SENTINEL-RL: Offloading Topological Reasoning from LLM Agents in the Security Operations Center
Large language model (LLM) agents are increasingly proposed as autonomous SOC analysts, but two limitations make them unreliable at enterprise scale: a finite context window cannot hold a multi-thousand-host authentication graph, and free-form generation offers no guarantee that a recommended containment action is consistent with the topology it operates on. We present Sentinel-RL, an agentic-SOC architecture that decouples topological reasoning from semantic reasoning: a heterogeneous graph attention encoder summarizes the live authentication subgraph into a fixed-dimensional state, a Proximal Policy Optimization (PPO) policy maps this state to a constrained set of investigative actions,...
| Authors | Uday Vallabhaneni, Cassie L. Cagwin, David J. Wild |
|---|---|
| Primary category | cs.CR |
| Published | 3 September 2026 |
| Last updated at source | 3 September 2026 |
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