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Paul Marinos
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SOAR & Automation

Automating enrichment and triage safely, guardrails for automated containment, and where the human approval gate belongs when the action is irreversible.

SOAR programmes fail in a recognisable way: a platform is bought, a containment playbook is built for the impressive demo, it isolates a production host during a false positive, and automation is never trusted again.

The failure is one of sequencing. Automation should start where mistakes are cheap and move toward expensive actions only as the underlying detections earn it.

Candidate Reversible? Verdict
Enrichment — asset, identity, geo, intel lookups Yes, no side effects Automate first, always
Correlation and grouping of related alerts Yes Automate early; large analyst-time win
Notification and ticket creation Mostly Automate, with dedupe or it becomes noise
Evidence collection — snapshot, memory capture Yes, additive Automate; it preserves what disappears
Triage decisions — close as benign Recoverable but risky Only with measured precision
Containment — disable account, isolate host, block Disruptive Gate on approval, scope tightly
Destructive — terminate, delete, revoke broadly No Human approval, always

Enrichment is the highest-value automation in security operations and the least glamorous. It is pure analyst time returned with no downside — every alert arriving pre-enriched saves minutes of identical lookups, consistently, forever.

The tempting one, and the one that needs the most evidence. Closing alerts automatically is reasonable only when the rule’s precision is measured and the closure condition is specific.

Two safeguards make it survivable: sample the auto-closed alerts and review them, so the automation itself is monitored; and never auto-close on the absence of evidence, only on its presence. “No enrichment returned anything” is not benign — it is unknown.

If a rule needs auto-closing to be workable, that is a tuning problem wearing a costume. Fix the rule.

Containment automation is defensible with real constraints:

  • Scope limits. Never isolate more than N hosts, or disable more than N accounts, without a human. A runaway playbook can do more damage in ninety seconds than the intrusion.
  • Asset criticality checks. Auto-isolate a developer laptop; never auto-isolate a domain controller or production database. This requires the asset context that the pipeline should be adding at ingest.
  • Time-of-day awareness. Automation that fires at 3am with nobody watching should be more conservative, not less.
  • Reversibility by design. Every containment action needs a documented, tested undo. An isolation you cannot reverse quickly is an outage.
  • Circuit breakers. If a playbook triggers unusually often, stop it and page a human. The most likely cause is a broken detection, not an outbreak.
  • Full audit trail. Every automated action logged with the triggering alert and the decision path — for incident reconstruction and for the postmortem when automation gets it wrong.

Identity actions deserve special mention. Revoking sessions and disabling an account are among the fastest and most effective containment moves available, and they are also how you lock out an executive mid-board-meeting on a false positive. Scope by account type, and prefer session revocation — which forces re-authentication — over disabling, which is blunter and more disruptive.

Not on everything: an approval step on enrichment is friction with no benefit, and universal gating trains people to approve without reading.

Gate where the action is disruptive and hard to reverse, and design the gate so the approver can actually decide — the alert, the enrichment, the proposed action, the blast radius, and the undo, in one screen. An approval prompt that shows only “Isolate host SRV-041? [Y/N]” gets rubber-stamped, which is worse than no gate because it launders the decision.

LLM-based triage is genuinely promising for the judgement-heavy, high-volume work that deterministic automation handles badly — summarising an alert with its context, drafting a first-pass assessment, proposing next investigative steps.

The constraints from AI & Automation apply directly, and two matter most here. Grounding: an assessment that cites the specific evidence is checkable; one that reads plausibly is not. And authorization: an agent with tools is a principal with permissions, so its blast radius is a scoping decision, not a prompt-engineering one.

The safe shape today is agent proposes, human disposes for anything consequential, with the agent’s reasoning visible rather than summarised. A confident wrong triage decision is more expensive than no triage, because it carries the authority of having been checked.

Automation quality is bounded by detection quality — automating on top of imprecise rules multiplies the error rather than absorbing it. Containment overlaps directly with incident response, where the same actions are taken manually under judgement. And the agent-assisted layer is AI engineering pointed at the SOC queue.

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