Mapping MITRE ATT&CK Techniques

When to Use

Use this skill when:

• Generating an ATT&CK coverage heatmap to show which techniques your detection stack addresses
• Tagging existing SIEM use cases or Sigma rules with ATT&CK technique IDs for structured reporting
• Aligning your security program roadmap to specific adversary groups known to target your sector

Do not use this skill for real-time incident triage — ATT&CK mapping is an analytical activity best performed post-detection or during threat hunting planning.

Prerequisites

• Access to MITRE ATT&CK knowledge base (https://attack.mitre.org) or local ATT&CK STIX data bundle
• ATT&CK Navigator web app or local installation (https://mitre-attack.github.io/attack-navigator/)
• Inventory of existing detection rules (Sigma, Splunk, Sentinel KQL) to assess current coverage
• ATT&CK Python library: pip install mitreattack-python

Workflow

Step 1: Obtain Current ATT&CK Data

Download the latest ATT&CK STIX bundle for the relevant matrix (Enterprise, Mobile, ICS):

curl -o enterprise-attack.json \
  https://raw.githubusercontent.com/mitre/cti/master/enterprise-attack/enterprise-attack.json

Use the mitreattack-python library to query techniques programmatically:

from mitreattack.stix20 import MitreAttackData

mitre = MitreAttackData("enterprise-attack.json")
techniques = mitre.get_techniques(remove_revoked_deprecated=True)
for t in techniques[:5]:
    print(t["external_references"][0]["external_id"], t["name"])

Step 2: Map Existing Detections to Techniques

For each SIEM rule or Sigma file, assign ATT&CK technique IDs. Sigma rules support native ATT&CK tagging:

tags:
  - attack.execution
  - attack.t1059.001  # PowerShell
  - attack.t1059.003  # Windows Command Shell

Create a coverage matrix: list each technique ID and mark as: Detected (alert fires), Logged (data present but no alert), Blind (no data source).

Step 3: Prioritize Coverage Gaps Using Threat Intelligence

Cross-reference coverage gaps with adversary groups targeting your sector. Use ATT&CK Groups data:

groups = mitre.get_groups()
apt29 = mitre.get_object_by_attack_id("G0016", "groups")
apt29_techniques = mitre.get_techniques_used_by_group(apt29)
for t in apt29_techniques:
    print(t["object"]["external_references"][0]["external_id"])

Prioritize adding detection for techniques used by high-priority threat groups where your coverage is blind.

Step 4: Build Navigator Heatmap

Export coverage scores as ATT&CK Navigator JSON layer:

import json

layer = {
    "name": "SOC Detection Coverage Q1 2025",
    "versions": {"attack": "14", "navigator": "4.9", "layer": "4.5"},
    "domain": "enterprise-attack",
    "techniques": [
        {"techniqueID": "T1059.001", "score": 100, "comment": "Splunk rule: PS_Encoded_Command"},
        {"techniqueID": "T1071.001", "score": 50, "comment": "Logged only, no alert"},
        {"techniqueID": "T1055", "score": 0, "comment": "No coverage — blind spot"}
    ],
    "gradient": {"colors": ["#ff6666", "#ffe766", "#8ec843"], "minValue": 0, "maxValue": 100}
}
with open("coverage_layer.json", "w") as f:
    json.dump(layer, f)

Import layer into ATT&CK Navigator (https://mitre-attack.github.io/attack-navigator/) for visualization.

Step 5: Generate Executive Coverage Report

Summarize coverage by tactic category (Initial Access, Execution, Persistence, etc.) with counts and percentages. Provide a risk-ranked list of top 10 blind-spot techniques based on adversary group usage frequency. Recommend data source additions (e.g., "Enable PowerShell Script Block Logging to address 12 Execution sub-technique gaps").

Key Concepts

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