The document introduces a mapping of Security Level recommendations to each Critical Capability Level, identifying minimum appropriate security mitigations for models at each CCL. The framework states these recommendations represent the minimum the field of frontier AI should apply, and that DeepMind's actual practices may exceed these baseline levels.
This analysis describes what Google DeepMind's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
This provision establishes the operational taxonomy that governs how DeepMind identifies and responds to capability thresholds in its models, and asserts that the recommended security levels represent a field-wide minimum rather than only a company-internal standard. The framing as a field-wide recommendation is notable given this is a voluntary corporate document without binding authority over other organizations.
Interpretive note: The specific CCL definitions and Security Level mappings are contained in the referenced technical report rather than this public document, limiting independent assessment of the classification criteria from this text alone.
This provision governs the internal classification system DeepMind applies to determine which of its AI models require heightened security and mitigation measures, which in turn affects which models are available for deployment and under what conditions. The document does not specify how CCL classifications are disclosed to users or enterprise customers.
Cross-platform context
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Compare across platforms →"Our initial Framework recognised the need for a tiered approach to security, allowing for the implementation of mitigations with varying strengths to be tailored to the risk. This proportionate approach also ensures we get the balance right between mitigating risks and fostering access and innovation. Since then, we have drawn on wider research to evolve these security mitigation levels and recommend a level for each of our CCLs.* These recommendations reflect our assessment of the minimum appropriate level of security the field of frontier AI should apply to such models at a CCL.Excerpt from Google DeepMind's Frontier Safety Framework
(1) REGULATORY LANDSCAPE: The CCL framework and associated security recommendations engage the EU AI Act's classification system for high-risk AI and systemic risk categories for general-purpose AI models, as well as export control frameworks that …
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This provision establishes the operational taxonomy that governs how DeepMind identifies and responds to capability thresholds in its models, and asserts that the recommended security levels represent a field-wide minimum rather than only a company-internal standard. The framing as a field-wide recommendation is notable given this is a voluntary corporate document without binding authority over other organizations.
This provision governs the internal classification system DeepMind applies to determine which of its AI models require heightened security and mitigation measures, which in turn affects which models are available for deployment and under what conditions. The document does not specify how CCL classifications are disclosed to users or enterprise customers.
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