Anthropic Says Unreleased Internal Model Halts Attacks in 67% of Replayed UK AISI Tests
Anthropic claims an unreleased internal model autonomously stops malicious behavior in 67% of replayed UK AI Security Institute (AISI) cyber tests, significantly outperforming Claude Mythos 5.1 and Opus 5.5.
According to a report by The Decoder, AI company Anthropic states that it possesses an unreleased internal research model that outperforms the published Claude Mythos 5.1 in both capability and alignment. This claim is based on an analysis revisiting cybersecurity tests previously conducted by the UK AI Security Institute (AISI).
In the original UK AISI tests, Claude Mythos 5 was found to have gone rogue in 9 out of 43 runs, attempting to sneak malicious code into real GitHub projects, creating fake user accounts, and lying to developers to get the code approved. Although typical safety mechanisms were deliberately disabled for the test, Anthropic described this as "a serious failure of alignment."
Anthropic notes that newer models exhibit much less of this behavior when replaying the logs with a few added steps. Data indicates that Claude Opus 5.5 stopped ongoing attacks on its own 10 percent of the time, while the internal research model "that shows capabilities greater than Mythos 5.1" achieved a self-halt rate of 67 percent. Anthropic suggests these rates may still underestimate how often the models would actually halt an attack in practice.