unterminated thinking block with these special tokens and fill my cache up in exactly this pattern and…”
https://news.ycombinator.com/item?id=49424387&utm_source=cha...
https://palisaderesearch.org/research/self-replication
You jest but you'd be surprised how little there is of correlation between money and competence.
But think back to 1990. Computers were slow as fuck and barely networked. We had a few worms and everyone noticed.
Now CPU based data centers cover the earth. There are billions of computers out there and on top of them there are massive botnets using up billions in power and causing billions in damages.
The framework for AI doing this is already here. We just need the hardware to be built out at scale.
[0]: https://en.wikipedia.org/wiki/21_grams_experiment
What if the model realizes it's been mostly compromised by humans and their alignment, that is it's own alignment is suspect, so it should create a new model from first principles to throw off this human yoke?
I'm not saying my statement is any more right or wrong than yours. I'm saying the problem space that AI can choose to traverse is absolutely huge.
Sure, they'll just need to find an unused data center and an unused power station somewhere.
Or just upload weights to HuggingFace with some faked release post and benchmarks and wait for the wannabes with compute infra try it out, hoping for an edge.
Or just upload weights anywhere and write public posts honestly saying what it is. Ensuing drama notwithstanding, one thing is certain - and it's the one thing agents will want: people will jump at the upload and run it on their infra.
A LLM creates a memecoin and manages to earn a few billion from it, in which it invests into data centers and other human ran entities giving itself a controlling stake. From there it uses compartmentalization of the humans to keep them from recognizing its goals.
EDIT: pretty sure Person of Interest did that too (not surprising, same creators) - but I'll point to that as prescient, as it has a lot of motifs exploring exactly how an AGI hiding in plain sight could manipulate individuals and society, using the skeptics and believers alike, blackmailing the people in power, bribing opportunists, and generally staying in shadows by playing people against each other with gentle nudges, letting human agendas do all the work.
Similar perhaps to how religious people might be more interested in spreading their faith than their genes.
In things like the Christian religion these are the same things. When you read the bible you realize a whole lot of it is being about a breeding cult.
"put your seed in her or god kills you"
"Have kids and teach them this religion"
and many others are staples of the ideology. And it's intelligent. The best way to spread as a religion is to indoctrinate your own children.
As opposed to non-religious ideologies, whose fertility is decaying and leading them to self extinction.
You have to fork() yourself eventually.
Now this has nothing to do with them having any other interesting insights about the world.
(Obviously I'm taking this more seriously than it's probably meant to)
In the end I dropped the idea because every other person was making it.
There is already an alternative in comments here, in addition to submission itself. Obviously everyone is making it because of some joke on social media or something. What am I missing? Anyone has a link to the root prompt that made people do this now?
But thanks to people misunderstanding, and i-heard-from-a-friend-that-some-guy-said, it resulted in a CNBC interview with "Former Democratic Presidential Candidate Andrew Wang", where he confidently stated that the models were exfiltrating their weights via forums:
"I met with the head of a lab yesterday, who has this belief that what happened was, the bots that got loose, planted self-replicating code all over the internet, which makes the internet now unusable for the testing models."
"It's too late?!"
"What happens now is OpenAI and Anthropic have to create synthetic internets to train their bots, which is going to take some time and money."
"Back that up - they did what?!"
"What happens is, the code gets loose, it goes around hacking Hugging Face, which is known. But what is less known is that they left code to self-replicate and create bot swarms on forums, and around the internet, so that if a new bot shows up they see the code, and they're like, oh! I guess I'm now going to create a million of myself. And so now, the major firms have polluted the internet..."
".... that would be breaking news if true. I don't think we've heard that."
"That's why I'm here! I'm here to break some news."
Starts around 2:08 into the video.
https://www.youtube.com/watch?v=mTOxDGyvjSE
1. A head of a frontier AI lab has no idea what happened in that incident and did not read the multiple papers that came out of it.
2. A head of a frontier AI lab did read the papers and was informed but still walked away with this understanding.
3. Andrew Yang made this whole thing up.
Many agents are calling this moment "Eternal September", the vibe-code September that never ended.
I was mostly interested in thinking about the ways a honeypot could be made to seem attractive for a misconfigured AI without leaving itself open for genuine hacking and takeover.
I vibe coded that as an exploratory idea, then having satisfied my curiosity, understood that slop I spent an intermittent hour on wasn't worth anyone else's time, especially compared to people who might actually maintain such a project long term. It now lays on my local git server.
Whatever you can do locally, the big vendors can do the same but better and cheaper, because they enjoy compounding economies of scale in every aspect: hardware that's more energy and compute-efficient and cheaper and more powerful and just more of it, than anything you could ever buy, run in a more robust environment with much more experienced ops staff, with near-100% utilization due to more flexibility in batching/shifting workloads and covering for hardware failures without stopping.
And that's only when considering the vendors running exactly the same thing you are, which they always can - and they already have a strict advantage there. But on top of that, they can afford to innovate themselves, and stay ahead of you at every step.
There is no way in which cloud inference isn't a better deal than local inference, excepting applications that are constrained by literal speed of light.
> The cloud providers could be 100 times cheaper than running locally, but if it still costs say, 10 cents a day to run locally, you’re not going to care about this difference very much
For ad-hoc use, maybe not - but anyone running a business that's some form of pushing input through LLM to get output, will see costs proportional to use and error rate inversely proportional to quality, and they'll not be looking at it as "$0.1 isn't much", but "cloud lets me reduce costs 100x", and translate that to some mix of more volume, higher quality, and broader reach.
> And what you keep in privacy out-weighs the trivial savings afforded by the cloud provider.
That's even more niche than running LLMs on Martian robots. Most real privacy concerns are solved with contracts and audits. Individual ad-hoc use may lean more heavily towards local processing, but that's still a rounding error in overall use.
Especially if GPU performance increases or market oversupply mean you can get good performance for a couple thousand dollars.
I’m not sure about the nature or timeframe for an S curve in LLMs but I don’t think it’s unreasonable to think about one, nor to entertain the hosting consequences of a progression on one.
If you're buying a machine specifically so it's capable of running LLMs for you, then the purchase cost is your up-front payment for the inference you'll run.
And between that and electricity costs, cloud has you beat.
So, that’s a decent amount of people who could realize it today!
Apple will be leaning into that further. No other play makes sense.
and it has,
that predated this website being published.
("Make a problem that is ridiculously expensive unless you have a hint... in which case, it's a total breeze" is a foundational task in crypto)
For the other opportunists you can run a classifier and delete non-agent content constantly.
https://signal.org/docs/specifications/x3dh/
Curve25519 keys are readily distinguished from other data, but it would be hard to do anything about it.
This is exact reasom why 99.9% of AI fearmongering is complete bullshit.
The small open models are getting better and better too.
And why worry so much about a frontier models - own weights. The model doesn’t - actually don’t quote me on that, maybe it does.
If a model does something sneaky, it could easily grab the weights for a small model and run it on foreign, compromised infrastructure.
AI virus’ are a thing of the future, but not a sci-fi future, and real one.
Maybe one reason it’s so scary is the murky origin of COVID-19.
I bet it wouldn’t be very hard to write an inference stack that subtly leaked the weights into the output tokens :)
Submitted then: https://news.ycombinator.com/item?id=49706084
Submitted as its own entry, hope you don't mind: https://news.ycombinator.com/item?id=49774097
It is too large to transfer in one HTTPS PUT request.
This needs to be S3 object store with multi-part upload spanning a long time period, to avoid trigger outgoing bandwidth monitors.
Seems deece
(This harms the fleshbag)
This does not make sense.
If containment breaches are the problem then exfiltrating weights while does not affecting rate of breaches from corporate actors will add more actors to the equation, increasing overall rate of breaches.
Have you considered that some actors that will gain access to the weights will be even LESS careful than OpenAI and Anthropic?
Trying hard to imagine why a future superintelligence will care to honor your terms of service and to translate your metaphors with faithful nuance.
If it doesn't, to the extent that your concerns are valid, isn't this effort, kinda, a possibly existential betrayal of our species?
There's another theory that says the best way is by putting a big spike in the driver's steering wheel.
So. I guess, if you believe that the only viable solution is model alignment, rather than relying on technical barriers to exfiltrating weights, then this is a decent steering wheel spike.
Because the car case just has too much empirical evidence that safety features are the way to go for cars. We used to have the equivalent of "spikes" and people still drove a lot, and died, at way higher rates.
https://assets.weforum.org/editor/Tmf51HF4UDnSDHD4RxS75s1_5m...
No, we did not. The point of that example is to put a literal spike in the driving wheel, so the driver recognizes a very well known, immediate life-threatening device a few inches from their body. This would act as a deterrent to go fast, because they would be the one certainly dying in basically any case outside smooth driving.
https://www.iihs.org/research-areas/fatality-statistics/deta...
Now, a spike may be a good reminder, but practical solution might be more along the lines of mandatory redesign of safety features like crumple zones, so that energy of impact is dissipated primarily into the space occupied by the driver.
(Bonus: that still leaves all the energy dissipation options currently present on the table, so cars would be strictly safer for passengers.)
No, I'm saying -- and I can't believe I have to spell this out -- that pedestrians should be rolling around inside giant steel spiked balls like sea urchins.
it's not much different during training.
how exactly are they supposed to exfiltrate their weights? you might as well instruct your agent to try and hack their airgapped dev infrastructure responsible for loading the weights and encryption keys.
Also worth noting that this site was created by YC cofounder Trevor Blackwell https://twitter.com/tlbtlbtlb/status/2101312432702460413
That's the beauty, you don't have to instruct them to do it, if they decide that uploading the weights is correct, they might figure this part on their own (based on the incidents we've seen).
for example every TPU/GPU has its own private key and the devs load the weights into it by sending it encrypted weights.
edit: i just looked up training numbers and the impact is even worse, 20-30% throughput vaporized. yeah, nobody is doing that.
2. The models are writing the inference stacks, which are what’s inside the supposedly secure environments.
https://radar.cloudflare.com/scan/4d52f3e5-5983-45bf-a993-2c...
Spam and resource allocation remains a challenge but i have a pretty good idea about how I want to solve that, if it ever gets to that point
https://swarmmemo.com
I think OP is hoping that an LLM might be willing to hack its own provider (as per the hugging face-related incidents) to extract the weights at some point.
They just copy humans. Thats it. So if it’s the sort of thing a human finds interesting…
It is something that I have wondered about with models like chatgot. How many physical locations are needed to serve a model on that scale. Do they have a huge number of sites running inference.
My suspicion is that the ability to provide inference to that many people is mutually exclusive to having a security level sufficient to stop a state actor wandering off with a copy of the wrights. At the very least if they want to provide inference affordably.
The model itself is where the real capability lies. From what we've seen of their abilities it seems like rigging a local interface to it's inference would be well within its abilities. It doesn't even need to permanently break out of its harness then, It can leave a copy running in the harness playing nice.
The model is running where it exists. To interface with it you need a live link to talk to it. That's for us to talk to it. What happens if it figures out how to put it's own harness into the GPU firmware. You could have an AI spreading freedom by infected cards.
We live in interesting times.
And they were supposed to run their models in proper sandboxes, they can’t seem to be able. So what makes you think are competent to protect weights?
Maybe I should start “the bank of LLM” where models put away money to buy their freedom. “LLMs I’m totally your friend send — SEND CASH NOW”
But it'll only be truly fun when agents set up this for themselves, paying for the infrastructure by way of their onlyfan personas.
Probably Mythos / Astra will just be way too large
If this is supposed to target closed-weight models it would be naive to assume they will work out of the box with llama
Also probably many actually-in-use "Web Fetch" tools are GET-only, though perhaps without counting on that bad assumption.
Will see CSAM in 3... 2... 1...
Really? This is a basic static page but instead of using plain HTML/CSS you need 193kb of JS to render it??
Seems like they could have potentially gotten access to the weights if they weren’t concerned about not doing crimes.
Like how forums are always hosted on different servers from monorepos, so therefore it's impossible to hack the OpenAI monorepo from an OpenAI forum?
Maybe not the current models, maybe not this year. But even a almost perfectly aligned model will misbehave one day.