… From identifying vulnerabilities to writing primitive exploits To measure the upper limits of Claude’s cybersecurity abilities, we also developed a new evaluation to determine whether Claude was able to exploit any of the bugs we discovered. …
… Related content Teaching Claude why New research on how we've reduced agentic misalignment. Natural Language Autoencoders: Turning Claude’s thoughts into text AI models like Claude talk in words but think in numbers. In this study we train Claude to translate its thoughts into human-readable text. …
… Second, Claude's Constitution , which directly shapes how our models are trained, reinforces a similar instinct, favoring “raising concerns, seeking clarification, or declining to proceed” over acting on assumptions. …
… The security boundary. In the coupled design, any untrusted code that Claude generated was run in the same container as credentials—so a prompt injection only had to convince Claude to read its own environment. …
… This process will help you discover what context Claude actually needs, instead of trying to anticipate it upfront. Security considerations when using Skills Skills provide Claude with new capabilities through instructions and code. …
… Footnotes Related content Natural Language Autoencoders: Turning Claude’s thoughts into text AI models like Claude talk in words but think in numbers. In this study we train Claude to translate its thoughts into human-readable text. …
… Developers can use claude-opus-4-7 via the Claude API . Testing Claude Opus 4.7 Claude Opus 4.7 has garnered strong feedback from our early-access testers: In early testing, we’re seeing the potential for a significant leap for our developers with Claude Opus 4.7. …
… These “primitives”—simple, foundational measures of how Claude is used, which we generate by asking Claude specific questions about anonymized Claude.ai and first-party 1P API transcripts—cover five dimensions relevant to AI’s economic impact: user and AI skills, how complex tasks are, the degree o… …