Security operations face a structural crisis. On one side, you have deterministic workflows: SIEM rules and SOAR playbooks, that are safe but brittle, expensive to maintain, and incapable of nuanced reasoning. Conversely, you have unbounded AI, which promises speed but introduces unacceptable risks like opacity, hallucinations, and new attack surfaces. Neither path is sufficient alone. This technical whitepaper presents a reference architecture for the Policy-Governed Autonomous SOC, detailing how to build a system where AI handles investigation and reasoning, while deterministic policies strictly control execution.
What You’ll Learn:
- The Architecture of Control: How to separate the intelligence plane (AI/LLM) from the control plane (policy) to prevent AI from going rogue.
- The Policy-Wrapped Agent Design Pattern: How to enumerate allowed actions for AI agents and attach explicit policies to each, ensuring high-risk actions (like server isolation) always require human approval.
- AI for Semantic Glue Work: Strategies for using LLMs to handle correlation and narrative generation, stitching together views across fragmented tools.
- Risk-Tiered Automation: A framework for organizing automation into three tiers, from fully autonomous L1 tasks to human-approved high-impact decisions.
- The Deployment Roadmap: A pragmatic 5-step roadmap to moving from manual triage to a self-healing SOC.
