Security Automation and Orchestration

The automation judgment framework

Every automation decision in this course runs through three questions — the same framework used in production SOC operations:

1. Can this be automated safely? Does the action require human judgment? What is the blast radius if the automation is wrong? Enriching an alert with IP reputation has zero blast radius — automate it. Disabling a CEO's account at 02:00 has massive blast radius — add an approval gate.

2. Should this be automated? What is the cost of manual execution vs the risk of automated execution? If an analyst spends 10 minutes enriching every AiTM alert with the same 5 queries, that is 10 minutes that automation handles in 30 seconds with zero risk.

3. What is the confidence threshold? When the detection is 99% accurate, auto-contain. When it is 80% accurate, auto-enrich and notify. When it is 60% accurate, do nothing automatically. The learner builds the metrics to set these thresholds for their environment.

Who this course is for

SOC analysts who triage the same alerts manually every day. You run the same 5 KQL queries on every AiTM alert. You copy the same enrichment data into the same incident comment. You send the same Teams message to the same channel. This course automates all of it.

Detection engineers whose rules have no automated response. You built 50 detection rules. They fire alerts. An analyst triages them. But the rule for "AiTM with high confidence" could auto-revoke the session and collect evidence before the analyst even opens Sentinel. This course connects your rules to automated action.

SOC managers who need to scale without hiring. Your team handles 500 alerts per day. You cannot justify another headcount. But you can justify automation that reduces MTTA from 45 minutes to 5 minutes and auto-resolves 60% of Tier 1 alerts.

IR practitioners who want evidence waiting when they arrive. By the time you pick up the AiTM incident, the session token has expired, the sign-in logs have rolled, and the volatile evidence is gone. This course builds the auto-collection that captures evidence at alert time — not investigation time.

What you build

Enrichment pipeline: Multi-source alert enrichment — IP reputation, user risk, device compliance, TI correlation, alert history — assembled automatically and attached to every incident in under 30 seconds.

Evidence auto-collection: Playbooks that capture SigninLogs, AuditLogs, mailbox audit, endpoint processes, and network logs the moment an incident is created — before evidence decays.

Notification and escalation: Teams adaptive cards, email notifications, MSSP coordination, on-call escalation with timeouts, and human approval workflows for high-impact actions.

Auto-containment: Identity containment (session revoke + MFA reset + CA emergency policy + OAuth revocation), endpoint containment (isolation + evidence collection), and synchronized cross-environment containment for multi-stage attacks.

The complete automation program: Testing framework, version control, governance, metrics dashboard, and a 90-day automation roadmap.

Where it connects

From Detection Engineering: You built the rules. This course makes them auto-respond. Every analytics rule becomes an automation trigger with the appropriate tier of response.

From Incident Triage: You learned the triage methodology. This course automates the repeatable parts — the 5-query cloud triage pack runs automatically, evidence is pre-collected, and the analyst starts with a fully enriched incident instead of a raw alert.

From SOC Operations: You defined the operational processes. This course executes them automatically — notification matrices become automated routing, playbooks become Logic Apps, and escalation procedures become timed workflows.

From Mastering KQL: KQL powers every automation trigger. The analytic rules you write determine what gets automated and at what confidence level. KQL accuracy directly controls automation safety.

Prerequisites

Required:

Mastering KQL (K0-K3 minimum) — KQL powers every automation trigger in this course. You need to read, write, and debug KQL queries confidently.

Familiarity with Microsoft Sentinel — incident queue, analytics rules, data connectors. From SOC Operations, M365 Security Ops, or Detection Engineering.

Recommended:

Detection Engineering — understanding analytics rules that feed automation. Incident Triage — understanding the triage workflow being automated. Entra ID Security — understanding identity controls used in containment automation.

Usage rights and disclaimer

Course materials: Licensed for individual professional development. You may deploy playbooks, automation rules, KQL queries, and Azure Functions from this course in your organization's production environment. You may not redistribute course content, share account credentials, or republish course materials.

Automation artifacts: All playbooks and functions are provided as-is. Test every automation against your environment in a staging workspace before production deployment. Automated containment actions have business impact — verify blast radius before enabling. Ridgeline Cyber Defence is not responsible for operational impact from deployed automation.

Fictional environment: All scenarios use the fictional Northgate Engineering environment. IP addresses use RFC 5737 documentation ranges.