Anthropic study shows AI can build working exploits from security patches in hours, not weeks

Reddit r/ArtificialInteligence Papers
ai-security exploit-generation large-language-models vulnerability-research anthropic patch-analysis

Summary

Anthropic's study demonstrates that large language models can rapidly generate working exploits from security patches, reducing the time from weeks to hours, raising concerns about AI-driven vulnerability exploitation.

https://preview.redd.it/bj4cb914nm6h1.png?width=1376&format=png&auto=webp&s=503dba9ffad477c7e72f000305d9c59e2edb846a Anthropic's security team systematically measured how fast large language models can exploit known vulnerabilities in Firefox and Windows. The study revealed that a single operator can now turn a month's worth of patches into working exploits in an afternoon for a few thousand dollars with no expert knowledge. Testing 6 Claude models, the researchers targeted 18 SpiderMonkey patches in Firefox. Mythos Preview successfully cracked 14 vulnerabilities, producing 8 working exploits in roughly 12 hours. The first exploit was ready in an hour, 18 days before the patched Firefox 148 officially shipped. In a second test, the model targeted 21 Windows kernel vulnerabilities. Mythos Preview found 18 flaws in under 6 hours for $2,200 in API costs and built 8 complete privilege escalation chains for $15,700. In contrast, Windows Autopatch takes 7 days to deploy security updates to 90 percent of devices. Source: [https://the-decoder.com/anthropic-study-shows-ai-needs-hours-not-weeks-to-build-exploits-from-security-patches/](https://the-decoder.com/anthropic-study-shows-ai-needs-hours-not-weeks-to-build-exploits-from-security-patches/)
Original Article

Similar Articles

Anthropic is finding bugs faster than Microsoft can fix them

Ars Technica

Anthropic's Mythos AI model has been uncovering critical and important bugs in Microsoft's SharePoint and other software at a rate that outstrips Microsoft's ability to patch them, raising urgent security concerns about adversaries exploiting the same vulnerabilities.

Measuring LLMs' impact on N-day exploits (18 minute read)

TLDR AI

This article from Anthropic evaluates how large language models like Claude Mythos Preview can accelerate the development of exploits for N-day vulnerabilities. Across tests on Firefox and Windows kernel patches, the model autonomously built working exploit chains, highlighting increased risks in the patch gap.

Jun 8, 2026Frontier Red TeamMeasuring LLMs’ impact on N-day exploits

Anthropic Research

Anthropic's Frontier Red Team evaluates how large language models can accelerate the exploitation of N-day vulnerabilities, finding that Claude Mythos Preview can autonomously build working exploits for 8 out of 18 Firefox patches and 8 out of 21 Windows kernel patches, highlighting increased threats during the patch gap.