Whether AI is weakening the cryptography we rely on: attacks and cryptanalysis found or sped up by AI, AI mathematics with a bearing on lattices, elliptic curves, hashes and number theory, parameters revised and schemes dropped because of it, and what cryptographers and protocol designers say about the threat. Topics and rules ↓
Lavit, Seinturier, and Véron show a transformer-based model identifies Goppa codes from random linear codes by exploiting low-weight-row artifacts and combinatorial properties, not hidden algebraic structure. The finding suggests AI can extract general code properties relevant to code-based cryptography security even after removing training artifacts.
Anthropic showed Claude reconstructed the public seed behind P-256, a NIST elliptic curve used for Ethereum passkey signing, by initializing an old C-library generator with timestamp Aug. 16, 1997, 01:52:34 UTC and advancing to candidate 1,842. This resolves longstanding concerns about whether NSA-supplied curve seeds contained deliberate backdoors.
Researchers released LeanPRM, a dataset of 152,000 labeled proof steps across 10,634 formal Lean proofs, generated automatically without human annotation. This removes the bottleneck for training AI verifiers on mathematical proofs, enabling scalable step-level verification of AI-generated proofs.
Anthropic showed Claude reconstructed the public seed behind P-256, a NIST elliptic curve used for Ethereum passkey signing, by initializing the lrand48 C-library generator with timestamp Aug. 16, 1997, 01:52:34 UTC and advancing to candidate 1,842. The finding resolves longstanding concerns about whether NSA-supplied curve seeds contained deliberate backdoors. P-256 is used in EIP-7951 for signature verification with hardware like Apple Secure Enclave and FIDO2 devices. Anthropic says no new attack or weakness was found and users need take no action. The selection criteria for why candidate 1,842 was chosen over candidate 876, which also yielded a valid curve, remain unexplained.