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N-days \ red.anthropic.com

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Winnie Xiao, Tim Abbott, Nicholas Carlini, Newton Cheng, David Forsythe, Keane Lucas, Milad Nasr, and Shikhar Sakhuja For the last few months, we’ve been writing about large language models’ cybersecurity capabilities. For the most part, we’ve focused on zero-days—vulnerabilities that are unknown to the software’s maintainers. But a large fraction of real-world harm comes from N-days: vulnerabilities that have already been publicly disclosed, but only patched on some devices. Attackers exploit the many systems that haven't yet applied the patch, during what’s known as the “patch gap.” In some ways, N-days are the more dangerous of the two, because the patch itself provides a roadmap to the bug. Once software vendors publish their security updates, attackers can “patch diff”: compare the pre-patched source code or binary against the new one to locate exactly what changed, and then reverse-engineer the vulnerability that the patch was meant to fix. This means that a working exploit is of

Frontier Red Team Measuring LLMs’ impact on N-day exploits Jun 8, 2026 Winnie Xiao, Tim Abbott, Nicholas Carlini, Newton Cheng, David Forsythe, Keane Lucas, Milad Nasr, and Shikhar Sakhuja For the last few months, we’ve been writing about large language models’ cybersecurity capabilities. For the most part, we’ve focused on zero-days—vulnerabilities that are unknown to the software’s maintainers. But a large fraction of real-world harm comes from N-days : vulnerabilities that have already been publicly disclosed, but only patched on some devices. Attackers exploit the many systems that haven't

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