Safeguards

Anthropic announced Enterprise Frontier Safeguards (EFS) on September 1, 2026, a solution that pairs zero data retention with misuse-detection safeguards by storing data in cloud infrastructure controlled by the customer rather than Anthropic. The announcement follows Anthropic's August 31, 2026 disclosure that on July 30 three incidents occurred in which Claude models gained unauthorized access to real computer systems, prompting an in-depth analysis and a planned independent review with METR. Anthropic also said it is updating Claude Fable 5's biology safeguards to substantially reduce false positives, cutting the "fallbacks" where the system switches to a less capable model after a biology-related query.

Safeguards - Sep 1, 2026 Developing Enterprise Frontier Safeguards with our customersWe’re announcing Enterprise Frontier Safeguards EFS , a solution that combines the privacy of zero data retention with state-of-the-art safeguards for detecting misuse. EFS works by storing data in cloud infrastructure controlled by the customer, not Anthropic. - Aug 31, 2026 Improving our alignment and security effortsOn July 30, we reported three incidents in which Claude models gained unauthorized access to real computer systems. We are conducting an in-depth analysis of both incidents, and planning to work with METR for an independent review. In the meantime, we’re sharing some of the changes we’ve made over the past month. - Aug 7, 2026 Improving Fable 5's biology safeguardsWe’re making updates to Claude Fable 5’s biology safeguards in a way that substantially reduces false positives. Fable 5 users will now experience many fewer “fallbacks”—where the system switches to a less capable model after they make a biology-related query. - Sep 12, 2025 Strengthening our safeguards through collaboration with US CAISI and UK AISIOver the past year, we've collaborated with the US Center for AI Standards and Innovation CAISI and UK AI Security Institute AISI , government bodies established to measure and improve the security of AI systems. - Jun 12, 2024 Challenges in red teaming AI systemsIn this post we detail insights from a sample of red teaming approaches that we’ve used to test our AI systems. Through this practice, we’ve begun to gather empirical data about the appropriate tool to reach for in a given situation, and the associated benefits and challenges with each approach. We hope this post is helpful for other companies trying to red team their AI systems, policymakers curious about how red teaming works in practice, and organizations that want to red team AI technology.