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mapping-hunts-to-mitre-attack

Maps hunts and detections to MITRE ATT&CK for coverage analysis: tagging hypotheses with techniques, building a coverage matrix from completed hunts, and identifying high-risk gaps to prioritize next. Activates for requests to map hunts to ATT&CK, build a coverage heatmap, or find detection gaps by technique.

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Files included (4)

  • SKILL.md2.9 KB
  • LICENSE340 B
  • references/api-reference.md1.2 KB
  • scripts/analyst.py2.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Mapping Hunts to MITRE ATT&CK

When to Use

  • You have a backlog of hunts/detections and want a coverage view by technique.
  • You need to prioritize the next hunt by mapping current coverage against relevant adversary TTPs (e.g., from a threat profile).
  • You want to produce an ATT&CK Navigator layer to visualize coverage and gaps.

Do not use technique counts as a quality metric — broad shallow coverage can hide weak detections; pair the map with detection confidence.

Prerequisites

  • An inventory of hunts/detections with the data sources each uses.
  • The ATT&CK enterprise matrix (technique IDs and tactics) for reference.

Workflow

Step 1: Tag each hunt with techniques

Annotate every hunt/detection with the ATT&CK technique(s) it covers and a confidence score (e.g., high/medium/low based on telemetry quality and FP rate).

Step 2: Build the coverage matrix

Aggregate tags into a technique → coverage map. Group by tactic to see where the kill chain is strong or thin.

python scripts/analyst.py coverage hunts.json --out layer.json

Step 3: Overlay your threat model

Weight techniques by relevance (actors targeting your sector, observed in incidents). A gap on a high-relevance technique outranks a gap on an unlikely one.

Step 4: Identify and prioritize gaps

Surface techniques with no coverage or low confidence; rank by threat relevance and data availability to pick the next hunt.

Step 5: Visualize and share

Emit an ATT&CK Navigator layer (scores/colors) for stakeholders and to track progress over time.

Validation

  • Every hunt maps to at least one valid technique ID (^T\d{4}(\.\d{3})?$).
  • Coverage reflects confidence, not just presence/absence.
  • The Navigator layer loads and renders the intended scores.

Pitfalls

  • Counting a low-confidence hunt as full coverage.
  • Mapping to overly broad parent techniques when a sub-technique is more accurate.
  • Ignoring data-source feasibility when prioritizing gaps.

References

  • See references/api-reference.md for the coverage/layer generator.
  • ATT&CK Navigator and enterprise techniques (linked in frontmatter).

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