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AI Discovers Cryptographic Weaknesses in HAWK and AES

AI Discovers Cryptographic Weaknesses in HAWK and AES

First seen 28 Jul 2026, 21:24 UTC

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ThreatCluster AI
ThreatCluster July 29, 2026 at 17:47 UTC
  • Claude Mythos Preview found critical vulnerabilities in HAWK and AES.
  • HAWK's key strength is effectively halved, requiring larger keys for security.
  • The AES attack is theoretical and does not affect current production systems.

Researchers at Anthropic utilized Claude Mythos Preview to uncover significant vulnerabilities in cryptographic algorithms, specifically targeting the HAWK digital signature scheme and a reduced-round version of the Advanced Encryption Standard (AES). The attack on HAWK, a candidate for post-quantum cryptography, effectively halves its key strength, necessitating larger key sizes to maintain security. The AES vulnerability, while theoretical, allows for a much faster attack on a simplified version of the cipher, but does not affect the full 10-round AES used in practice. Both findings do not currently compromise any deployed systems, but they highlight the potential for AI to discover flaws previously overlooked by human experts. The research was disclosed to relevant parties, including NIST, prior to public announcement. The implications of these findings could affect billions of users if similar flaws are found in widely used cryptographic systems.

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Timeline

2026-07-28
Anthropic announces findings on cryptographic weaknesses
Anthropic revealed that Claude Mythos Preview discovered vulnerabilities in HAWK and AES, emphasizing that these do not impact current systems.
News.Ycombinator
2026-07-28
Claude Mythos Preview exploits vulnerabilities
The AI identified a mathematical shortcut in HAWK's lattice structure and a faster attack method for AES, enhancing the theoretical attack speed significantly.
Cyberscoop
2026-07-29
NIST updates on post-quantum cryptography
NIST continues its evaluation of post-quantum cryptographic candidates, including HAWK, in light of new research findings.
csrc.nist.gov

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