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Insider Risk Baseline

  • 55 installs
  • 165 repo stars
  • Updated June 18, 2026
  • vinayaklatthe/microsoft-security-skills

Helps with ai & agent building tasks.

About

insider-risk-baseline is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • insider-risk-baseline
  • AI & Agent Building
  • AI-coding skill

Insider Risk Baseline by the numbers

  • 55 all-time installs (skills.sh)
  • +1 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #6,846 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
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Installs55
repo stars165
Last updatedJune 18, 2026
Repositoryvinayaklatthe/microsoft-security-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Microsoft Purview Insider Risk Management (Baseline)

Insider Risk Management (IRM) uses signals across Microsoft 365 and connected sources to detect, investigate, and act on risky insider activity - data theft, leaks, and policy violations - with privacy-by-design controls (pseudonymisation, RBAC, separation of duties).

When to use

Standing up an insider-risk program: departing-employee data theft, sensitive-data leaks, and security-policy violations - with legal/HR/privacy sponsorship in place.

Do not use this skill for risk-adaptive DLP design after IRM is running (use purview-advanced-dlp) or for general communication compliance (use purview-communication-compliance if available).

Pick the right starting policy template

ConcernTemplate
Employees leaving with dataData theft by departing users (needs HR connector for resignation/termination)
Sensitive-content leaks to unauthorised recipientsData leaks (general / by priority users / by disgruntled users)
Security-policy violations (malware, AV disable, etc.)Security policy violations
Risky AI usageRisky AI usage (preview/GA as available)
Patient data / healthcare scenariosPatient data leaks (sector-specific)

Rule of thumb: pick one template per quarter, tune it to acceptable signal-to-noise, then add the next. Multiple templates active simultaneously without tuning swamps reviewers.

Approach

1. Engage stakeholders - Bring legal, HR, privacy, and (where applicable) works councils to the design table; document the lawful basis for monitoring. Verify: signed-off scope document specifying data sources, retention, reviewer roles. 2. Configure prerequisites - Set IRM settings, enable required indicators (Office, device, physical badging via connectors), and connect HR data via the Microsoft 365 HR connector for events like resignation/termination. Verify: HR connector status is healthy and a test resignation event appears within 24 hours. 3. Choose policy templates - Start with templates: data theft by departing users, data leaks, security policy violations, and risky AI usage; configure scope. Verify: policy is in place with a defined user scope (pilot first) and indicator set. 4. Privacy by design - Enable pseudonymisation of usernames, scope analyst/reviewer roles tightly (RBAC, separation of duties), and configure anonymisation per legal/works-council needs. Verify: reviewers see pseudonymised identifiers by default; un-anonymise requires elevated role. 5. Triage & investigate - Review alerts, build cases, examine the user activity timeline, and escalate (e.g., to eDiscovery / HR) per the documented workflow. Verify: case management workflow exists with stages, owners, SLAs. 6. Tune indicators and thresholds - Adjust thresholds to acceptable signal-to-noise; document tuning decisions for audit. Verify: alert volume per reviewer per week within the agreed range. 7. Adaptive Protection - Feed IRM risk levels into Adaptive Protection so DLP/Conditional Access tighten dynamically for elevated-risk users. Verify: an elevated-risk test user triggers the stricter DLP branch.

Guardrails

  • Engage legal/HR/privacy stakeholders before deployment; insider risk monitoring is sensitive

and getting governance wrong damages employee trust and creates legal risk.

  • Use pseudonymisation and least-privilege reviewers by default; separate IRM analyst from

investigator roles.

  • Tune indicator thresholds to avoid alert overload; start with a focused scope (one BU or

priority-user group) before tenant-wide.

  • HR connector is mandatory for departing-user detection - resignation/termination events drive

the highest-confidence signal; without it the template is half-blind.

  • Document retention for IRM signals/cases per legal/regulatory requirements; do not retain

longer than justified.

Common anti-patterns

  • Switching on every template tenant-wide on day one - reviewer fatigue within a week.
  • No HR connector - departing-user template fires on weak signal and misses real cases.
  • Pseudonymisation off because "we trust our analysts" - works council and legal disagree later.
  • Single role group with full IRM permissions - no separation of duties.
  • No defined escalation path to HR/legal - cases die in the queue.

Example prompts

  • Stand up an Insider Risk Management policy for departing-employee data theft.
  • How do I configure pseudonymisation and least-privilege reviewers in IRM?
  • Connect HR data so resignation/termination events trigger IRM signals.
  • Feed IRM risk levels into Adaptive Protection.
  • Tune IRM indicator thresholds to reduce alert overload.

Microsoft Learn

  • IRM overview: https://learn.microsoft.com/purview/insider-risk-management
  • Plan & configure IRM: https://learn.microsoft.com/purview/insider-risk-management-configure
  • Policy templates: https://learn.microsoft.com/purview/insider-risk-management-policies
  • Adaptive Protection: https://learn.microsoft.com/purview/insider-risk-management-adaptive-protection
  • HR connector: https://learn.microsoft.com/purview/import-hr-data
  • Permissions & role groups: https://learn.microsoft.com/purview/insider-risk-management-permissions

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