This paper introduces the Hierarchical Autonomy Evolution (HAE) framework, a novel approach to categorizing security vulnerabilities in AI agents as they evolve from cognitive entities to collective societies. It details a taxonomy of threats across three levels of autonomy, highlighting critical research gaps and guiding the development of robust, multilayered defense architectures for trustworthy AI agent systems.