AgentWall: A Runtime Safety Layer for Local AI Agents

This paper introduces AgentWall, a runtime safety and observability layer for local AI agents, addressing the critical problem of ensuring their safety. It intercepts proposed agent actions before they execute on the host environment, tackling a gap not covered by traditional model alignment or input filtering approaches.