benchflow-ai/skillsbench/cvss-score-extraction
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Extract CVSS (Common Vulnerability Scoring System) scores from vulnerability data sources with proper fallback handling. This skill covers understanding CVSS v3, handling multiple score sources (NVD, GHSA, RedHat), implementing source priority logic, and dealing with missing scores in security reporting.
Install
npx vskill@latest install benchflow-ai/skillsbench/cvss-score-extractionSKILL.md
CVSS Score Extraction from Vulnerability Data
This skill provides guidance on extracting CVSS scores from vulnerability data—a critical component of security report generation.
Overview
CVSS (Common Vulnerability Scoring System) provides a standardized way to assess the severity of security vulnerabilities. When generating security reports, extracting the correct CVSS score from multiple data sources is essential for accurate risk assessment.
What is CVSS?
CVSS Scoring System
CVSS assigns a numerical score (0.0-10.0) representing vulnerability severity:
| Score Range | Severity Level | Description | |
|---|---|---|---|
| 0.0 | None | No impact | |
| 0.1-3.9 | Low | Minimal impact | |
| 4.0-6.9 | Medium | Moderate impact | |
| 7.0-8.9 | High | Significant impact | |
| 9.0-10.0 | Critical | Severe impact |
CVSS Versions
- CVSS v2: Legacy scoring system (0-10 scale)
- CVSS v3: Current standard with refined metrics
- CVSS v3.1: Minor refinement of v3
Best Practice: Prefer CVSS v3/v3.1 scores when available.
Multiple Vulnerability Data Sources
Vulnerability scanners often aggregate data from multiple sources, each providing their own CVSS assessment:
Common Sources
- NVD (National Vulnerability Database)
- Maintained by NIST (U.S. government)
- Most authoritative source
- Priority: Highest
- GHSA (GitHub Security Advisory)
- Community-driven vulnerability database
- Strong for open-source packages
- Priority: Medium
- RedHat Security Data
- RedHat's security team assessments
- Focused on enterprise Linux ecosystem
- Priority: Lower
Why Multiple Sources?
- Not all sources have scores for every CVE
- Scores may differ based on interpretation
- Need fallback logic when primary source unavailable
Source Priority Strategy
When multiple sources provide scores, use a priority cascade:
Rationale: NVD is the most comprehensive and authoritative, followed by community sources, then vendor-specific databases.
Data Structure
Trivy (and similar tools) return CVSS data in nested format:
Python Implementation
Basic Score Extraction
Enhanced Version with V2 Fallback
Usage in Report Generation
Integrating CVSS Extraction
Common Patterns
Pattern 1: Numeric Score or 'N/A'
Use case: Simple reports where missing scores are acceptable
Pattern 2: Score with Metadata
Use case: Detailed reports showing data provenance
Pattern 3: Filtering by Score Threshold
Error Handling
Handling Missing Data
Best Practices
- Always provide fallback: Use 'N/A' when scores unavailable
- Prefer newer versions: V3 > V2
- Respect source hierarchy: NVD is most authoritative
- Validate data types: Ensure scores are numeric before using
- Document source: In detailed reports, note which source provided the score
Complete Example
Dependencies
Python Modules
json(standard library)
Data Format
- Expects Trivy JSON format or similar structured vulnerability data
References
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingtasks/software-dependency-audit/environment/skills/cvss-score-extraction/SKILL.md
Popularity
- Repository stars
- 1,474
- Repository forks
- 325
- 7-day trend score
- 36
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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