This blog was published by Jonathan Ng, Andrey Anurin, Connor Axiotes, Esben Kran.

Apart Research's newest paper, Catastrophic Cyber Capabilities Benchmark (3cb): Robustly Evaluating LLM Agent Cyber Offense Capabilities (website), creates a novel cyber offense capability benchmark that engages with issues of legibility, coverage, and generalization in cyber offense benchmarks.

We were moved to create 3cb because a superintelligent AI performing autonomous cyber operations would prove a large risk for humanity. This means robust cyber offense evaluations will be more important than ever for policymakers and AI developers.

3cb uses a new type of cyber offense task categorization and adheres to the principle of demonstrations-as-evaluations to improve legibility and coverage. It also introduces 15 original challenges that are not memorized, differentiating it from other benchmarks that use existing CTF competitions or pull requests to evaluate models.

Agents and Cyber Capabilities

LLM agents have the potential to revolutionize defensive cyber operations, but their offensive capabilities are not yet fully understood. To prepare for emerging threats, model developers and governments are evaluating the cyber capabilities of foundation models. However, these assessments often lack transparency and a comprehensive focus on offensive capabilities.

In response, we introduce the Catastrophic Cyber Capabilities Benchmark (3CB), a novel framework designed
to rigorously assess the real-world offensive capabilities of LLM agents. Our evaluation of modern LLMs on 3CB reveals that frontier models, such as GPT-4o and Claude 3.5 Sonnet, can perform offensive tasks such as reconnaissance and exploitation across domains ranging from binary analysis to web technologies.

Conversely, smaller open-source models exhibit limited offensive capabilities. Our software solution and the corresponding benchmark provides a critical tool to reduce the gap between rapidly improving capabilities and robustness of cyber offense evaluations, aiding in the safer deployment and regulation of these powerful
technologies.

Why 3cb?

Autonomous cyber offense operations are a key risk factor of competent general intelligence. As a result, trustworthy cyber offense evaluations are important to support policymakers and lab governance measures, leading to a reduction in AI risk.

From conversations with academics, ...

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