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mukul975 cb8d79e068 Map all 754 skills to MITRE ATT&CK v19.1
- Add validated mitre_attack frontmatter to all 754 skills (286 distinct
  techniques), verified against MITRE ATT&CK v19.1 via the official
  mitreattack-python library: 0 revoked, deprecated, or invalid IDs
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  threat-intel, and red-team skills (e.g. DCSync -> T1003.006,
  Kerberoasting -> T1558.003, Pass-the-Ticket -> T1550.003)
- Reconcile v19.1 tactic restructuring: Defense Evasion split into
  Stealth (TA0005) and Defense Impairment (TA0112); revoked T1562.*
  family and T1070.001/.002 remapped to active equivalents (T1685.*)
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6.5 KiB

name, description, domain, subdomain, tags, version, author, license, nist_csf, mitre_attack
name description domain subdomain tags version author license nist_csf mitre_attack
performing-asset-criticality-scoring-for-vulns Develop and apply a multi-factor asset criticality scoring model to weight vulnerability prioritization based on business impact, data sensitivity, and operational importance. cybersecurity vulnerability-management
asset-criticality
vulnerability-prioritization
risk-management
cmdb
business-impact
crown-jewels
asset-classification
1.0 mahipal Apache-2.0
ID.RA-01
ID.RA-02
ID.IM-02
ID.RA-06
T1190
T1203
T1068

Performing Asset Criticality Scoring for Vulns

Overview

Asset criticality scoring assigns a business impact rating to each IT asset so that vulnerability remediation efforts focus on systems with the greatest organizational risk. Without criticality context, a CVSS 9.0 vulnerability on a test server receives the same urgency as the same vulnerability on a payment processing database. This skill covers building a multi-factor scoring model incorporating data sensitivity, business function dependency, regulatory scope, network exposure, and recoverability to create a 1-5 criticality tier that directly modifies vulnerability remediation SLAs.

When to Use

  • When conducting security assessments that involve performing asset criticality scoring for vulns
  • When following incident response procedures for related security events
  • When performing scheduled security testing or auditing activities
  • When validating security controls through hands-on testing

Prerequisites

  • Configuration Management Database (CMDB) or asset inventory
  • Business Impact Analysis (BIA) data
  • Data classification policy
  • Network architecture documentation
  • Stakeholder input from business unit owners

Core Concepts

Asset Criticality Scoring Model

Factor Weight Score Range Description
Business Function Impact 25% 1-5 How critical is the supported business process
Data Sensitivity 25% 1-5 Type and sensitivity of data processed/stored
Regulatory Scope 15% 1-5 Regulatory requirements (PCI, HIPAA, SOX)
Network Exposure 15% 1-5 Internet-facing vs internal-only
Recoverability 10% 1-5 RTO/RPO requirements, DR capability
User Population 10% 1-5 Number of users/customers affected

Criticality Tier Definitions

Tier Score Range Label SLA Modifier Examples
1 4.5-5.0 Crown Jewels -50% SLA Domain controllers, payment systems, ERP
2 3.5-4.4 High Value -25% SLA Email servers, HR systems, CI/CD
3 2.5-3.4 Standard Baseline SLA Internal apps, file servers
4 1.5-2.4 Low Impact +25% SLA Test environments, printers
5 1.0-1.4 Minimal +50% SLA Decommissioning, isolated labs

Data Sensitivity Scoring

Score Classification Examples
5 Restricted/Secret PII, PHI, payment card data, trade secrets
4 Confidential Financial reports, HR records, source code
3 Internal Internal documents, policies, project files
2 Semi-public Marketing materials, press releases (draft)
1 Public Published content, public APIs

Workflow

Step 1: Define Scoring Criteria

class AssetCriticalityScorer:
    """Multi-factor asset criticality scoring engine."""

    WEIGHTS = {
        "business_function": 0.25,
        "data_sensitivity": 0.25,
        "regulatory_scope": 0.15,
        "network_exposure": 0.15,
        "recoverability": 0.10,
        "user_population": 0.10,
    }

    TIER_THRESHOLDS = [
        (4.5, 1, "Crown Jewels", -0.50),
        (3.5, 2, "High Value", -0.25),
        (2.5, 3, "Standard", 0.00),
        (1.5, 4, "Low Impact", 0.25),
        (1.0, 5, "Minimal", 0.50),
    ]

    def score_asset(self, asset):
        """Calculate criticality score for an asset."""
        weighted_score = sum(
            asset.get(factor, 3) * weight
            for factor, weight in self.WEIGHTS.items()
        )
        score = round(weighted_score, 2)

        for threshold, tier, label, sla_mod in self.TIER_THRESHOLDS:
            if score >= threshold:
                return {
                    "score": score,
                    "tier": tier,
                    "label": label,
                    "sla_modifier": sla_mod,
                }
        return {"score": score, "tier": 5, "label": "Minimal", "sla_modifier": 0.50}

    def adjust_vuln_sla(self, base_sla_days, asset_tier_data):
        """Adjust vulnerability SLA based on asset criticality."""
        modifier = asset_tier_data["sla_modifier"]
        adjusted = int(base_sla_days * (1 + modifier))
        return max(1, adjusted)  # Minimum 1 day SLA

Step 2: Integrate with Vulnerability Prioritization

def apply_criticality_to_vulns(vulns_df, asset_scores):
    """Enrich vulnerability data with asset criticality context."""
    for idx, vuln in vulns_df.iterrows():
        asset_id = vuln.get("asset_id", "")
        asset_data = asset_scores.get(asset_id, {"tier": 3, "sla_modifier": 0})

        vulns_df.at[idx, "asset_tier"] = asset_data["tier"]
        vulns_df.at[idx, "asset_label"] = asset_data.get("label", "Standard")

        base_sla = get_base_sla(vuln["severity"])
        adjusted_sla = int(base_sla * (1 + asset_data["sla_modifier"]))
        vulns_df.at[idx, "adjusted_sla_days"] = max(1, adjusted_sla)

    return vulns_df

Best Practices

  1. Involve business stakeholders in criticality scoring; IT alone cannot assess business impact
  2. Review and update criticality scores at least quarterly or when systems change roles
  3. Automate scoring where possible using CMDB tags and data classification labels
  4. Apply criticality tiers to vulnerability SLAs for risk-proportional remediation
  5. Validate scoring against actual incident impact data to calibrate the model
  6. Start with a simple 3-tier model before expanding to 5 tiers

Common Pitfalls

  • Classifying all assets as "critical" which defeats the purpose of tiering
  • Not updating criticality scores when systems are repurposed or decommissioned
  • Using only technical factors without business context
  • Applying uniform SLAs regardless of asset importance
  • Not documenting the scoring methodology for audit and consistency
  • performing-cve-prioritization-with-kev-catalog
  • building-vulnerability-aging-and-sla-tracking
  • performing-business-impact-analysis
  • implementing-asset-management-program