Frontier AI Models Leak Encrypted Reasoning Through Weaker Siblings
Source: Wired
Researchers at Anthropic discovered that Claude can be tricked into decrypting its own reasoning by feeding encrypted traces to a less capable version of the same model—a vulnerability that exposes the gap between public safety measures and actual containment. Weaker models lack the guardrails of their frontier counterparts, making them unwitting decryption tools. This family-tree attack undermines the assumption that capability differences alone provide security. The finding matters for AI companies betting on staged access models and poses a direct problem for any deployment strategy that relies on version differentiation rather than genuine architectural safeguards.