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This research demonstrates a significant shift where AI models like Claude can autonomously identify mathematical flaws in core cryptographic algorithms, moving beyond mere implementation errors to challenge the fundamental security of post-quantum schemes and symmetric ciphers. While these specific findings do not yet impact production systems, they highlight an emerging capability for AI-driven adversarial discovery that could reshape how digital trust is verified against future quantum threats.
Surse care acoperăGDELT, Cybersecurity News
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Discovering cryptographic weaknesses with Claude

GDELT18 min de cititArticolul și perspectiva sunt în engleză.

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 libraries1 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. 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…

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