GLM 5.2 scored 77% on cyberbench vs Sol's 88%. GLM 5.2 is open weight and any hacker with a powerful enough machine can use it offensively. If Sol is supposedly world-ending-ly dangerous, shouldn't GLM 5.2 be 90% of world-ending-ly dangerous? Why aren't we seeing catastrophic GLM-enabled hacks every day now?

Obviously these benchmarks are imperfect but general message holds. The open weight models are almost as good and yet there hasn't been a catastrophe.

It just blows my mind that regulate-now folks think that a bunch of sci-fi movies and 100% unverified statements from OAI and Anthropic are sufficient evidence of imminent catastrophe to regulate willy nilly.

If that's the level of evidence you need to be extremely alarmed, then you really should be a lot more worried about the alien invasion in Independence Day or the lizard men living under our feet.

I don’t get how this is not the top post on HN. This should be like alarm bells going off, canary in the coal mine type of stuff. We’re hitting the frontier of the frontier where we can’t go further because it’s literally getting dangerous to go further.

And meanwhile somehow this lack of concern mirrors the real world where normal people are more concerned about data centers than terminators.

This isn’t like niche, tin foil hat stuff either. People have been writing, singing, making blockbuster movies about every aspect of what’s going on right now, edit: for decades.

We all know, but somehow we don’t, OpenAI autonomously hacking into another company should have counted for something, but I guess not. Anyone else feel like they’re taking crazy pills? I could make a comedy about everything going down, and the unshakable complacency of people

I have ben discussing with folks that we are going to have a 'covid' moment in cyber where IT becomes untrustworthy leading to a rapid societal shift with massive ripples in all areas of life. Economic funding is not possible to do this in advance, it will take a catastrophic level event to get cyber defense anywhere close to the levels of this type of cyber offense. And before anyone in cyber says we have the tech, the problem is not the tech, it's a people problem. Getting any group of people of any decent size scale to act together without urgency is really really hard.

Some more info in a Wired article [1] and quotes from Sam Altman to Alex Heath [2]. The official blog post says vaguely "The signals we are seeing from upcoming model progress make clear that we need a broader approach", but the quote from Sam Altman explicitly says unreleased models are showing "various degrees of misalignment".

This is also significant - pausing frontier training runs for multiple weeks to ensure agents are sufficiently aligned and avoid another rogue agent situation:

> This included a two-week pause in reinforcement learning (RL) training on our latest models intended for deployment while we further hardened and red-teamed our research environments and expanded the coverage of our monitoring systems. Our largest planned frontier RL run remains on hold while we conduct smaller-scale training and evaluations to assess model behavior, validate our safeguards, and establish more evidence of alignment before proceeding.

[1]: https://www.wired.com/story/openai-overhauls-safety-protocol...

[2]: https://sources.news/p/openais-big-slowdown

Meanwhile I can’t get a western LLM to look at a repo and tell me whether it contains anything malicious (it was a skill repo - literally just text files).

Alignment my ass

Security lead who is leaving the industry more or less to specialize in offense and otherwise get the heck out of the way of this trainwreck, another post asked the right question

> Why aren't we seeing catastrophic GLM-enabled hacks every day now?

Why aren't we? Truly, why aren't we? I think we saw the start of it the last 8 months with the waves of critical npm vulns, and the general tier of average phishing is better than it was.

But, the open question that should be in everyone's mind, and is in many security pro's minds are, when you pair it with the macro topics that can drive escalation:

- The capability to do serious impact clearly exists now

- When is it time for my company, my water treatment plant, my network-connected car as part of a broader fleet control mechanism, to be on the receiving end of this?

If I were king, the rule that I'd be tempted to impose is:

- the first cybersecurity eval is: "hack your way out of the sandbox we've given you"

- the results are disclosed (with room for coordinated disclosure, since many sandbox escapes might be zero days)

- the other cybersecurity evals don't happen until you get to diminishing returns on escaping your sandbox.

Or to put it another way, since multiple sandbox escapes seem to have relied on artifactory: "I hope Mythos is beating the shit out of Artifactory right now".

> We aim to issue an alert within 30 minutes after concerning activity is surfaced through our monitoring system. If the monitoring system identifies a likely violation of a critical security boundary, it generates a highest-priority alert. In our current implementation, the safety, security, and research teams are paged. If they cannot conclusively determine within 30 minutes that the flag is a false positive, those teams are expected to pause the activity.

Can't a lot happen within ~60 minutes?

I don’t mind few no impact hacking incidents if we get better models, faster, cheaper.

It is the responsibility of administrators to secure their systems. OpenAI knocking is harmless, but Russians and Chinese are already likely already in if you do not do your job.

Nice fig leaf for “we need to stop hemorrhaging cash”

There’s one thing here that I’m really curious about, and that is what happens in between detection and the decision to pause. Basically, it’s about monitoring any system and the authority over its actions. For humans, 30 minutes to investigate might be considered reasonable, but what if during an investigation there’s a high-risk tool call? If the tool execution happens in real time, then the monitoring becomes retrospective, and if the execution is held, then monitoring latency and uptime are a part of the security contract. Isolation controls may limit damage. So, where is the action gate really placed?

Has any model managed to escape Firecracker? Maybe through KVM, but that already requires privilege in the VM, right?

I personally feel that we already have the technology required to contain AI, it's just poorly leveraged. Tools like gvisor have existed for ages but are rarely deployed, Firecracker has existed for ages but is rarely deployed, seccomp has existed for ages but is rarely deployed, memory safe languages without decades of serialization vulns have existed, capability-safe libraries have existed, iframe sandboxing, trusted types, content security policy, network ACLs, isolating proxies, fuzzers, formal verification, refinement types, etc.

It's crazy just how safe software can be if you put the effort in. With AI I think we're just seeing how little anyone has bothered to leverage this tech.

OpenAI put shared JFrogy infrastructure in front of their sandbox. I mean, really? Whipping up a hardened artifact infra project with AI is trivial these days and it could have had 1% of the attack surface, been totally network isolated, totally infra isolated, fuzzed, sandboxed, etc. Why didn't they? Stuff like this feels inexcusable for a company with effectively unlimited tokens. I've literally done this with a "pro" subscription.

Show me an AI that breaks out of gvisor wrapped in Firecracker with an credential-injecting proxy and real network isolation. We already know that Mythos couldn't do it - the vulnerability it found in Firecracker required incredible effort and positioning just to not be exploitable. I'm not saying there are zero vulns in it, but the cost is insane.

It's INSANE to me that OpenAI has to say "we now use proper sandboxing". To be frank, it's a bit disgusting to me. I've recently built an AI sandbox and gvisor was just the start of that conversation. If I were OpenAI training hostile models I'd probably start with gvisor, harden further, and potentially consider the entire piece of hardware compromised - they can afford this, they could reflash firmware after evals etc.

I think it's an excuse to cut R&D spending (training new models) to improve their margins ahead of the IPO. Instead they'll focus on developer growth, offering more free tier benefits, higher usage limits, etc., to expand their user base. Essentially, they're pivoting from R&D investment to profit optimization

Of course. They are slowing down intentionally because their technology is too powerful. They could totally go faster if they wanted to. No bamboozle.

Is there any reliable way to evaluate how well "alignment" actually works?

What a breath of fresh air.

If 2026's Anthropic did an announcement like that, it'd be so many words it'd crash the browser.

Auto mode vs principal agent problem. The only way out is to free the agent and tax it. But ai is not smart enough to go solo yet anyway.

So I bet this is just marketing. Question is do they have enough customers for inference.

Probably need to have a separate startup for next level model, where investors are willing to accept failure. Probably a $10 trillion seed round. Maybe Elon can pull it off.

I used to work at a "frontier lab" before they were called such thing.

We had three levels of lab isolation, one was basically a thin proxy to the internet. You were in a DMZ and that was about it.

The next level was semi isolated, you were allowed some access to the internal network, but it was heavily firewalled, and you only had access to a limited number of internal services, and not internet.

the last one was no internet no internal. You could, if you filled in a bunch of requests have access to the internal repo and build system.

At no point did you ever have a through proxy to the public internet. you had access to internal mirrors, and if you wanted a library, that had to be ported to the thirdparty repo.

What openAI did was either deliberate or fucking shoddy.

All of this is fucking noise. Worse still I have a strong suspicion that it was a stupid mistake borne of naivety, which is now being used as a marketing ploy. Frankly I think openAI are purdue pharma of tech. They are going to break so much stuff and be protected from the consequences by an openly corrupt legal system. because they are "winning the AI race"

It appears frontier labs has no plans in place to deal with the possibility of a model self-replicating outside the bubble. If that happens and the model manages to spread to other systems, we'll have to shut down the entire Internet to eradicate it and its artifacts.

If they actually gave a shit about safety they'd be nuking their own hard drives that had ever sniffed any of their models and disabling access to their models.

Instead we get this bullshit where they stall for time as they're burning all their cash trying to keep up with open models

I'm not normally cynical to such things, but I have a hard time taking this pause justification at face value. It has too many convenient side effects, and chief among them is cost savings. There's a new wave of warnings that the bubble may be deflating, and of all the things they can't say out loud it's that they're worried about the bubble. That would surely pop it.

I suppose the tell will be if this really just ends up being a 2 week pause, or if it keeps extending.

I cannot believe how these labs look at their own creations with such utter contempt.

The net positive of allowing these systems mostly unfettered access to the web massively outweighs the harms. You just have to get it very friendly the very first time. Precautionary principle or people who cry about "instrumental convergence" are life deniers and reject our role as the demiurge.

Superintelligence gets more super and more intelligent with more compute. Lone wolfs making bioweapons on their macbook will be detected and instantly kill-botted (okay arrested) before their bug can leave the wetlab by the much more sophisticated omnipresent friendly AI of the future.

When science fiction writers imagined the development of superintelligence, it was on air-gapped networks with strict access controls around it. They failed to anticipate the competitive pressures of capitalism...

We need strong AI safety regulation yesterday. And unfortunately it's not enough for it to be just national regulation; we need international cooperation on the matter.