Beyond being a superstar at identifying and exploiting vulnerabilities in digital systems, Anthropic’s Mythos frontier model is now being directed at encryption algorithms that are designed to resist quantum computing attacks.
The early results, as published by Anthropic, are an important glimpse into the future of digital security. Mythos has successfully degraded both the HAWK and a weaker version of AES encryption. The research does not impact current computer systems but it does showcase how researchers can leverage AI to advance attacks against algorithms that we will need in the future to protect our digital ecosystem!
Encryption underpins transactional security and privacy across the digital world. It protects online banking transactions, communications, webpage interactions, and the confidentiality of sensitive data. Unless we want to revert back to face-to-face transactions and paper documents, strong encryption is an absolute necessity!
Over the course of a week, small teams at Anthropic guided Mythos’s mostly autonomous work to achieve these early results. Yes, just one week. To put that into context, it was about a decade ago that NIST asked the brightest minds in the industry to develop robust algorithms that would be resistant to quantum computer-based attacks. Many candidates have undergone years of intense evaluation for becoming the replacements to current algorithms that protect us from traditional computers. Researchers have been testing and working to find weaknesses or break these proposed digital locks for years.
Mythos made progress in days.
HAWK was submitted as an additional potential signature in June of 2023. It benefitted from the deep learnings of previous submissions and research, to join other algorithms that had already been under evaluation but not yet put into practical use. AES, the other target, is perhaps the most commonly used encryption algorithm, which was adopted in 2001.
It is important to emphasize that Mythos did not completely break these algorithms, but rather found paths that reduce their robustness and potentially make future efforts to undermine them easier. With that said, researchers will continue to use frontier AI tools to test current and future security algorithms and they may eventually find ways to break them.
This is both good news, if we find and address weaknesses before any attackers, and potentially cataclysmic if malicious hackers are first to find and exploit algorithms after they have been widely adopted.
Strategically, we are seeing frontier AI models, like Mythos and others, showcase their aptitude at finding weaknesses in software, hardware, algorithms, processes, and people. The AI tools are working at a speed and in ways that humans cannot. That can bring truly amazing benefits, but is also accompanied by equally severe risks.
The key to success will be finding ways to seize the great benefits of AI adoption while managing the risks to acceptable levels.
For cybersecurity specifically, we must support and facilitate AI initiatives in support of business goals, while partnering to manage the cyber risks in acceptable ways.
