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Anthropic said its Mythos AI security model found a weakness in the post-quantum digital signature candidate HAWK, prompting the algorithm’s withdrawal from NIST consideration after the system reportedly identified a new way to locate automorphisms that cut HAWK’s effective security roughly in half. The same research also improved a meet-in-the-middle attack on a deliberately weakened seven-round AES challenge, reducing the known-plaintext requirement from about 2^105 to 2^89, although both results were described as impractical against widely deployed production cryptography and focused on challenge systems or immature candidates rather than live enterprise deployments.
The developments come amid broader concern that AI is changing how cryptanalytic claims are validated, because multiple researchers may rely on the same models and inherit common failure modes while appearing independent. Recent examples cited in the debate include near-simultaneous July papers on unclonable encryption that both credited OpenAI’s GPT-5.6 Sol Ultra with core ideas, and AI-assisted reviews of a claimed polynomial-time algorithm for the Dihedral Coset Problem that disclosed model involvement unevenly; researchers are calling for clearer provenance, explicit verification-status reporting, and continued emphasis on crypto-agility rather than abrupt changes to post-quantum deployment plans based on early AI-assisted findings.
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Daniel Simon posted a claimed polynomial-time algorithm for the Dihedral Coset Problem. Because of possible implications for assumptions underlying ML-KEM, ML-DSA, and FN-DSA, the claim drew immediate scrutiny.
Review of Simon’s claim on the qcryptanalysis Discord server surfaced serious issues, including disputed points in Lemmas 3 and 4. Daniel Apon circulated “The Search for Simon,” arguing the proof strategy had no local repair, while Michael David Gardiner circulated an AI-assisted draft identifying a post-selection gap.
Pierre Botteron, Anne Broadbent, Eric Culf, Ion Nechita, Clément Pellegrini, and Denis Rochette published a closely related unclonable encryption scheme in Quantum. Later July arXiv papers positioned their own contributions relative to this result.
Prabhanjan Ananth and Amit Sahai posted “Unconditional Unclonable Encryption” on arXiv, and Seyoon Ragavan posted “Efficient Unclonable Encryption from Pauli Eigenstates” three hours and eighteen minutes later. Both papers credited OpenAI’s GPT-5.6 Sol Ultra with core ideas and traced their work to the same open problem raised earlier that month at a Simons Institute talk in Berkeley.
The International Association for Cryptologic Research adopted an AI-use policy applying at Crypto, Eurocrypt, and TCC. The policy bars listing generative AI tools as authors and requires disclosure appendices for substantial generated content.
Yilei Chen posted an update stating that Step 9 of his claimed LWE algorithm contained a bug he did not know how to fix. He thanked Hongxun Wu and Thomas Vidick for independently finding the flaw.
During the NIST PQC Standardization Conference, Yilei Chen posted a claimed polynomial-time quantum algorithm for Learning With Errors. The claim became a test case for how cryptanalytic results are independently reviewed.
Anthropic also said Mythos improved a meet-in-the-middle attack on a deliberately weakened seven-round AES instance, reducing the required known plaintext inputs from about 2^105 to 2^89. The article notes the attack remains impractical outside laboratory conditions and does not affect standard deployed AES.
After Anthropic announced its findings, HAWK’s developer confirmed that the post-quantum signature candidate was being withdrawn from consideration. HAWK had already passed two rounds of NIST evaluation and was in a third round of testing.
Anthropic reported that its Mythos AI security model discovered a previously unknown way to locate automorphisms relevant to attacks on HAWK, improving the best known attack after about 60 hours and roughly $100,000 in compute. The result reportedly cut HAWK’s effective key strength roughly in half.
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Anthropic disclosed that its **Claude Mythos Preview** model helped uncover two new cryptanalytic results: an end-to-end key-recovery attack against the post-quantum signature target **HAWK-256** and a substantially faster attack on **7-round AES-128**. In the HAWK work, researchers said the model identified a previously unused symmetry in the scheme’s lattice structure, cutting the estimated cost of breaking HAWK-256 from about `2^64` to `2^38` operations and making recovery practical for that challenge parameter, while **HAWK-512** and **HAWK-1024** remain impractical to attack. Anthropic said the AES result improved an existing meet-in-the-middle attack by removing a `256`-way guessing step through a new fingerprinting technique described as a **Möbius Bridge**, yielding a roughly **200- to 800-fold** speedup against reduced-round AES-128. The company emphasized that **full 10-round AES-128 remains secure** and that neither finding requires changes to production systems, but said the results show frontier AI can materially accelerate cryptanalysis; Anthropic coordinated disclosure of the HAWK finding with the scheme’s authors and **NIST**, and released technical papers, code, reproducibility artifacts, and a new **CryptanalysisBench** benchmark.
Aug 7, 2026
Reports and commentary have intensified around claims that advanced AI systems can now discover software flaws and, in some cases, produce working exploits for them. A widely discussed account about Anthropic’s reported system, **Mythos**, said access had been limited to about 40 organizations in critical infrastructure so they could identify and remediate vulnerabilities before the capability spreads more broadly. Security contacts cited in the reporting said the tool was finding a notable number of high-quality bugs, while skeptics cautioned that some of the claims may be overstated. The debate has focused less on automated bug hunting alone than on the more consequential assertion that AI can bridge the gap from vulnerability discovery to exploit development, including alleged `zero-day` exploitation against major operating systems and browsers. Separate commentary described the development as a potential **“AlphaGo moment”** for vulnerability research, arguing that once such capability is demonstrated, containment becomes difficult because model replication, distillation, and parallel advances elsewhere could quickly erode any initial controls. The prospect has sharpened concerns for CISOs that defenders may face a dangerous period in which elite organizations gain access to powerful AI-assisted security tooling while critical infrastructure and legacy environments remain slow to patch, harden, or replace.
Jun 29, 2026
Researchers reported that **HAWK**, a lattice-based digital signature candidate in NIST's additional post-quantum signature process, can be weakened when an attacker knows a nontrivial automorphism of the underlying integer lattice. In the paper *"HAWK: Having Automorphisms Weakens Key"*, the authors show that for cyclotomic rings whose degree is a power of two, the search rank-2 module Lattice Isomorphism Problem used by HAWK can be reduced to an instance with at most half the rank, accelerating key-recovery attacks by at least a quadratic factor and effectively cutting the scheme's security margin by roughly half in bits. The work does **not** claim a full practical break of HAWK, but it identifies a new attack avenue tied to the automorphism group of the lattice structure. The paper also links its findings to earlier ASIACRYPT 2024 research by Luo et al., which identified a symplectic automorphism that broke HAWK's original `omSVP` assumption; the HAWK team subsequently revised that definition in its second-round NIST additional-signatures submission. HAWK remains listed among NIST's additional digital signature candidates, making the result relevant to organizations tracking the resilience of post-quantum signature schemes under evaluation.
Jul 29, 2026