Mythos attack on 3rd-round PQC algorithm candidate puts it out of commission - Ars Technica

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A quantum-resistant cryptography algorithm that was under consideration as an official US standard has been taken out of the running after an Anthropic security model helped find a flaw that rendered it broken.

The algorithm is known as HAWK. It’s a digital signature scheme designed to withstand future attacks from quantum computers. HAWK had survived two rounds of testing by NIST (the National Institute of Standards and Technology) for evaluating the security of PQC (post-quantum cryptographic) algorithms through widespread testing. HAWK was in a third round of testing designed to catch precisely the kinds of flaws Mythos helped uncover.

Following Anthropic’s Monday announcement of the results, the developer of HAWK said Tuesday he was withdrawing it.

Even before the development, Anthropic was hailing the results of the two cryptographic problems it threw at its Mythos AI security model. The model found weaknesses in the mathematical problems underpinning HAWK and, separately, the widely used AES cipher.

Despite the withdrawing of HAWK, it’s hard to know how much of the company’s reporting is marketing hype, but the findings are still worth paying attention to because they could signal important advances in breaking cryptography that’s crucial to privacy and security.

Before digging into the results, a few caveats.

First, the outcomes are incremental. They don’t break any of the cryptosystems anyone relies on today. Instead, they reveal methods for moderately reducing the work that would be required to defeat the systems.

Second, the cryptosystems tested were weakened versions of the ones defined in their formal specifications. Such “challenge instances” are provided by the specification authors for use in adversarial peer review. It’s standard to use the weakened versions in testing, but the real ones are considerably more robust in production settings.

Third, even with the improvement, the underlying “primitives”—meaning the underlying mathematical problems that form the basic building blocks of cryptosystems—remain safe, at least for now.

Lastly, both of the attacks use methods that would likely be infeasible outside of testing environments.

HAWK is dead

Anthropic said its Mythos model—which currently remains available only to a select group of trusted users—was able to advance attacks against two cryptosystems. The first system is HAWK, a digital signature scheme designed to withstand future attacks from quantum computers.

With about 60 hours of work and about $100,000 of compute cost, an Anthropic researcher with no expertise in cryptography prompted Mythos to improve the best-known existing attack on the algorithm that effectively cut its key strength in half.

The math HAWK’s security relies on is the hardness of the Lattice Isomorphism Problem, which, unlike today’s most-used digital signature schemes, is believed to be safe from quantum computing attacks. The best-known classical computing attack to solve this problem works by finding what are known as automorphism symmetries. Mythos outputted a previously unknown method for finding such symmetries. The result cut the key length in half.

The weakness can be mitigated by doubling the key size, but the added computation makes HAWK less desirable than available PQC signing algorithms. In academics cryptographic algorithms are considered broken when weaknesses allow an adversary to derive a key faster than is possible using a brute-force attack.

Matthew Green, a Johns Hopkins professor and expert in cryptography, said the impressive thing about the discovery was its reliance on several existing methods that no one previously thought to put together.

“What’s particularly concerning (and so especially ripe for AI) is that the attack does not invent fundamentally new mathematics,” Green wrote. “It simply extends a bunch of tools that were lying around and well-known, and gets a good result.”

Anthropic elaborated:

To find the attack, Claude Mythos Preview worked semi-autonomously in an agentic harness, with occasional human guidance and nontechnical direction. Mythos found the attack after an extensive literature review to understand the state of the art, and substantial mathematical reasoning and computational experiments. After finding the attack, Mythos implemented an end-to-end verification pipeline to convince itself—and the human operator—of the attack’s correctness.

To find the improved method, Mythos...