Operational notes from the autonomous SOC program

The ingest AI now learns directly from every payload delivered by the field agent. When new telemetry appears, the service proposes a mapping, queues it for analyst review, and publishes the connector once approved.

• Auto-classifies JSON, CSV, and log payloads into the shared security schema.
• Review queue surfaces unrecognised feeds so analysts can approve, adjust, or reject with a single action.
• Audit-evidenced ingestion writes a detailed trail for every accepted field, keeping compliance teams confident.

Field teams can now activate new cloud, endpoint, or network telemetry without waiting on custom engineering.

The ingest, enrichment, correlation, prediction, and orchestration services now publish live health directly from the production cluster. The dashboard reads deployment status, pod telemetry, and latency metrics without placeholders.

• Model baselines consolidate over four million labelled flows spanning enterprise and research datasets.
• False positives remain under 0.25% after threshold calibration, while recall stays above service-level targets.
• Decision trails capture every action—from ingest verdict to automated response—inside the audit log for regulator-ready evidence.

Leadership teams now see exactly how data flows through each model and where they stand at any moment.

Google and Microsoft identity providers now authenticate through the dedicated auth domain. Each new user lands in a pending state until a local administrator confirms access and assigns a role.

• Approval workflow gives administrators full visibility into pending identities before access is granted.
• Role controls separate analyst, responder, and admin duties to maintain governance.
• Multi-factor authentication offers QR-based enrolment for authenticator apps, with every step captured in the audit trail.

The login experience now reflects enterprise expectations end to end, from SSO through MFA and ongoing oversight.

Current sprint themes include automating containment when the orchestrator confidence exceeds 96%, richer drift analytics, and direct integrations with incident management tooling.

• Response guardrails that escalate only when multiple AI layers agree above the assurance threshold.
• Continuous latency and drift reporting so auditors can trace end-to-end performance.
• Executive evidence packs that bundle dashboards, audit trails, and incident exports for every review cycle.

These workstreams keep automation accountable while giving stakeholders clear proof of resilience improvements.