Wardn Hub
MCP ServersSkillsCategoriesAPI docsSubmit server
Submit server
Wardn HubTrusted MCP server directory.

Registry

  • MCP Servers
  • Skills
  • Categories

Resources

  • API docs
  • Score method

Contribute

  • Submit server
  • Advertise
© 2026 Wardn Hub
Wardn Hub
MCP ServersSkillsCategoriesAPI docsSubmit server
Submit server
skills/benchflow-ai/skillsbench/tasks-software-dependency-audit-environment-skills-cvss-score-extraction

cvss-score-extraction

1
benchflow-ai/skillsbench·Security·Audit passed·Snapshot 89c52f9237c4

Summary

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.

SKILL.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 RangeSeverity LevelDescription
0.0NoneNo impact
0.1-3.9LowMinimal impact
4.0-6.9MediumModerate impact
7.0-8.9HighSignificant impact
9.0-10.0CriticalSevere 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

Installs
0

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:

    NVD → GHSA → RedHat → N/A
    

    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:

    {
      "VulnerabilityID": "CVE-2021-44906",
      "PkgName": "minimist",
      "Severity": "CRITICAL",
      "CVSS": {
        "nvd": {
          "V2Vector": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
          "V3Vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
          "V2Score": 7.5,
          "V3Score": 9.8
        },
        "ghsa": {
          "V3Vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
          "V3Score": 9.8
        }
      }
    }
    

    Python Implementation

    Basic Score Extraction

    def get_cvss_score(vuln_data):
        """
        Extract CVSS v3 score from vulnerability data.
        Uses priority: NVD > GHSA > RedHat
        
        Args:
            vuln_data: Dictionary containing vulnerability information
            
        Returns:
            CVSS v3 score as float, or 'N/A' if not available
        """
        cvss = vuln_data.get('CVSS', {})
        
        # Priority 1: NVD (National Vulnerability Database)
        if 'nvd' in cvss:
            score = cvss['nvd'].get('V3Score')
            if score is not None:
                return score
        
        # Priority 2: GHSA (GitHub Security Advisory)
        if 'ghsa' in cvss:
            score = cvss['ghsa'].get('V3Score')
            if score is not None:
                return score
        
        # Priority 3: RedHat
        if 'redhat' in cvss:
            score = cvss['redhat'].get('V3Score')
            if score is not None:
                return score
        
        # No score available
        return 'N/A'
    

    Enhanced Version with V2 Fallback

    def get_cvss_score_with_fallback(vuln_data):
        """
        Extract CVSS score with v2 fallback.
        Priority: NVD v3 > GHSA v3 > RedHat v3 > NVD v2 > N/A
        """
        cvss = vuln_data.get('CVSS', {})
        
        # Try v3 scores first
        for source in ['nvd', 'ghsa', 'redhat']:
            if source in cvss:
                v3_score = cvss[source].get('V3Score')
                if v3_score is not None:
                    return {'score': v3_score, 'version': 'v3', 'source': source}
        
        # Fallback to v2 if v3 not available
        if 'nvd' in cvss:
            v2_score = cvss['nvd'].get('V2Score')
            if v2_score is not None:
                return {'score': v2_score, 'version': 'v2', 'source': 'nvd'}
        
        return {'score': 'N/A', 'version': None, 'source': None}
    

    Usage in Report Generation

    Integrating CVSS Extraction

    import json
    
    def parse_vulnerabilities(json_file):
        """Parse Trivy JSON and extract vulnerabilities with CVSS scores."""
        with open(json_file, 'r') as f:
            data = json.load(f)
        
        vulnerabilities = []
        
        if 'Results' in data:
            for result in data['Results']:
                for vuln in result.get('Vulnerabilities', []):
                    # Extract basic fields
                    record = {
                        'Package': vuln.get('PkgName'),
                        'Version': vuln.get('InstalledVersion'),
                        'CVE_ID': vuln.get('VulnerabilityID'),
                        'Severity': vuln.get('Severity'),
                        'CVSS_Score': get_cvss_score(vuln),  # Use extraction function
                        'Fixed_Version': vuln.get('FixedVersion', 'N/A'),
                        'Title': vuln.get('Title', 'No description')
                    }
                    vulnerabilities.append(record)
        
        return vulnerabilities
    

    Common Patterns

    Pattern 1: Numeric Score or 'N/A'

    cvss_score = get_cvss_score(vuln)
    # Returns: 9.8 or 'N/A'
    

    Use case: Simple reports where missing scores are acceptable

    Pattern 2: Score with Metadata

    cvss_info = get_cvss_score_with_fallback(vuln)
    # Returns: {'score': 9.8, 'version': 'v3', 'source': 'nvd'}
    

    Use case: Detailed reports showing data provenance

    Pattern 3: Filtering by Score Threshold

    def is_high_severity(vuln_data, threshold=7.0):
        """Check if vulnerability meets severity threshold."""
        score = get_cvss_score(vuln_data)
        if score == 'N/A':
            # If no score, use severity label
            return vuln_data.get('Severity') in ['HIGH', 'CRITICAL']
        return score >= threshold
    

    Error Handling

    Handling Missing Data

    def safe_get_cvss_score(vuln_data):
        """Safely extract CVSS score with comprehensive error handling."""
        try:
            cvss = vuln_data.get('CVSS', {})
            
            # Validate cvss is a dictionary
            if not isinstance(cvss, dict):
                return 'N/A'
            
            for source in ['nvd', 'ghsa', 'redhat']:
                if source in cvss and isinstance(cvss[source], dict):
                    score = cvss[source].get('V3Score')
                    # Validate score is numeric
                    if score is not None and isinstance(score, (int, float)):
                        return score
            
            return 'N/A'
        except (AttributeError, TypeError):
            return 'N/A'
    

    Best Practices

    1. Always provide fallback: Use 'N/A' when scores unavailable
    2. Prefer newer versions: V3 > V2
    3. Respect source hierarchy: NVD is most authoritative
    4. Validate data types: Ensure scores are numeric before using
    5. Document source: In detailed reports, note which source provided the score

    Complete Example

    import json
    
    def get_cvss_score(vuln_data):
        """Extract CVSS v3 score with source priority."""
        cvss = vuln_data.get('CVSS', {})
        
        for source in ['nvd', 'ghsa', 'redhat']:
            if source in cvss:
                score = cvss[source].get('V3Score')
                if score is not None:
                    return score
        
        return 'N/A'
    
    def generate_report_with_cvss(json_file):
        """Generate vulnerability report with CVSS scores."""
        with open(json_file, 'r') as f:
            data = json.load(f)
        
        print(f"{'Package':<20} {'CVE ID':<20} {'CVSS':<8} {'Severity':<10}")
        print("-" * 60)
        
        if 'Results' in data:
            for result in data['Results']:
                for vuln in result.get('Vulnerabilities', []):
                    pkg = vuln.get('PkgName', 'Unknown')
                    cve = vuln.get('VulnerabilityID', 'N/A')
                    cvss = get_cvss_score(vuln)
                    severity = vuln.get('Severity', 'UNKNOWN')
                    
                    print(f"{pkg:<20} {cve:<20} {cvss:<8} {severity:<10}")
    
    # Usage
    generate_report_with_cvss('trivy_report.json')
    

    Dependencies

    Python Modules

    • json (standard library)

    Data Format

    • Expects Trivy JSON format or similar structured vulnerability data

    References

    • CVSS v3.1 Specification
    • NVD CVSS Calculator
    • GitHub Security Advisories

    Related skills

    testing-python13f-analyzerAutomatic Speech Recognition (ASR)Multimodal Fusion for Speaker DiarizationSpeaker Clustering Methods