Framework for Mitigating Risks of Large Language Models Using Process Analysis and Systems Theory

The integration of Large Language Models (LLMs) into critical applications raises concerns about security and operational reliability. A systematic approach to assessing AI system risks is proposed using process analysis and Systems-Theoretic Process Analysis (STPA). The framework aims to mitigate risks associated with LLMs without specifying technical details, numbers, or timelines. No specific vulnerabilities, CVE IDs, or quantified impacts are mentioned in the provided content. The focus is on theoretical methodologies for risk evaluation rather than concrete incidents or threats.