7 Total
2 High severity
5 Medium severity
0 Low severity
Summary

This is Anthropic's system card for Claude Sonnet 4.5, a technical disclosure document describing how the model is built, evaluated, and constrained. The document states that certain behaviors are hardcoded and cannot be unlocked by operators or users, including refusal to generate content that provides serious uplift toward weapons capable of mass casualties or sexual content involving minors. The document also discloses that Claude Sonnet 4.5 has been evaluated for agentic and multi-agent task risks, and that residual safety risks remain, particularly in adversarial prompting scenarios.

Technical / Legal Breakdown

This document is the Claude Sonnet 4.5 (Claude Sonnet 5) System Card published by Anthropic, governing the design, evaluation, safety posture, and known limitations of a specific large language model release. The system card states that Claude Sonnet 4.5 is trained to balance capability and safety through a layered framework of hardcoded and softcoded behaviors, with the document asserting that certain absolute restrictions (such as refusal to assist with weapons of mass destruction or CSAM) cannot be overridden by any operator or user instruction. Notable provisions include the model's agentic use guidelines, which establish that Claude is designed to apply particular caution in multi-step autonomous tasks where actions may be difficult to reverse, and the document discloses evaluations for catastrophic risk categories including CBRN uplift and cyberweapon development. The document engages with the EU AI Act's high-risk and general-purpose AI provider requirements, the FTC's AI accountability guidance, and emerging frameworks for frontier AI safety governance, with applicability of specific compliance obligations depending on deployment jurisdiction, operator classification, and use-case context. Material compliance considerations include third-party operator reliance on Anthropic's usage policies, the allocation of safety responsibility between Anthropic and API operators, and the model's disclosed residual risks in jailbreak resistance and agentic task execution.

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High — 2 provisions
Medium — 5 provisions

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Mapped Governance Frameworks

CFAA
United States Federal
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DMCA
United States Federal
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DSA
European Union
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Trump Executive Order on AI Policy Framework
US
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Archival ProvenanceSource & Archival Record
Last Captured July 7, 2026 00:08 UTC
Capture Method Automated scheduled archival capture
Document ID CA-D-000921
Version ID CA-V-004536
SHA-256 6efa3d43fd9618f4be7f7cfe46cd7f4c7cef6da893a9190dc03eda21aa21ce21
✓ Snapshot stored ✓ Text extracted ✓ Change verified ✓ Hash verified

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