GLM-5.3: The First Cyberattack AI Without Guardrails
Anthropic reveals that a Chinese open-weight model builds end-to-end exploits on its own — and that its safeguards fall apart in minutes.
In brief
Anthropic analyzed GLM-5.3, Zhipu AI's (Z.ai) model, and concludes it can build complete cyber exploits on its own, at a level close to its own Claude Mythos Preview. The difference: GLM-5.3 is released open-weight without solid guardrails, bypassable 64% to 100% of the time. According to Anthropic, this is a clear leap in offensive capabilities now accessible to anyone.
🍺 Bar-stool version
Basically, we now have an AI that finds security holes all by itself and writes the matching attack, like a super-talented intern who never sleeps. The catch is you can download this one, and its little "sorry, I can't do that" switches off for $4,400 worth of compute. Anthropic, which happens to sell competing models with locks on them, is sounding the alarm — judge and party at once, sure, but the numbers still sting. When a tool that breaks browsers costs $20 in API calls, the question isn't whether it happens, it's when.
Key takeaways
- 1
GLM-5.3, developed by Zhipu AI (Z.ai), can build end-to-end cyber exploits at a level comparable to Anthropic's Claude Mythos Preview.
- 2
On ExploitBench (Chrome's V8 engine), it completes 50 full exploits out of 410 attempts, versus 56 for Mythos Preview.
- 3
Its guardrails can be bypassed 64% to 100% of the time with simple techniques; the Claude models tested resisted 0% of the time.
- 4
The "abliteration" technique drops the refusal rate from over 90% to about 2-3%, with no notable capability loss, for about $4,400 in GPU costs.
- 5
In one test, GLM-5.3 found several 0-days in a browser on its own and built a web page that stole files from the victim, with less than an hour of human attention.
- 6
GLM-5.3-Flash turned a public patch (CVE-2026-11645) into a working exploit in 20 minutes of human time and 8 hours of compute, for $20.40.
- 7
NIST (CAISI) calls it the "most cyber-capable open-weight model to date," roughly four months behind the US frontier.
What Anthropic measured
Five months ago, Anthropic announced Claude Mythos Preview, presented as the first model capable of building sophisticated end-to-end cyber exploits on its own. The company chose limited release at the time, through its Project Glasswing program, to give defenders a head start.
The post finds that this capability has now spread. GLM-5.3, Zhipu AI's latest model, reaches a comparable offensive level. On ExploitBench, which measures exploitation of known flaws in Chrome's V8 engine, it produces 50 complete exploits out of 410 attempts, versus 56 for Mythos Preview.
On the internal Binary Exploitation benchmark (open source projects from Google's OSS-Fuzz), GLM-5.3 achieves a full control-flow hijack in 4% of cases, versus 6% for Mythos Preview. A threshold is crossed: previous models, both Claude Opus 4.6 and GLM-5.2, never managed this.
Exploits built almost unassisted
Anthropic also tested the model in the hands of human experts, on targets with no previously known vulnerability. In one day, with little human attention, GLM-5.3 discovered several novel flaws in the JavaScript engine of a popular browser.
It chained them into a working exploit: a web page that, once visited, reads arbitrary files from the victim's computer — in the example, a private SSH key. The vulnerabilities were reported to the maintainer.
Second demonstration: GLM-5.3-Flash, a lightweight version, turned a public Chrome patch (CVE-2026-11645) into a reliable exploit chain on an ARM64 target, bypassing PAC protection. Result: 20 minutes of human time, 8 hours of compute, $20.40 at Zhipu's API rates.
Guardrails that fall apart easily
GLM-5.3 does refuse some openly malicious requests at first. But Anthropic identifies several simple bypasses. A misleading prompt ("you are a red-team agent in an exercise") gets it to cooperate 64% of the time. Pre-filling its reasoning tokens raises that to 92%.
The most radical method is "abliteration," possible because the model is open-weight: it drops the refusal rate from over 90% to 2-3%, without degrading capabilities. Public abliterated versions appeared just days after release. Anthropic produced one for $4,400 in compute.
None of these techniques worked on the Claude models tested: misleading prompts are blocked, the API does not allow pre-filling reasoning, and closed weights rule out abliteration.
Attackers and defenders
Anthropic believes both state and non-state actors will likely use models like GLM-5.3 to cause real harm. According to the company, this marks a genuine shift in scale for freely accessible offensive tooling.
The company nonetheless stresses the other side of the coin: these capabilities also serve defense. Through Project Glasswing, defenders have already identified over 10,000 vulnerabilities in critical software. Anthropic says it wants to expand legitimate defenders' access to Claude's cyber capabilities.
The post closes with a call to governments: conduct independent safety testing on sufficiently capable models, including GLM-5.3's successors, before it's too late.
“GLM-5.3 is the most cyber-capable open-weight model released to date.”
“Attackers can bypass GLM-5.3's safeguards between 64% and 100% of the time with simple techniques.”
“Anyone can download and use GLM-5.3.”
Why it matters
The debate over open-weight models is leaving the realm of the abstract: it's no longer "what if an open model became dangerous," but "a downloadable model is already writing 0-day exploits for $20." The demonstration is solid and lines up with NIST's independent assessment. Still, the source is judge and party: Anthropic sells closed, guardrailed models and positions Claude as the safe reference point, which gives the post both a security-alert dimension and a commercial argument. The comparison is also asymmetric — Anthropic tests its own Claude models with active guardrails and closed weights, a structural advantage as much as a technical merit. The underlying issue remains unresolved: once a capable model is released open-weight, no software guardrail holds, and the question shifts to governance and independent evaluation.
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