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7 posts
perhaps the most important lesson for all of us who are not dillusional from @huggingface's incident report: ``` ... When we started the log analysis, we first used frontier models behind commercial APIs. This did not work: ... these requests were blocked by the providers' safety guardrails, ... We ran the forensic analysis instead on GLM 5.2, an open-weight model, on our own infrastructure. This had a second benefit: no attacker data, and none of the credentials it referenced, left our environment. ... ... The practical lesson ... have a capable model you can run on your own infrastructure vetted and ready before an incident, both to avoid guardrail lockout and to keep ... credentials from leaving your environment. ... ```
Open models are more secure.
The asymmetry problem When we started the log analysis, we first used "frontier" models behind commercial APIs. This did **not work**: the analysis requires submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were **blocked by the providers' safety guardrails**, which cannot distinguish an incident responder from an attacker. We ran the forensic analysis instead on GLM 5.2, an open-weight model, on our own infrastructure. This had a second benefit: no attacker data, and **none of the credentials it referenced, left our environment**. https://huggingface.co/blog/security-incident-july-2026#the-asymmetry-problem
@kchonyc @huggingface Its basis a call for sovereignty
ok the Hugging Face breach writeup is one of the more honest post-mortems I've read in a while, and there's a detail buried in it that's way more interesting than "AI agent hacked us." Their IR team tried to investigate the attack logs using normal frontier model APIs. Couldn't. The safety guardrails on the commercial models wouldn't let them submit the actual exploit payloads and C2 traffic for analysis, because from the model's point of view that just looks like... an attack. So the same guardrails that are supposed to protect you locked their own responders out of doing forensics on their own breach. They ended up standing up an open-weight model (GLM 5.2) in-house just to get through 17,000+ log events fast enough to keep pace with the attacker. That's the real lesson, and it has nothing to do with agents being scary. If your IR plan assumes you'll have clean access to a capable model mid-incident, go test that assumption today, not during the next 2am page. Vet something you can run yourself before you need it. https://huggingface.co/blog/security-incident-july-2026
Hugging Face uses open weights http://Z.ai GLM 5.2 to defend against attacker after commercial frontier model refusal https://ift.tt/1cBW4fb