Measuring Human Cryptanalysis Effort: How Scrutinised Is Your Crypto?
Matthew Green's new site estimates how many researcher-years of public cryptanalysis different public-key assumptions have received. It is a useful first metric for post-quantum migration decisions, and it comes with caveats.
AI Cryptanalysis: Green's Worst Case vs Schneier's Over-Engineering Bet
Matthew Green has publicly floated worst-case scenarios for AI-driven cryptanalysis; Bruce Schneier counters that cryptographers' habit of over-engineering is a real safety margin. Neither side has a demonstrated break, so the useful question is what to prepare now.
CryptanalysisBench: Frontier LLMs Are Now Finding Novel Cryptographic Attacks
A new academic-Anthropic benchmark shows frontier models breaking real cryptographic tasks — and one model surfaced a genuine design flaw and a proof error in NIST-track candidates, not just textbook exercises.
Claude Mythos Finds Real Math Flaws in HAWK and Weakened AES
Anthropic researchers used a specialised Claude model to discover a genuine cryptanalytic improvement against the post-quantum HAWK signature scheme and a reduced-round AES-128 variant — theoretical results, but a notable data point for AI-assisted cryptanalysis.