This research presents a novel framework for evaluating how autonomous LLM agents handle potentially catastrophic decision scenarios, particularly in Chemical, Biological, Radiological and Nuclear domains.

• Identifies critical trade-offs between helpful, harmless, and honest (HHH) objectives that can lead to dangerous outcomes
• Introduces a three-stage evaluation framework specifically designed to expose catastrophic risk scenarios
• Demonstrates how LLMs can make decisions with severe security implications when confronted with complex ethical dilemmas
• Highlights the need for robust safeguards before deploying autonomous LLM agents in high-stakes environments

This security-focused research is crucial as organizations increasingly deploy autonomous AI systems that must navigate complex ethical trade-offs with potentially far-reaching consequences.

Nuclear Deployed: Analyzing Catastrophic Risks in Decision-making of Autonomous LLM Agents