BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense

• URL: http://arxiv.org/abs/2609.11852v1
• Date: Thu, 10 Sep 2026 17:36:18 GMT
• Title: BlueSTAR: Tiered Agentic Architecture for Autonomous Cyber Defense
• Abstract summary: Large language models (LLMs) offer a promising foundation for autonomous cyber defense.<n>We present BlueSTAR, a tiered agentic architecture for autonomous cyber defense in enterprise IT/OT networks.<n>We evaluate BlueSTAR on two live enterprise IT/OT cyber ranges using seven attack chains based on real-world intrusion techniques.
• Score: 8.077485614476132
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Cyber attacks are increasingly automated, narrowing the time available for human analysts to detect, reason about, and respond to intrusions. Large language models (LLMs) offer a promising foundation for autonomous cyber defense because they can correlate heterogeneous evidence and reason about previously unseen threats. However, directly applying LLMs to operational security telemetry is impractical: raw logs arrive faster than current models can process them, individual events are often ambiguous, and unconstrained LLM actions can introduce significant operational risk. We present BlueSTAR, a tiered agentic architecture for autonomous cyber defense in enterprise IT/OT networks. BlueSTAR first transforms high-volume security telemetry into compact indicators of compromise. We further introduce a resilience metric that jointly captures attacker reach, impact on mission-critical assets, and disruption caused by defensive actions. We evaluate BlueSTAR on two live enterprise IT/OT cyber ranges using seven attack chains based on real-world intrusion techniques. Across attack chains, BlueSTAR retains the fast containment of deterministic response for known threats while successfully defending against attacks requiring contextual and cross-cycle reasoning, including credential theft, repeated compromise, concurrent attackers, and attacks against physical processes.

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