AI SOC Analyst (Security Operations Center Simulator)
A simulated Security Operations Center where autonomous agents ingest server, authentication, and firewall logs to classify incidents and compile root-cause timelines.
The Problem
What difficult challenge is this experiment tackling?Human SOC analysts suffer from severe alert fatigue, triaging thousands of daily low-priority firewall log events while sophisticated slow-and-low cyber attacks slip through.
The Hypothesis
What do I believe autonomous AI & engineering can accomplish?Specialized security agents can correlate events across Apache access logs, SSH auth logs, and fail2ban streams to reconstruct complete intrusion kill chains automatically.
System Architecture & Workflow
End-to-end design, data pipelines, and component interactionBenchmark & Empirical Metrics
Accuracy • Latency • Cost • Token Usage • Human InterventionTriages 10,000 synthetic log records in under 30 seconds; successfully reconstructs simulated brute-force and SQLi attack chains with 0 missed steps.
Security, Privacy & Ethical Guardrails
Risk mitigation, strict boundaries, and sandbox controlsStrictly runs on synthetic honeypot or anonymized test server logs; zero operational exposure.
Lessons Learned & Observations
Empirical findings from prototyping and testingCorrelating timestamps between SSH brute-force attempts and suspicious web requests instantly exposes multi-vector attacks.
Next Experiment Iteration
Upcoming modifications, scaling factors, or new hypothesesAuto-generate fail2ban and Cloudflare firewall rule blocks in response to detected threats.