GuardianAgentBench: Where Agents Fail and How to Guard Them

Researchers have introduced GuardianAgentBench, a new benchmark featuring 580 scenarios designed to evaluate the safety and reliability of autonomous large language model agents. The project aims to identify specific operational failures when agents interact with external tools and environments, providing a standardized framework to improve how these systems are guarded against errors and security risks.