The Ethics of Autonomous AI Agents for Offensive Security
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TL;DR - This paper examines the ethics of autonomous LLM agents used for offensive security. It argues that their unpredictable behavior, open-ended impact, and low skill barrier could industrialize cyber offense and diffuse responsibility across users, developers, and third parties.
- Identifies three independent forms of indeterminacy: agent actions, real-world impact, and user population.
- Argues that opaque models and LLM supply chains hinder safety review, explanation, and incident attribution.
- Predicts a short-term advantage for attackers due to offense-defense cost asymmetry, despite possible long-term defensive benefits.
- Finds existing dual-use and AI-ethics frameworks inadequate and proposes stakeholder-specific recommendations.
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The Ethics of Autonomous AI Agents for Offensive Security
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Semantic Scholar citations 1 · Semantic Scholar influential citations 0
TL;DR - This paper examines the ethics of autonomous LLM agents used for offensive security. It argues that their unpredictable behavior, open-ended impact, and low skill barrier could industrialize cyber offense and diffuse responsibility across users, developers, and third parties.
- Identifies three independent forms of indeterminacy: agent actions, real-world impact, and user population.
- Argues that opaque models and LLM supply chains hinder safety review, explanation, and incident attribution.
- Predicts a short-term advantage for attackers due to offense-defense cost asymmetry, despite possible long-term defensive benefits.
- Finds existing dual-use and AI-ethics frameworks inadequate and proposes stakeholder-specific recommendations.