Foundations for Investigations of Agentic AI Systems from the Forensic Analysis of OpenClaw
This study empirically investigated OpenClaw, a personal AI assistant, to create a systematic forensic approach for investigating agentic AI. Researchers analyzed its code and interaction loop using differential analysis to identify recoverable traces across five distinct planes of agent activity. This work proposes an artifact taxonomy and an open-source tool to structure the complex investigation of AI actions, highlighting the challenge of nondeterminism in LLM execution.