Sentinel Ops — A SOC
That Triages Itself.
An AI-powered Security Operations Centre platform for enterprise IT. Ingests millions of events per second, correlates them against the MITRE ATT&CK matrix, auto-remediates known patterns, and surfaces only the alerts that need a human. Built for analysts who are tired of drowning.
Why this project existed.
The problem
Modern SOCs ingest 80,000+ events per second across multiple clusters. Analysts see 1,200 alerts a day and can investigate maybe 60. The other 1,140 are noise — but the breach is always somewhere in that pile. Tooling that promised AI triage has historically just added another queue to clear.
The solution
Real-time event ingest with deterministic dedupe and AI-assisted clustering. Each candidate incident is scored against MITRE ATT&CK, attached to its runbook, and auto-remediated when confidence is high. Analysts see a ranked priority queue, a live threat-surface map, and audit-ready runbooks attached to every action.
Built on a deliberate stack.
Every choice in this project was made for two horizons — fast iteration during build, and a 3-5 year operational life with minimal vendor lock-in.
Three views of the system.
Live threat-surface map, MITRE ATT&CK coverage (172/183), mean time to detect, and a priority alert feed ranked by confidence × blast radius.
Per-incident timeline with attached runbook, AI-generated narrative summary, related events, and one-click containment actions audited end-to-end.
Cluster, region, and host-level health view. Detector coverage per asset, ingest lag, and false-positive trend per detection rule.
What changed for the team.
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