npx claudepluginhub plurigrid/asi --plugin asiThis skill uses the workspace's default tool permissions.
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 incorporat...
Builds multi-factor asset criticality scoring model (business impact, data sensitivity, regulatory scope, exposure, recoverability) to prioritize vulnerability remediation with tiered SLAs.
Develops multi-factor asset criticality scoring model to prioritize vulnerabilities by business impact, data sensitivity, regulatory scope, and recoverability. Includes Python scorer and SLA adjuster.
Prioritizes vulnerabilities using CVSS v4.0 scoring by calculating scores, interpreting vector strings, and integrating EPSS/CISA KEV for security workflows.
Share bugs, ideas, or general feedback.
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.
| 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 |
| 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 |
| 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 |
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
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