| name | mitre-coverage-report |
| description | MITRE ATT&CK Coverage Report — YAML-driven PowerShell pipeline gathers analytic rule MITRE tags, custom detection techniques, SOC Optimization recommendations, and alert/incident operational data via az rest/az monitor/Graph API, writes a deterministic scratchpad, LLM renders the report. Covers tactic-level coverage matrix, technique-level drill-down with rule mapping, coverage gap identification, SOC Optimization threat scenario alignment, untagged rule remediation, ICS/OT technique tracking, and MITRE Coverage Score (5 weighted dimensions). Inline chat and markdown file output. |
| threat_pulse_domains | ["incidents"] |
| drill_down_prompt | Run MITRE ATT&CK coverage report — tactic/technique coverage, gaps, SOC optimization |
MITRE ATT&CK Coverage Report — Instructions
Purpose
This skill generates a comprehensive MITRE ATT&CK Coverage Report analyzing detection coverage across the ATT&CK Enterprise framework. It inventories all analytic rules and custom detections, maps them to MITRE tactics and techniques, identifies coverage gaps, and provides prioritized recommendations for improving detection posture.
Entity Type: Sentinel workspace (from config.json)
| Scope | Data Sources | Use Case |
|---|
| Workspace-wide (default) | Analytic Rules (REST), Custom Detections (Graph), SOC Optimization (REST), SecurityAlert/SecurityIncident (KQL) | Full MITRE coverage analysis |
| Operational correlation | SecurityAlert, SecurityIncident | Which MITRE-tagged rules actually produce alerts and incidents |
What this report covers: Tactic-level coverage matrix with per-tactic technique counts and percentages, technique-level drill-down with rule-to-technique mapping, coverage gap identification against the full ATT&CK Enterprise framework, SOC Optimization threat scenario alignment (AiTM, ransomware, BEC, etc.), untagged rule remediation with AI-suggested MITRE tags, ICS/OT technique tracking, operational MITRE correlation (which rules actually fire), and a composite MITRE Coverage Score.
Complementary to: This skill pairs with the sentinel-ingestion-report skill — ingestion report covers data volume, tier optimization, and cost; MITRE coverage report covers detection posture against the ATT&CK framework. Run both for a complete workspace assessment.
Architecture
┌──────────────────────────────────────────────────────────────────┐
│ YAML query files PowerShell script LLM render │
│ queries/phase1-3/ ──→ Invoke-MitreScan.ps1 ──→ Phase 4 │
│ (6 .yaml files) (~1030 lines) (SKILL- │
│ • az rest (Sentinel API) report.md) │
│ • Invoke-MgGraphRequest │
│ • az monitor (KQL) │
│ • mitre-attck-enterprise.json │
│ • m365-platform-coverage.json (CTID) │
│ ↓ │
│ temp/mitre_scratch_<ts>.md │
│ (~35 KB, 18+ sections) │
└──────────────────────────────────────────────────────────────────┘
Execution model:
- Phases 1-3 (data gathering): Fully automated by
Invoke-MitreScan.ps1. Phase 1 uses az rest (Sentinel REST API) and optionally Invoke-MgGraphRequest (Graph API). Phase 2 uses az rest (SOC Optimization API). Phase 3 uses az monitor log-analytics query (KQL).
- Phase 4 (rendering): LLM reads the scratchpad +
SKILL-report.md and renders the report. This is the only phase requiring LLM involvement.
Static reference: mitre-attck-enterprise.json contains ATT&CK Enterprise v16.1 with 14 tactics, 216 techniques, and 475 sub-techniques. The PS1 loads this at startup to compute coverage gaps against the full framework. This file is version-controlled and should be updated when MITRE publishes new ATT&CK releases.
Platform coverage reference: m365-platform-coverage.json is a compact CTID (Center for Threat-Informed Defense) mapping of M365 Defender product capabilities to ATT&CK techniques. Contains detect/protect/respond coverage for 81 detect techniques across 38 capabilities (7 SecurityAlert product groups). Used for the 3-tier platform coverage classification:
- Tier 1 (Alert-Proven): SecurityAlert from M6 query has MITRE technique attribution — highest confidence
- Tier 2 (Deployed Capability): Product is active (has alerts) and CTID claims detect coverage for the technique — medium confidence
- Tier 3 (Catalog Capability): CTID maps coverage but no alert evidence for the product in this workspace — lowest confidence
To rebuild from upstream: download the CTID M365 mapping JSON, transform with PowerShell (group by parent technique, map capabilities to SecurityAlert ProductName). See temp/ctid_raw.json for the raw source.
Companion Files — When to Load
| File | Purpose | When to Load |
|---|
| SKILL.md (this file) | Architecture, workflow, rendering rules, score methodology, domain reference | Always — primary entry point |
| SKILL-report.md | Report templates (§1-§6), section-to-scratchpad mapping, formatting rules | Phase 4 rendering only |
| Invoke-MitreScan.ps1 | PowerShell data-gathering pipeline (Phases 1-3) | Execution only — no need to read unless debugging |
| mitre-attck-enterprise.json | ATT&CK Enterprise v16.1 static reference | Referenced by PS1 at runtime — no manual loading |
| m365-platform-coverage.json | CTID M365 platform coverage reference (detect/protect/respond) | Referenced by PS1 at runtime — no manual loading |
📑 TABLE OF CONTENTS
- Quick Start - 3-step execution pattern
- Critical Workflow Rules - Prerequisites and prohibitions
- Execution Workflow - Phases 0-4
- Query File Reference - All 5 YAML files
- Output Modes - Inline chat vs. Markdown file
- Deterministic Rendering Rules - Rules A-D (mandatory for Phase 4)
- MITRE Coverage Score - 5-dimension scoring methodology
- Domain Reference - ATT&CK interpretation, tactic priorities, Sentinel-specific mappings
- SVG Dashboard Generation - Visual dashboard from completed report
Quick Start (TL;DR)
3-step execution pattern:
Step 1: Run Invoke-MitreScan.ps1 (Phases 1-3 — data gathering)
Step 2: Read scratchpad + SKILL-report.md (Phase 4 prep)
Step 3: Render report incrementally (§1 via create_file, then §2–§6 appended via replace_string_in_file)
Step 1: Run Data Gathering
# From workspace root — run all phases (default: 30 days alert/incident lookback):
& ".github/skills/mitre-coverage-report/Invoke-MitreScan.ps1"
# Specify a custom alert/incident lookback:
& ".github/skills/mitre-coverage-report/Invoke-MitreScan.ps1" -Days 7
# Run a specific phase (for re-runs / debugging):
& ".github/skills/mitre-coverage-report/Invoke-MitreScan.ps1" -Phase 1
Output: Scratchpad file at temp/mitre_scratch_<timestamp>.md (~28 KB, 12 sections).
Timing: Full run takes ~60-90 seconds (varying with REST API response times and KQL auth state).
Step 2: Load Rendering Context
- Read the scratchpad file (path printed by PS1 at completion)
- Read SKILL-report.md for rendering templates
Step 3: Render Report (Incremental Writes)
Render the report across multiple tool calls — one section per call — to avoid single-call output token limits that truncate large reports:
create_file → header + disclaimer + §1 (Executive Summary, Score, Inventory, Top 3 Recs)replace_string_in_file → append §2 (Tactic Coverage Matrix)replace_string_in_file → append §3 (Technique Deep Dive — largest section)replace_string_in_file → append §4 (Coverage Gap Analysis)replace_string_in_file → append §5 (Operational MITRE Correlation)replace_string_in_file → append §6 + Appendix
Apply SKILL-report.md templates to scratchpad data, following Rules A–D. See SKILL-report.md for full section templates and the anchor pattern for each append.
🔴 Verbatim table sections — use the deterministic slicer, never hand-copy. Several report tables (§3 TechniqueTables, §5.1 CombinedTacticCoverage, §5.2 AlertFiring, §5.3 ActiveVsTagged, §5.4 IncidentsByTactic, §5.5 DataReadiness, §5.6 ConnectorHealth) are pre-rendered by the PS1 under ## PRERENDERED in the scratchpad. Copy them with the read-only helper instead of transcribing by hand:
python .github/skills/mitre-coverage-report/slice_scratch.py --scratch temp/mitre_scratch_<ts>.md --list
python .github/skills/mitre-coverage-report/slice_scratch.py --scratch temp/mitre_scratch_<ts>.md --section AlertFiring
The slicer prefers the ## PRERENDERED copy when a section name also exists as a raw data block, strips pipeline scaffolding (<!-- … --> comments, SectionTitle: markers) wherever it appears, preserves #### sub-headings, and collapses blank runs — so the output drops straight into the report as a valid markdown table. Do NOT paste the raw Key | Value | … data blocks (the ones with a <!-- header --> comment and no |---| separator row) — they render as plain text, not tables, and pasting the whole scratchpad tail into one section corrupts the report.
⛔ Do NOT render §1–§6 in a single create_file call. The output will truncate silently. The scratchpad is ~60 KB; the rendered report exceeds the single-call output budget.
🔴 ALL 6 APPENDS ARE MANDATORY. Do NOT stop after §5 — §6 (Recommendations) and the Appendix (Score Methodology, Limitations) are critical and must be appended. After the 6th append, run grep_search for ## 6. Recommendations and ## Appendix on the report file to verify both exist. If either is missing, append the missing content immediately.
⚠️ CRITICAL WORKFLOW RULES - READ FIRST ⚠️
Before starting ANY MITRE coverage report:
- Run
Invoke-MitreScan.ps1 — this single script handles ALL data gathering (Phases 1-3). The LLM does NOT run queries, transcribe output, or write scratchpad sections
- Read
config.json for workspace ID, tenant, subscription, and Azure MCP parameters
- ALWAYS ask the user for output mode if not specified: inline chat summary, markdown file report, or both (default: both)
- ALWAYS ask the user for timeframe if not specified: the
-Days parameter controls the alert/incident KQL lookback (Phase 3). Default: 30 days. Phases 1-2 (REST API) are not time-bounded
- ALWAYS use
create_file for markdown reports (never use terminal commands)
- ALWAYS sanitize PII from saved reports — use generic placeholders for real rule names, workspace names, and tenant GUIDs in committed files
- Read scratchpad + SKILL-report.md before rendering — the scratchpad is the sole data source
- Custom Detections may be SKIPPED — the Graph API requires
CustomDetection.Read.All which needs admin consent. If skipped, the report notes this and shows AR-only analysis. Do NOT treat SKIPPED as an error — it's a graceful degradation
Prerequisites
| Dependency | Required By | Setup |
|---|
Azure CLI (az) | All phases (REST + KQL) | Install: aka.ms/installazurecli. Authenticate: az login --tenant <tenant_id> then az account set --subscription <subscription_id> |
| Azure RBAC | Phase 1-2 (REST API) | Microsoft Sentinel Reader on the workspace (analytic rule inventory + SOC Optimization) |
| KQL auth | Phase 3 (az monitor) | az login with https://api.loganalytics.io/.default scope (CA policy may enforce re-auth) |
| Microsoft.Graph PowerShell | Phase 1 M2 (Custom Detections) | Install-Module Microsoft.Graph.Authentication -Scope CurrentUser. Required scope: CustomDetection.Read.All. PS1 skips gracefully if unavailable |
| PowerShell 7.0+ | Script execution | #Requires -Version 7.0 |
🔴 PROHIBITED
- ❌ Running REST/KQL queries via MCP tools during data gathering — PS1 handles all queries
- ❌ Writing or modifying scratchpad sections manually — PS1 is the sole writer
- ❌ Fabricating technique counts, rule names, or coverage percentages
- ❌ Inventing ATT&CK technique IDs or names not in the reference JSON
- ❌ Overriding MITRE Coverage Score dimensions — the PS1 computes these deterministically
- ❌ Rendering the report without first reading the scratchpad file
- ❌ Reporting "100% coverage" for any tactic unless the data actually shows every technique covered
Execution Workflow
Phase 0: Initialization
- Read
config.json for sentinel_workspace_id, subscription_id, Azure MCP parameters
- Confirm output mode and timeframe with user (pass
-Days to PS1; default 30)
- Verify prerequisites:
az login session active, correct subscription set
Phases 1-3: Data Gathering (automated by PS1)
Run Invoke-MitreScan.ps1 — it handles all 3 phases automatically:
| Phase | Queries | Description | Execution Type |
|---|
| 1 | M1, M2 | Rule inventory — Analytic rules with MITRE tactics/techniques (REST), Custom Detection rules with mitreTechniques (Graph, graceful skip) | REST + Graph |
| 2 | M3 | SOC Optimization — Coverage recommendations with threat scenario context, MITRE tagging suggestions for untagged rules | REST |
| 3 | M4, M5, M6, M7, M8 | Operational correlation — SecurityAlert firing counts per rule with MITRE cross-reference, SecurityIncident volume by tactic, platform-native alert MITRE coverage, table ingestion volume for data readiness validation, data connector health from SentinelHealth | KQL |
Post-processing (automated by PS1):
| Task | Phase | Description |
|---|
| Tactic coverage matrix | 1 | For each ATT&CK tactic, count enabled rules and covered techniques against the framework reference |
| Technique drill-down | 3 | Map every framework technique to its covering rules AND pre-compute tier/product annotations from CTID cross-reference |
| Untagged rule identification | 1 | Find rules with no MITRE tactics AND no techniques |
| ICS technique extraction | 1 | Separate T0xxx (ICS/OT) technique mappings |
| Threat scenario parsing | 2 | Extract active/recommended detection counts and per-tactic breakdowns from SOC Optimization |
| AI MITRE tagging suggestions | 2 | Extract suggested tactics/techniques for untagged rules. Cross-reference against Phase 1 actual rule tags to verify if suggestions were applied (emits VerifyStatus: Applied/Partial/NotApplied/NotFound per rule, plus summary counts AR_TagsApplied/AR_TagsPartial/AR_TagsNotApplied/AR_TagsNotFound) |
| Alert-to-MITRE correlation | 3 | Cross-reference firing alerts with Phase 1 MITRE tags |
| Active tactic coverage | 3 | Compute which tactics have rules that actually fire alerts |
| Platform alert MITRE extraction | 3 | Extract MITRE techniques attributed by platform-native product alerts (M6) |
| Product presence detection | 3 | Derive active M365 Defender products from SecurityAlert ProductName |
| CTID tier classification | 3 | Cross-reference active products with CTID mapping to classify techniques as Tier 1/2/3 |
| Combined tactic coverage | 3 | Merge custom rule and platform Tier 1/2 coverage per tactic |
| Data readiness cross-reference | 3 | Extract KQL table dependencies from rule queries, cross-reference with M7 ingestion volumes, classify rules as Ready/Partial/NoData |
| Connector health enrichment | 3 | Cross-reference M8 SentinelHealth connector status with Data Readiness — flag "Ready" rules whose feeding connector is degraded or failing |
| Table tier classification | 3 | Cross-reference M9 table tier metadata with rule KQL table dependencies — flag rules targeting Basic/Data Lake tier tables as "TierBlocked" (phantom coverage: rule structurally cannot fire regardless of data volume) |
| Coverage Score computation | All | Weighted composite score from 5 dimensions |
Scratchpad output: PS1 writes all results to temp/mitre_scratch_<timestamp>.md (~28 KB, ~12 named sections). See SKILL-report.md for the Section-to-Scratchpad Mapping.
Phase 4: Render Output (LLM)
🔴 MANDATORY — Load scratchpad + report template before rendering:
- Read the scratchpad file (path printed by PS1). This single file contains ALL data from Phases 1-3.
- Read SKILL-report.md for the complete rendering templates and formatting rules.
Pre-render validation:
- Verify scratchpad has all 3 phase sections (PHASE_1 through PHASE_3)
- Check SCORE section has all 5 dimensions
- If Phase 3 shows FAILED for M4/M5 (token expiry), note this in the report — the Operational dimension defaults to 0
Render — Section-by-Section:
| Section | Data Source (scratchpad keys) | Required |
|---|
| §1 Executive Summary | All phases + SCORE | ✅ Coverage Score, Workspace at a Glance, Top 3 |
| §2 Tactic Coverage | PHASE_1.TacticCoverage | ✅ 14-tactic matrix with coverage % |
| §3 Technique Deep Dive | PHASE_3.TechniqueDetail (enriched with Tier/TierProducts) | ✅ Per-tactic technique tables with pre-computed tier badges |
| §4 Coverage Gap Analysis | PHASE_1.TacticCoverage + PHASE_3.TechniqueDetail + PHASE_2.ThreatScenarios | ✅ Gaps, priorities, threat scenario alignment |
| §5 Operational MITRE Correlation | PHASE_3.AlertFiring + IncidentsByTactic + ActiveTacticCoverage + PlatformAlertCoverage + PlatformTechniquesByTier + PlatformTacticCoverage + DataReadiness + DataReadiness_Summary + MissingTables + TierBlockedTables + ConnectorHealth + ConnectorHealth_Summary | ✅ Which rules fire, platform coverage, combined tactic view, data readiness, tier-blocked phantom coverage, connector health |
| §6 Recommendations | All phases | ✅ Untagged rule remediation, Content Hub suggestions, coverage priorities |
Query File Reference
All queries are defined as YAML files in queries/phase1-3/.
YAML Format
id: mitre-m1
name: Analytic Rule MITRE Extraction
description: Fetch rules with tactics/techniques
phase: 1
type: rest
url: https://management.azure.com/...
jmespath: value[].{...}
Complete Query Inventory
| Phase | File | ID | Type | Description |
|---|
| 1 | M1-AnalyticRuleMitre.yaml | mitre-m1 | rest | Scheduled + NRT analytic rules with MITRE tactics, techniques, severity, query text |
| 1 | M2-CustomDetectionMitre.yaml | mitre-m2 | graph | Custom Detection rules with mitreTechniques (graceful skip if auth unavailable) |
| 2 | M3-SocOptCoverage.yaml | mitre-m3 | rest | SOC Optimization coverage recommendations with threat scenarios and MITRE tagging suggestions |
| 3 | M4-AlertFiringByMitre.yaml | mitre-m4 | kql | SecurityAlert firing counts per rule with severity breakdown (30d lookback) |
| 3 | M5-IncidentsByTactic.yaml | mitre-m5 | kql | SecurityIncident volume by tactic with classification breakdown |
| 3 | M6-PlatformAlertCoverage.yaml | mitre-m6 | kql | Platform-native SecurityAlert detections with MITRE technique attribution (excludes custom rules) |
| 3 | M7-TableIngestionVolume.yaml | mitre-m7 | kql | 7-day average daily ingestion volume per table from Usage table for data readiness validation |
| 3 | M8-ConnectorHealth.yaml | mitre-m8 | kql | SentinelHealth data connector fetch status — latest state, success/failure counts, health % per connector (supplements M7 with early-warning connector failure detection) |
| 3 | M9-TableTierClassification.yaml | mitre-m9 | cli | Log Analytics table tier metadata (Analytics/Basic/Data Lake) via az monitor log-analytics workspace table list — identifies tables that analytics rules cannot query |
Output Modes
Mode 1: Inline Chat Summary (default for quick requests)
Compact executive summary rendered directly in chat with MITRE Coverage Score and top coverage gaps.
Mode 2: Markdown File Report
Full detailed report saved to reports/sentinel/mitre_coverage_report_<YYYYMMDD_HHMMSS>.md.
Mode 3: Both (default when user says "report" or "generate report")
Inline chat executive summary + full markdown file.
Ask user if not specified:
"How would you like the MITRE coverage report? I can provide:
- Inline chat summary — MITRE Score + top gaps in chat
- Markdown file — detailed report saved to reports/sentinel/
- Both (recommended) — summary in chat + full report file"
Deterministic Rendering Rules
These rules eliminate LLM interpretation variance. Apply them EXACTLY during Phase 4 rendering.
Rule A: Coverage Level Classification
Assign emoji badges to each tactic row in the coverage matrix based on the percentage of techniques covered:
| Coverage % | Badge | Level |
|---|
| 0% | 🔴 | No coverage |
| 1-15% | 🟠 | Critical gap |
| 16-30% | 🟡 | Partial |
| 31-50% | 🔵 | Moderate |
| 51-75% | 🟢 | Good |
| >75% | ✅ | Strong |
⛔ PROHIBITED: Assigning badges based on "importance" or "this tactic is more relevant." The badge MUST match the percentage threshold table above.
Rule B: Threat Scenario Priority
When rendering SOC Optimization threat scenarios, order by coverage gap (recommended minus active) descending, but assign badges based on completion rate (proportional to scenario size):
| Completion Rate | Priority | Badge |
|---|
| <15% | 🔴 High | Very early stage — most recommendations unaddressed |
| 15–35% | 🟠 Medium | Work in progress — significant room for improvement |
| 35–60% | 🟡 Low | Approaching healthy coverage for typical environments |
| ≥60% | ✅ Met | Strong coverage — well above realistic implementation targets |
Why rate-based? Recommendation counts reflect the full Content Hub template catalogue including templates for vendor products not deployed in the environment (e.g., all firewall vendors). A 609-rule scenario will be permanently 🔴 under absolute-gap thresholds even at 80% coverage. Rate-based badges give proportional, meaningful progress signals.
CompletedBySystem note: CompletedBySystem is a SOC Optimization state, not a rate indicator. Some CompletedBySystem entries have low rates (recommended >> active). Always use the completion rate for badge assignment. The State column is displayed for context but does NOT override the rate-based badge.
Rule C: "Paper Tiger" Detection
When Phase 3 data is available, identify paper tiger rules — rules with MITRE tags that have NEVER produced an alert in the lookback period. These rules are tagged but non-operational, and their coverage is theoretical, not proven.
| Condition | Classification | Display |
|---|
| Rule tagged with MITRE + 0 alerts in lookback | ⚠️ Paper tiger | Note in technique drill-down |
| Rule tagged with MITRE + ≥1 alert | ✅ Operationally validated | Normal display |
| Phase 3 data unavailable (FAILED/SKIPPED) | — | Skip paper-tiger analysis, note data gap |
⛔ PROHIBITED: Reporting coverage percentages as "validated" when Phase 3 data is missing. If M4/M5 failed, state: "Coverage percentages reflect rule tagging only — operational validation unavailable (Phase 3 KQL queries failed)."
Rule D: Recommendation Ranking
Rank recommendations by impact using this priority order:
| Priority | Category | Criteria |
|---|
| 1 | 🔴 Low-rate threat scenarios | SOC Optimization scenarios with <15% completion rate. Exclude CompletedByUser scenarios with ≥50% completion rate (Rule E — Reviewed & Addressed). Only include ⚠️ Premature CompletedByUser (<50% rate) |
| 2 | 🔴 Zero-coverage detectable tactics | Tactics with 0% coverage AND ✅ Detectable classification (see tactic table). Exclude ⬜ Inherent blind spot tactics (Reconnaissance, Resource Development) — report these as acknowledged limitations, not actionable gaps |
| 3 | 🟠 Untagged rule remediation | Rules with AI-suggested MITRE tags from SOC Optimization |
| 4 | 🟠 Paper tiger rules | MITRE-tagged rules that never fire (if Phase 3 available) |
| 5 | 🟡 Low-coverage tactics | Tactics with 1-15% coverage |
| 6 | 🟡 Content Hub suggestions | Template-based rules available for uncovered techniques |
| 7 | ⬜ Inherent blind spot tactics | Zero-coverage tactics classified as ⬜ Inherent blind spot. Acknowledge the limitation; suggest compensating controls (threat intel feeds, brand monitoring) only if relevant to the organization |
Rule E: CompletedByUser Completion-Rate Gate
When a SOC Optimization threat scenario has State == CompletedByUser, the user has manually marked it as reviewed. However, marking a scenario "complete" after enabling 2/500 recommendations is fundamentally different from enabling 28/46. Use the completion rate (ActiveDetections / RecommendedDetections × 100) to determine rendering treatment:
| CompletedByUser + Completion Rate | Treatment | Rationale |
|---|
| ≥ 50% | 🟢 Reviewed & Addressed — render in a separate muted "Reviewed Scenarios" summary below the active gaps table. Exclude from §6 recommendations and Coverage Priority Matrix | User has genuinely triaged the scenario; remaining gap is likely non-applicable templates or platform-only coverage |
| < 50% | ⚠️ Premature Completion — render in the main active gaps table with full gap badge + ⚠️ flag in the State column. Include in §6 recommendations | Gap is too large relative to recommendations to be a deliberate triage decision |
Threshold: 50% is the default. This balances trust in the user's judgment against protection from rubber-stamped completions.
Scratchpad column: CompletionRate is pre-computed by the PS1 and included in the ThreatScenarios row. The LLM reads this value directly — do not recompute it.
Interaction with Rule B (rate-based badges): Rule B still applies for badge assignment on all scenarios. Rule E only controls where CompletedByUser scenarios are rendered (active table vs reviewed summary) and whether they appear in §6 recommendations.
CompletedBySystem scenarios are not affected — they continue to use rate-based badges (Rule B) without the completion-rate gate, since the system assessment is independent of user action.
MITRE Coverage Score
The MITRE Coverage Score is a composite metric (0-100) computed by the PS1 from 5 weighted dimensions. Each dimension scores 0-100 independently, then the weighted sum produces the final score.
Dimensions
| # | Dimension | Weight | Formula | What It Measures |
|---|
| 1 | Breadth | 25% | (Σ per-technique readiness credit / total ATT&CK techniques) × 100 blended 60/40 with combined platform coverage | Readiness-weighted technique coverage. Each technique gets fractional credit based on the best rule covering it: Fired=1.0, Ready=0.75, Partial=0.50, NoData=0.25, TierBlocked=0.0. AR and CD rules follow the same readiness constraints. One firing rule gives full credit even if other rules covering the same technique are NoData |
| 2 | Balance | 10% | (tactics with ≥1 rule / 14 tactics) × 100 | Whether coverage spans all kill chain phases or clusters in a few |
| 3 | Operational | 30% | (MITRE-tagged rules that fired alerts / total MITRE-tagged enabled rules) × 100 | Whether tagged rules actually produce detections (not paper tigers). Highest weight: directly rewards purple teaming and operationally validated detections |
| 4 | Tagging | 15% | (rules with MITRE tags / total rules) × 100 | Completeness of MITRE classification across the rule inventory |
| 5 | SOC Alignment | 20% | (completed SOC recommendations / total SOC coverage recommendations) × 100 | Alignment with Microsoft's threat-scenario-driven coverage model |
Score Interpretation
| Score Range | Assessment | Typical Profile |
|---|
| 80-100 | 🟢 Strong | Broad coverage, balanced tactics, operationally validated, well-tagged, SOC-aligned |
| 60-79 | 🔵 Good | Solid coverage with some gaps; may have clustering or unvalidated rules |
| 40-59 | 🟡 Moderate | Significant gaps in breadth or operational validation; improvement opportunities |
| 20-39 | 🟠 Developing | Limited coverage across the framework; many uncovered tactics |
| 0-19 | 🔴 Critical | Minimal detection coverage; urgent investment needed |
Score Context Notes
- Operational = 0 when Phase 3 KQL queries fail (token expiry). Report this: "Operational score 0 reflects data unavailability, not necessarily poor operational coverage."
- SOC Alignment = 50 (default) when no SOC Optimization recommendations exist. This is a neutral baseline, not a penalty.
- Breadth score is naturally low because the ATT&CK framework contains 216+ techniques, many of which are endpoint-specific or pre-compromise with limited Sentinel visibility. Do NOT present this as a crisis — contextualize it: "Prioritize coverage by threat scenario relevance rather than pursuing raw percentage."
- Custom Detections SKIPPED affects Breadth and Tagging dimensions (rules not counted). Note the impact in the report.
- Platform Coverage is reported as a supplementary metric alongside the MITRE Score (not folded into the 5 dimensions). The scratchpad includes
Platform_Tier1/2/3, Platform_ActiveProducts, and RuleBasedPlusPlatform_Coverage. Render this in §1 and §5 per SKILL-report.md templates. The CTID tier classification requires m365-platform-coverage.json — if the file is missing, platform tiers default to empty and the report notes the limitation.
Domain Reference
ATT&CK Enterprise Tactic Kill Chain Order
The 14 ATT&CK Enterprise tactics in kill chain order (PS1 uses this ordering for all output):
| # | Tactic (Sentinel API name) | Display Name | Cloud/Identity Relevance | Detectability |
|---|
| 1 | Reconnaissance | Reconnaissance | 🟡 Low — mostly pre-compromise; limited Sentinel visibility | ⬜ Inherent blind spot |
| 2 | ResourceDevelopment | Resource Development | 🟡 Low — attacker infrastructure; limited Sentinel visibility | ⬜ Inherent blind spot |
| 3 | InitialAccess | Initial Access | 🔴 High — phishing, valid accounts, external services | ✅ Detectable |
| 4 | Execution | Execution | 🟠 Medium — scripting, cloud admin commands | ✅ Detectable |
| 5 | Persistence | Persistence | 🔴 High — account manipulation, app registrations, inbox rules | ✅ Detectable |
| 6 | PrivilegeEscalation | Privilege Escalation | 🔴 High — tenant policy modification, valid accounts | ✅ Detectable |
| 7 | DefenseEvasion | Defense Evasion | 🟠 Medium — many techniques are endpoint-focused | ✅ Detectable |
| 8 | CredentialAccess | Credential Access | 🔴 High — brute force, token theft, AiTM | ✅ Detectable |
| 9 | Discovery | Discovery | 🟡 Medium — account/cloud service discovery | ✅ Detectable |
| 10 | LateralMovement | Lateral Movement | 🟠 Medium — remote services, internal spearphishing | ✅ Detectable |
| 11 | Collection | Collection | 🟡 Medium — email collection, data from cloud storage | ✅ Detectable |
| 12 | CommandAndControl | Command and Control | 🟠 Medium — application layer protocol, web service | ✅ Detectable |
| 13 | Exfiltration | Exfiltration | 🟠 Medium — exfiltration over C2 channel, cloud account | ✅ Detectable |
| 14 | Impact | Impact | 🟠 Medium — resource hijacking (crypto mining), account removal | ✅ Detectable |
Detectability classification:
- ✅ Detectable: Techniques in this tactic generate observable events in Sentinel data sources (sign-in logs, audit logs, endpoint telemetry, email events, etc.). KQL detection rules can be written and deployed.
- ⬜ Inherent blind spot: Techniques in this tactic describe attacker activity that occurs outside the monitored environment (e.g., attacker creating fake accounts on external services, acquiring infrastructure). CTID mappings for these tactics are typically protect/respond capabilities (Conditional Access blocking, PAM restrictions), not detect. No KQL detection rules exist or can realistically be created. Do not recommend deploying rules for inherent blind spot tactics — acknowledge the limitation and recommend compensating controls (e.g., brand monitoring services, threat intelligence feeds) if relevant.
Sentinel-Specific MITRE Mapping Notes
- Sentinel uses PascalCase for tactic names in the REST API:
InitialAccess, CommandAndControl, CredentialAccess. The ATT&CK STIX data uses kebab-case (initial-access). The reference JSON maps between these.
- Sub-techniques (T1xxx.xxx) are tracked by Sentinel but the REST API
properties.techniques field may contain both parent techniques (T1078) and sub-techniques (T1078.004). The PS1 counts at the parent technique level for coverage matrix purposes.
- ICS/OT techniques (T0xxx) use a separate numbering scheme from ATT&CK for ICS. These are extracted and reported separately since they don't map to the Enterprise framework.
- Custom Detection
mitreTechniques uses the same technique ID format but may specify sub-techniques that analytic rules don't. The PS1 aggregates both sources.
Tactic-Specific Detection Guidance
When rendering recommendations (§6), use these cloud/identity-relevant technique priorities:
| Tactic | Key Sentinel-Detectable Techniques | Priority |
|---|
| InitialAccess | T1078 (Valid Accounts), T1566 (Phishing), T1133 (External Remote Services) | 🔴 Must-have |
| Persistence | T1098 (Account Manipulation), T1136 (Create Account), T1078 (Valid Accounts) | 🔴 Must-have |
| CredentialAccess | T1110 (Brute Force), T1528 (Steal App Access Token), T1621 (MFA Request Gen) | 🔴 Must-have |
| PrivilegeEscalation | T1484 (Domain/Tenant Policy Mod), T1078 (Valid Accounts), T1098 (Account Manipulation) | 🔴 Must-have |
| DefenseEvasion | T1078 (Valid Accounts), T1484 (Domain/Tenant Policy Mod), T1562 (Impair Defenses) | 🟠 Important |
| Exfiltration | T1567 (Exfil Over Web Service), T1537 (Transfer to Cloud Account) | 🟠 Important |
| Collection | T1114 (Email Collection), T1213 (Data from Info Repos) | 🟠 Important |
SOC Optimization Threat Scenario Reference
SOC Optimization recommendations map to named threat scenarios. When rendering §4, interpret these:
| Scenario | Key Attack Pattern | Priority Tactics |
|---|
| AiTM (Adversary in the Middle) | Session token theft, AiTM phishing | InitialAccess, CredentialAccess |
| BEC (Financial Fraud) | Email account takeover for wire fraud | InitialAccess, CredentialAccess, Persistence |
| BEC (Mass Credential Harvest) | Large-scale phishing campaigns | InitialAccess, CredentialAccess, DefenseEvasion |
| Human Operated Ransomware | Post-compromise hands-on keyboard | LateralMovement, CredentialAccess, DefenseEvasion, Impact |
| Credential Exploitation | Credential stuffing, password spray | InitialAccess, CredentialAccess, Discovery |
| IaaS Resource Theft | Cloud compute hijacking (crypto mining) | CredentialAccess, Persistence, Impact |
| Network Infiltration | Traditional network-based attacks | Discovery, LateralMovement, C2 |
| X-Cloud Attacks | Cross-cloud lateral movement | CredentialAccess, PrivilegeEscalation, Persistence |
| ERP (SAP) | SAP financial process manipulation | InitialAccess, DefenseEvasion |
SOC Optimization Recommendation States
| State | Meaning | Report Treatment |
|---|
Active | Recommendation is open and actionable | Show as gap — count toward coverage deficit |
InProgress | User has started addressing the recommendation | Show as in-progress — partial credit |
CompletedBySystem | Microsoft's automated assessment found coverage adequate | Use rate-based badge (may still show 🔴/🟠/🟡 if completion rate is low). State displayed in table for context |
Completed | User manually marked as complete | Show as met — ✅ |
SVG Dashboard Generation
After the report is generated, the user may request an SVG dashboard visualization.
Trigger: "generate SVG dashboard", "visualize this report", "SVG from the MITRE report"
✅ DEFAULT: run the deterministic renderer (render_dashboard.py)
Do this first — do NOT hand-author the SVG. render_dashboard.py produces the manifest-driven 5-row dashboard non-interactively, parsing every value from the scratchpad + report + svg-widgets.yaml (no hardcoded run data). It is faster, deterministic, and produces a known-good layout. Run it:
python .github/skills/mitre-coverage-report/render_dashboard.py \
--scratch temp/mitre_scratch_<ts>.md \
--manifest .github/skills/mitre-coverage-report/svg-widgets.yaml \
--report reports/sentinel/mitre_coverage_report_<label>_<ts>.md \
--out reports/sentinel/mitre_coverage_report_<label>_<ts>_dashboard.svg
It reads the donut center, score dimensions, tactic bars, threat-scenario table, and KPI values from the scratchpad, and the Top-3 recommendation cards from the report's ### 🎯 Top 3 Recommendations table (falling back to top threat-scenario gaps if absent). Output is self-contained SVG with explicit fill on every <text>.
| Action | Status |
|---|
Running render_dashboard.py when the user asks to visualize/generate a dashboard | ✅ REQUIRED (default path) |
Hand-authoring the SVG via the svg-dashboard skill instead of running the script | ❌ PROHIBITED unless the user explicitly asks for a bespoke/custom layout the renderer can't produce |
Fallback — bespoke/interactive dashboards (svg-dashboard skill)
Only use this path when the user explicitly wants a custom layout, different widgets, or styling the deterministic renderer doesn't support. Edit svg-widgets.yaml first if the change is layout/field-level — the renderer reads it at generation time, so many "customizations" don't require hand-authoring.
- Load the
svg-dashboard skill
- Use the rendered report + scratchpad data to build visualization widgets
- Recommended widget types for MITRE coverage:
- Score card — MITRE Coverage Score with 5 dimension breakdown
- Bar chart — Per-tactic coverage percentages (14 bars)
- Donut chart — Rule inventory breakdown (AR enabled/disabled, CD enabled/disabled, untagged)
- Table — Top 5 coverage gaps (tactic + gap %)
- KPI cards — Total techniques covered, SOC scenarios met, untagged rules
Troubleshooting
| Issue | Solution |
|---|
| Phase 3 KQL queries fail (token expired) | Re-authenticate: az login --tenant <tenant_id> --scope https://api.loganalytics.io/.default |
| Custom Detections SKIPPED | Normal if Graph API admin consent not granted. Report proceeds with AR-only analysis |
| SOC Optimization returns 0 recs | Workspace may not have SOC Optimization enabled, or all recommendations are already completed |
| Breadth score seems low (10-20%) | This is typical — 216+ techniques means even well-covered workspaces have low percentages. Focus on threat-scenario-aligned priorities, not raw percentage |
| ICS techniques appear in output | Normal if Defender for IoT rules are deployed. They're reported separately from Enterprise ATT&CK |
az rest returns 403 | Check RBAC: user needs Microsoft Sentinel Reader on the workspace |
