xuansenpa1/skillrevise/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 xuansenpa1/skillrevise/cvss-score-extraction

SKILL.md

The same SKILL.md was published earlier as benchflow-ai/skillsbench/cvss-score-extraction.

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
  1. NVD (National Vulnerability Database)
  • Maintained by NIST (U.S. government)
  • Most authoritative source
  • Priority: Highest
  1. GHSA (GitHub Security Advisory)
  • Community-driven vulnerability database
  • Strong for open-source packages
  • Priority: Medium
  1. 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:

json
{
"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
python
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
python
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
python
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'
python
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
python
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
python
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
python
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

python
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

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

Popularity

Repository stars
56
Repository forks
3
7-day trend score
25

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