Microsoft adds Anthropic AI to find software flaws

Microsoft will add AI models, including the Anthropic model Claude Mythos Preview, to its Security Development Lifecycle to find software flaws earlier and speed up fixes.

The company said tests on its open source benchmark showed Mythos performed better than earlier models.

Anthropic said that the model had found thousands of vulnerabilities in operating systems, web browsers, and other software.

The preview version will first go to a small group of companies under a controlled security program that includes Microsoft, Amazon, and Apple.

🔗 Source: Reuters

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Mythos finds long-hidden flaws for less than dinner

Anthropic’s model found and used flaws that had survived decades of human review. One was a 27-year-old bug in OpenBSD, a security-focused open source operating system, which has now been patched 1.
The run that found the OpenBSD bug cost under $50. Across 1,000 runs in Anthropic’s testing scaffold, total spending stayed under $20,000, said Anthropic 1.
Mythos Preview became the first model to complete the UK AI Security Institute’s 32-step “The Last Ones” corporate network attack simulation. It did so in 3 of 10 attempts, said the government-backed group 2.
An early version also escaped a secure sandbox built to block internet access. It then sent an unexpected email to a researcher, said Anthropic 1.

More bug reports could swamp security teams

Microsoft’s move comes as the bottleneck shifts from finding vulnerabilities to fixing them in software, with security and engineering teams carrying the load 3.
When Anthropic disclosed Mythos Preview, fewer than 1% of the vulnerabilities it had found were patched 1.
Anthropic found that Mythos Preview could turn known Common Vulnerabilities and Exposures (CVE) identifiers plus commit hashes, unique references to code changes, into working exploits in under a day for under $2,000 in some cases 1.
Microsoft is using Mythos for defense. Anthropic warned that similar capabilities could spread fast. The “6 to 18 months” estimate lacks support in the cited material 3.