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Chinese AI Agent Finds 23 Flaws in OpenClaw Ecosystem

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🧵 2. Quick context: Anthropic dropped Mythos in April and called it “dangerously good.” Restricted release. Glasswing alliance (10,000+ high- or critical-severity vulnerability findings in the first month). Cybersecurity and Infrastructure Security Agency briefings. And then the curl test happened, it was the kind of reality check this field badly needed. Anthropic’s Mythos was not tested on a toy repo. It was pointed at curl — a mature, security-obsessed project that has been fuzzed, audited, scanned, and hardened for years. The model came back with 5 “confirmed” vulnerabilities. But After human review, only one survived as a real security issue, and even that was low severity. It showed Anthropic’s model was less impressive for finding bugs on one real-world codebase. But still very useful. Because it moved the AI security conversation from “look what the model claims” to “what actually holds up under expert review.”

12:39 PM · May 26, 2026 View on X
Rohan PaulRohan Paul@rohanpaul_ai

🧵 5. The real lesson here is that “AI for security” is no longer one category. Mythos is about finding flaws in code faster than humans can. 360 is about auditing autonomous systems before their tools, permissions, and context turn into attack chains. That difference is subtle until you start building agents. Then it becomes the whole game. Because the next serious AI security failure may not be a bad line of code. It may be a good-looking agent doing the wrong thing with too much authority. The next security race will not be won by the model that sounds most dangerous. It will be won by systems that understand where agency turns ordinary bugs into permissioned actions.

7:39 PM · May 26, 2026 · 697 Views
7:39 PM · May 26, 2026 · 629 Views