Anthropic says its Mythos model found vulnerabilities in cryptographic algorithms that secure the internet Key Points - Anthropic's AI model Claude Mythos Preview found mathematical weaknesses in cryptographic algorithms, including a reduced version of AES, the world's most widely used symmetric encryption standard. Anthropic says the findings have no immediate impact on systems currently in use. - Working largely on its own in a multi-agent system, the model developed two attacks at an API cost of roughly $100,000 each. - According to Anthropic, the human researchers mostly handled project management, provided simple prompts, and later verified the results. Anthropic's AI model Claude Mythos Preview found mathematical weaknesses in cryptographic algorithms that underpin digital security. According to Anthropic, the model developed an improved attack on the post-quantum signature scheme HAWK and a new attack on a reduced version of the Advanced Encryption Standard (AES). Encryption protects nearly everything people do online, and AES is the world's most widely used symmetric encryption standard for digital data. Anthropic says neither finding affects systems in use today. HAWK is only a candidate in an ongoing standardization process run by the U.S. National Institute of Standards and Technology (NIST) and the AES attack applies to a modified version that uses 7 of the full scheme's 10 rounds. Still, the results show how AI models could challenge core assumptions behind internet security. Mythos found the HAWK attack in 60 hours for $100,000 HAWK is one of the remaining schemes in the third round of NIST's competition for additional post-quantum signatures. These schemes are designed to stay secure even against future quantum computers. Human experts had reviewed HAWK for over two years, but Mythos Preview found an improved attack in just 60 hours, according to Anthropic. The attack exploits a previously undetected symmetry in the mathematical lattice
Anthropic says its Mythos model found vulnerabilities in cryptographic algorithms that secure ...
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