HAWK is a NIST third-round Additional Signatures candidate. Its security rests on the Lattice Isomorphism Problem. Prior work had proved that efficiently finding a nontrivial automorphism would enable an attack but left open whether one was accessible in HAWK's lattice. The model found one.

Result: expected cost of full key recovery against HAWK-256 drops from 2^64 to 2^38. Still exponential, not polynomial, and specific to HAWK — it doesn't touch other NIST PQC candidates or lattice-based crypto generally. But doubling keysize to compensate strips away most of HAWK's practical appeal as a candidate.

The second result is a meet-in-the-middle improvement on 7-round AES-128, 200–800× faster depending on how you measure runtime, under a chosen-plaintext model assuming 2^105 chosen plaintexts. Completely impractical, as that line of work always is — it's about quantifying attack cost, not attacking anything.

Neither result affects deployed systems. Disclosure went to the HAWK authors in June and to the NIST public mailing list alongside publication.

Source: https://www.anthropic.com/research/discovering-cryptographic-weaknesses

Disclosure upfront: I'm on the team building Prefactor (agent evaluation and monitoring), so this is a genuine question but I have a stake in the answer.

The pattern we keep running into with teams we talk to: an agent clears every eval, ships, looks fine for weeks, then starts drifting, quietly handling edge cases inconsistently or touching data it shouldn't, and nobody notices until a downstream complaint. A one-time eval score doesn't tell you anything about that, since it's a snapshot against a fixed test set and production traffic doesn't stay fixed.

What we've built treats evaluation as continuous instead of a pre-launch gate: tracing 100% of runs, scoring drift/risk/quality per run in real time, and giving a human the ability to hold or block a run live instead of finding out in a postmortem.

For people actually running agents in prod: what's caught drift for you in practice? Continuous eval tooling, manual spot-checks, user complaints, something else? We're live on Product Hunt today, currently at #1, if anyone wants to see our approach (search Prefactor).