Researchers introduced a new framework for detecting zero-day jamming attacks, which combines graph attention networks and Dirichlet process clustering. They also proposed an inference-driven reinforcement learning-based jammer that can evade detection. These advancements are relevant to the AI agent security landscape, particularly in the context of Model Context Protocol (MCP) security.