GuardAgent is a novel approach to enhancing the safety and trustworthiness of LLM-powered agents. It provides a guardrail through knowledge-enabled reasoning, showcasing strong generalization capabilities and effectiveness in moderating inputs/outputs. This paper introduces two benchmarks and demonstrates GuardAgent’s adaptability to emergent LLM agents.