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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
"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
| 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