关键词: 智能体；人工智能安全；安全治理；自主决策闭环；分级行为干预；全生命周期管理

Abstract: Agents are moving from proof of concept to large-scale deployment. However, their autonomous execution can easily lead to behavioral runaway, algorithmic black boxes make decision processes difficult to trace, and cross-domain collaboration blurs accountability boundaries. Accordingly, this paper constructs a “five objectives–four phases–nine measures” security governance framework, which takes trusted identity, controllable authorization, auditable process, traceable accountability and manageable scenario as the objectives, risk observation, runtime management, behavior intervention and capability improvement as the closed-loop phases, and nine capabilities including interaction detection and context protection as the measures. An L1~L5 graded behavior intervention mechanism is further proposed, providing a reusable governance paradigm for full lifecycle security management of enterprise agents.

Key words: agent; artificial intelligence security; security governance; autonomous decision-making loop; graded behavior intervention; full lifecycle management