Historically, Hawk, as a lattice signature candidate in NIST's additional post-quantum signature solicitation, has undergone multiple rounds of expert review over the past two years without being significantly compromised, and is viewed as a potential standardization candidate that is "lightweight, compact, and post-quantum"; Anthropic's Claude Mythos Preview model helped researchers find a mathematical shortcut using non-trivial self-isomorphisms of lattice structures in about 60 hours, reducing the expected attack complexity of Hawk-256 from approximately 2642^{64}264 to 2382^{38}238, effectively halving the effective key strength, which directly undermines the original narrative of "Hawk being both efficient and strongly secure."

In terms of capital and computational pathways, this case demonstrates a new path of "AI as a productivity tool for cryptanalysis": Anthropic reports that researchers achieved breakthroughs on a scheme that had undergone years of human expert review by utilizing high-end models, investing around $100,000 in API costs and several dozen hours of computational power; in the future, funding will no longer only pay for "building secure algorithms" but also for "continuous attacks and reviews of candidate algorithms," rewriting the balance of security budgets between "design and offense/defense," with cloud computing providers and cutting-edge model suppliers upgrading their roles in cryptography and security research from tool providers to core infrastructure.

In analogy and industry positioning, the breach of Hawk and seven rounds of AES by Claude Mythos resonates structurally with the past processes of DES being replaced and MD5/SHA-1 being deprecated: early algorithms were forced out of production environments after new attack techniques emerged; the difference this time is that the attack was assisted by a general AI model, with speed and search space far exceeding traditional manual or semi-automated tools, making the "frontier AI + human expert" combination the new protagonist in cryptographic research and security audits; this also places systems like Bitcoin, which have long relied on fixed algorithms, under external pressure from "AI-accelerated cryptanalysis."

In structural judgment, Guillemet's emphasis on "crypto-agility" essentially belongs to "technological substitution + pricing power transfer + governance model reconstruction": technically, systems must switch from "fixed algorithms for all time" to "pluggable, upgradable algorithm stacks" to quickly replace algorithms when new attacks emerge without rewriting business logic; in terms of pricing power, the cost and value assessment of security will increasingly rely on considerations of "algorithm migrability and update speed," rather than just current formal proofs and parameter strength; at the governance level, decentralized protocols like Bitcoin must establish processes capable of handling algorithm migrations in community consensus, soft and hard forks, and compatibility paths to achieve true crypto-agility, transforming "updating cryptographic algorithms" from a rare extreme event into a manageable long-term mechanism.

ABAB News · Cognitive Laws

When AI begins to perform cryptanalysis, the lifespan of algorithms is determined not by proofs but by computational power and search speed.
If a security system lacks crypto-agility, any new attack could force the entire architecture to be rebuilt from scratch.
In the post-quantum era, a static signature scheme is a risk, while an evolvable cryptographic layer is an asset.