NeuBench

Discovering cryptographic weaknesses with Claude

Researchers at Anthropic used Claude Mythos Preview to discover new attacks on two cryptographic algorithms. The first attack weakens HAWK, a post‑quantum digital signature scheme, by halving its effective key size. The second attack improves the speed of attacks on a reduced‑round version of AES by 200‑800×. Neither attack affects current production systems, but they demonstrate the potential of large language models to find mathematical flaws in cryptographic primitives.

Category
Models
Industry Domain

The Core Development

Using Claude Mythos Preview, researchers at Anthropic have discovered improved ways to attack cryptographic algorithms (the mathematical methods used to keep online data private). The first attack significantly weakens HAWK, a digital signature scheme that was built for a post-quantum world. The second identifies a new way to attack round-reduced AES, the most widely used symmetric cipher. These are substantial research advances, but they do not currently affect any production systems. This post describes both findings in more detail and discusses the implications for cryptography in an age of powerful AI models.

When we launched Claude Mythos Preview, we showed it was able to autonomously find and exploit vulnerabilities in almost every piece of software we pointed it at. This included several major cryptographic libraries—shared collections of code that are used to encrypt data.

The vulnerabilities that Claude found in these cryptographic libraries 1 were due to incorrect implementation of the algorithms—that is, errors in how programmers used the algorithms in their code that created opportunities for attackers to break the encryption.

Real-World Use Cases & Applications

Nevertheless, both results show the potential for frontier AI models to help discover flaws in important cryptographic algorithms, both before and after real-world deployment. This is cryptography research working as intended: stress-testing algorithms to build trust and ultimately make systems more secure.

The multi-agent workflow led to interesting dynamics. For example, the key idea in producing this attack was discovered by a pair of workers working together. Both started investigating the idea; the first worker prematurely rejected the idea as infeasible, but the second found a way to fully exploit it. The pair kept exchanging messages, and eventually both agreed they had found an effective attack.

Strategic Perspective & Ecosystem Impact

Now, we have found that Claude is able to find mathematical flaws in the algorithms themselves .

Cryptographic algorithms are a fundamental building block of digital security. For example, when you visit a webpage like https://www.anthropic.com , your browser checks that it is communicating with an authentic website using an algorithm called a digital signature scheme . Later, the traffic between you and the website is encrypted using symmetric ciphers —codes that allow secure data transmission between parties who share an identical key. Without secure cryptographic systems like these, your email, online banking, and other internet use would be open to cybercriminals, who could intercept or modify your communications. Flaws in these widely used cryptographic systems could put billions of users’ data at risk.

The first result we describe in this post, which was discovered with Claude Mythos Preview, is an improved attack against a digital signature scheme called HAWK . In 2022, the US Government’s National Institute of Standards and Technology (NIST) put out a call for additional cryptographic systems that would remain secure even against quantum computers (which could, if developed, break most of the existing signature schemes in use today). HAWK is one of the third-round candidates under consideration from this call. Despite HAWK having survived two rounds of expert human review over a period of two years, Mythos was able to improve the best-known attack on it in just 60 hours of work—effectively cutting its key strength in half.

Why it matters

The results illustrate how advanced AI can accelerate cryptanalysis, highlighting both opportunities for strengthening security and risks if such models are misused.

Topic dossiers Anthropic & Claude