Title: Cognitive Control Architecture (CCA): A Lifecycle Supervision Framework for Robustly Aligned AI Agents
Primary area: alignment, fairness, safety, privacy, and societal considerations
Keywords: Cognitive Control, Lifecycle Supervision, Injection Attacks, Adversarial Robustness, AI Safety, AI Agents

Abstract: Autonomous Large Language Model (LLM) agents exhibit significant vulnerability to Indirect Prompt Injection (IPI) attacks. These attacks hijack agent behavior by polluting external information sources, exploiting fundamental trade-offs between security and functionality in existing defense mechanisms. This leads to malicious and unauthorized tool invocations, diverting agents from their original objectives. The success of complex IPIs reveals a deeper systemic fragility: while current defenses demonstrate some effectiveness, most models are inherently fragmented. Consequently, they fail to provide full integrity assurance across the entire task execution pipeline, forcing unacceptable multi-dimensional compromises among security, functionality, and efficiency. Our method is predicated on a core insight: no matter how subtle an IPI attack, its pursuit of a malicious objective will ultimately manifest as a detectable deviation in the action trajectory, distinct from the expected legitimate plan. Based on this, we propose the Cognitive Control Architecture (CCA), a holistic framework achieving full-lifecycle cognitive supervision. CCA constructs an efficient, dual-layered defense system through two synergistic pillars: (i) proactive and preemptive control-flow integrity enforcement via a pre-generated "Intent Graph"; and (ii) an innovative "Tiered Adjudicator" that, upon deviation detection, initiates deep reasoning based on multi-dimensional scoring, specifically designed to counter complex conditional attacks. Experiments on the AgentDojo benchmark demonstrate that CCA not only effectively withstands sophisticated attacks that challenge other advanced defense methods but also achieves superior security with outstanding efficiency and enhanced robustness, thereby resolving the aforementioned multi-dimensional trade-off dilemma.

TL;DR: We introduce the Cognitive Control Architecture (CCA), a lifecycle supervision framework to defend AI agents against injection attacks.