Yoshinari Fujinuma

This paper proposes and evaluates guardian-based defenses, both dynamic and static, to mitigate skill injection attacks targeting LLM agents that rely on reusable procedural skills.

This paper introduces and evaluates guardian-based defenses, showing that an intermediary LLM agent can significantly reduce the success rate of skill injection attacks on terminal-based agents, even when attacks are reframed.