Implementing MITRE ATT&CK Coverage Mapping Skill

Implementing MITRE ATT&CK Coverage Mapping

Overview

MITRE ATT&CK coverage mapping gives SOC teams a structured, adversary-centric lens to evaluate detection capabilities. Enterprise SIEMs on average have detection coverage for only 21% of ATT&CK techniques (2025 CardinalOps report), with 13% of existing rules being non-functional due to misconfigured data sources. Systematic coverage mapping identifies gaps, prioritizes rule development, and tracks detection maturity over time. ATT&CK v18.1 (December 2025) is the latest version.

When to Use

When deploying or configuring implementing mitre attack coverage mapping capabilities in your environment
When establishing security controls aligned to compliance requirements
When building or improving security architecture for this domain
When conducting security assessments that require this implementation

Prerequisites

Access to MITRE ATT&CK Navigator (https://mitre-attack.github.io/attack-navigator/)
Inventory of all active SIEM detection rules
MITRE ATT&CK technique mapping for each detection rule
Data source inventory (which log sources are ingested)
Understanding of adversary threat profiles relevant to your industry

Coverage Mapping Process

Step 1: Export Current Detection Rules

# Splunk ES - Export all active correlation searches with MITRE mappings
| rest /services/saved/searches
| search disabled=0 action.correlationsearch.enabled=1
| table title, search, action.notable.param.security_domain,
    action.notable.param.severity, action.correlationsearch.annotations
| eval mitre_techniques=mvfilter(match('action.correlationsearch.annotations', "mitre_attack"))

// Microsoft Sentinel - Export analytics rules with MITRE mapping
SecurityAlert
| summarize count() by AlertName, ProductName
| join kind=inner (
    resources
    | where type == "microsoft.securityinsights/alertrules"
    | extend tactics = properties.tactics
) on $left.AlertName == $right.name

Step 2: Build the Coverage Matrix

ATT&CK Navigator Layer Format

{
    "name": "SOC Detection Coverage - 2025",
    "versions": {
        "attack": "16",
        "navigator": "5.1",
        "layer": "4.5"
    },
    "domain": "enterprise-attack",
    "description": "Current detection coverage mapping",
    "techniques": [
        {
            "techniqueID": "T1110",
            "tactic": "credential-access",
            "color": "#00ff00",
            "comment": "2 active rules - Brute Force detection via EventCode 4625",
            "score": 75,
            "metadata": [
                {"name": "rule_count", "value": "2"},
                {"name": "data_sources", "value": "Windows Security Log, Linux Auth"},
                {"name": "last_validated", "value": "2025-01-15"}
            ]
        },
        {
            "techniqueID": "T1059.001",
            "tactic": "execution",
            "color": "#00ff00",
            "comment": "3 rules - PowerShell Script Block Logging",
            "score": 85
        },
        {
            "techniqueID": "T1055",
            "tactic": "defense-evasion",
            "color": "#ff0000",
            "comment": "NO DETECTION - Requires Sysmon EventCode 8/10",
            "score": 0
        }
    ],
    "gradient": {
        "colors": ["#ff0000", "#ffff00", "#00ff00"],
        "minValue": 0,
        "maxValue": 100
    }
}

Step 3: Score Each Technique

| Score | Color | Meaning | Criteria | |---|---|---|---| | 0 | Red | No Detection | No rules, missing data sources | | 25 | Orange | Minimal | Rule exists but not validated/tested | | 50 | Yellow | Partial | Rule works but limited coverage | | 75 | Light Green | Good | Validated rule with good data sources | | 100 | Green | Excellent | Multiple validated rules, tested with emulation |

Scoring Criteria Detail

Score = Data_Source_Score (0-25) + Rule_Quality_Score (0-25) +
        Validation_Score (0-25) + Enrichment_Score (0-25)

Data_Source_Score:
  25: All required data sources ingested and parsed
  15: Primary data source available
  5:  Partial data source coverage
  0:  Required data sources not available

Rule_Quality_Score:
  25: Rule uses CIM-compliant queries with proper thresholds
  15: Rule works but may generate false positives
  5:  Basic rule with no tuning
  0:  No detection rule

Validation_Score:
  25: Validated with adversary emulation (Atomic Red Team)
  15: Tested with synthetic data
  5:  Logic reviewed but not tested
  0:  Not validated

Enrichment_Score:
  25: Context-rich with asset, identity, and TI enrichment
  15: Basic enrichment (asset lookup)
  5:  No enrichment
  0:  N/A (no rule)

Step 4: Identify Priority Gaps

Gap Prioritization Framework

Priority = Technique_Prevalence x Impact x Feasibility

Technique_Prevalence (0-10):
  - Based on MITRE Top Techniques report
  - Frequency in your industry's threat landscape
  - Observed in recent incidents/breaches

Impact (0-10):
  - Damage potential if technique succeeds
  - Difficulty of recovery
  - Data sensitivity at risk

Feasibility (0-10):
  - Data source availability
  - Rule complexity
  - Engineering effort required

Top Priority Techniques to Cover (2025)

| Technique | ID | Prevalence | Typical Gap Reason | |---|---|---|---| | Command and Scripting Interpreter | T1059 | Very High | Requires script block logging | | Phishing | T1566 | Very High | Email gateway integration | | Valid Accounts | T1078 | High | Baseline behavior needed | | Process Injection | T1055 | High | Requires Sysmon or EDR | | Lateral Movement (RDP/SMB) | T1021 | High | Network segmentation visibility | | Scheduled Task/Job | T1053 | High | Event log collection | | Data Encrypted for Impact | T1486 | High | File system monitoring | | Ingress Tool Transfer | T1105 | Medium | Network traffic analysis |

Step 5: Build Detection Roadmap

Quarter 1: Close Critical Gaps (Score 0, High Prevalence)
  Week 1-2: Enable missing data sources
  Week 3-4: Build and test rules for top 5 gap techniques
  Week 5-8: Validate with adversary emulation
  Week 9-12: Tune and operationalize

Quarter 2: Improve Partial Coverage (Score 25-50)
  - Upgrade existing rules with enrichment
  - Add secondary detection methods
  - Validate with purple team exercises

Quarter 3: Mature Good Coverage (Score 50-75)
  - Add behavioral analytics
  - Implement detection-as-code pipeline
  - Cross-technique correlation rules

Quarter 4: Excellence (Score 75-100)
  - Continuous testing with BAS tools
  - Automated coverage regression testing
  - Red team validation

Automated Coverage Assessment

Data Source to Technique Mapping

# Map available data sources to detectable techniques
DATA_SOURCE_TECHNIQUE_MAP = {
    "Windows Security Event Log": [
        "T1110", "T1078", "T1053.005", "T1098", "T1136",
        "T1070.001", "T1021.001", "T1543.003"
    ],
    "Sysmon": [
        "T1055", "T1059", "T1003", "T1547.001", "T1036",
        "T1218", "T1105", "T1071"
    ],
    "Network Traffic (Firewall/IDS)": [
        "T1071", "T1048", "T1105", "T1572", "T1090",
        "T1571", "T1573"
    ],
    "DNS Logs": [
        "T1071.004", "T1568", "T1583.001", "T1048.003"
    ],
    "Email Gateway": [
        "T1566.001", "T1566.002", "T1534"
    ],
    "Cloud Audit Logs": [
        "T1078.004", "T1537", "T1530", "T1580",
        "T1087.004", "T1098.001"
    ],
}

Reporting Dashboard Queries

Coverage Summary by Tactic

| inputlookup mitre_coverage_lookup
| stats avg(score) as avg_score count(eval(score=0)) as no_coverage
    count(eval(score>0 AND score<50)) as partial
    count(eval(score>=50 AND score<75)) as good
    count(eval(score>=75)) as excellent
    count as total
    by tactic
| eval coverage_pct=round((total - no_coverage) / total * 100, 1)
| sort -coverage_pct

Agent Skills: Implementing MITRE ATT&CK Coverage Mapping

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