Vulnerability CSV Report Generation Skill

Vulnerability CSV Report Generation

This skill provides guidance on generating structured CSV reports from vulnerability scan data—a common format for security audits and compliance reporting.

Overview

CSV (Comma-Separated Values) is a widely-used format for security reports because it's:

Human-readable: Can be opened in Excel, Google Sheets
Machine-parseable: Easy to process programmatically
Universal: Supported by all data analysis tools
Lightweight: Smaller than JSON/XML formats

When to Use CSV Reports

Ideal Use Cases

Compliance audits requiring tabular data
Executive summaries for non-technical stakeholders
Integration with ticketing systems (Jira, ServiceNow)
Automated vulnerability tracking pipelines
Data analysis in spreadsheet tools

Limitations

No hierarchical data (flat structure only)
Limited support for nested information
No standard for binary data

Alternative formats: JSON (for APIs), PDF (for formal reports), HTML (for dashboards)

CSV Schema Design for Security Reports

Essential Fields

A well-designed vulnerability report CSV should include:

| Field | Type | Description | Example | |-------|------|-------------|---------| | Package | String | Vulnerable package name | express | | Version | String | Installed version | 4.17.1 | | CVE_ID | String | Vulnerability identifier | CVE-2022-24999 | | Severity | Enum | Risk level | CRITICAL, HIGH | | CVSS_Score | Float/String | Numeric severity score | 9.8 or N/A | | Fixed_Version | String | Patched version | 4.18.0 or N/A | | Title | String | Brief description | XSS in Express.js | | Url | String | Reference link | https://nvd.nist.gov/... |

Design Principles

Use descriptive column names: Package not pkg, CVE_ID not id
Handle missing data: Use N/A for unavailable fields, not empty strings
Consistent data types: Ensure all rows have same format
Include metadata: Consider adding scan date, target, tool version

Python CSV Generation with DictWriter

Why DictWriter?

Python's csv.DictWriter is ideal for structured reports:

Type-safe: Column names defined upfront
Readable: Use dictionary keys instead of indices
Maintainable: Easy to add/remove columns
Automatic header generation: No manual header writing

Basic Usage

import csv

# Define schema
headers = ["Package", "Version", "CVE_ID", "Severity", "CVSS_Score", 
           "Fixed_Version", "Title", "Url"]

# Prepare data
vulnerabilities = [
    {
        "Package": "minimist",
        "Version": "1.2.5",
        "CVE_ID": "CVE-2021-44906",
        "Severity": "CRITICAL",
        "CVSS_Score": 9.8,
        "Fixed_Version": "1.2.6",
        "Title": "Prototype Pollution",
        "Url": "https://avd.aquasec.com/nvd/cve-2021-44906"
    }
]

# Write CSV
with open('security_audit.csv', 'w', newline='', encoding='utf-8') as f:
    writer = csv.DictWriter(f, fieldnames=headers)
    writer.writeheader()  # Write column names
    writer.writerows(vulnerabilities)  # Write all rows

Important parameters:

newline='': Prevents extra blank lines on Windows
encoding='utf-8': Handles special characters in descriptions

Severity-Based Filtering

Why Filter by Severity?

Security teams prioritize based on risk. Filtering ensures reports focus on critical issues:

| Severity | Action Required | Typical SLA | |----------|----------------|-------------| | CRITICAL | Immediate patch | 24 hours | | HIGH | Urgent patch | 7 days | | MEDIUM | Scheduled patch | 30 days | | LOW | Optional patch | 90 days |

Implementation

def filter_high_severity(vulnerabilities, min_severity=['HIGH', 'CRITICAL']):
    """
    Filter vulnerabilities by severity level.
    
    Args:
        vulnerabilities: List of vulnerability dictionaries
        min_severity: List of severity levels to include
        
    Returns:
        Filtered list containing only specified severity levels
    """
    filtered = []
    for vuln in vulnerabilities:
        if vuln.get('Severity') in min_severity:
            filtered.append(vuln)
    return filtered

# Usage
all_vulns = [...]  # From scanner
critical_vulns = filter_high_severity(all_vulns, ['CRITICAL', 'HIGH'])

Field Mapping from JSON to CSV

Extracting Fields from Scanner Output

import json

def parse_trivy_json_to_csv_records(json_file):
    """
    Parse Trivy JSON output and extract CSV-ready records.
    
    Returns list of dictionaries, one per vulnerability.
    """
    with open(json_file, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    records = []
    
    if 'Results' in data:
        for result in data['Results']:
            target = result.get('Target', 'Unknown')
            
            for vuln in result.get('Vulnerabilities', []):
                # Map JSON fields to CSV fields
                record = {
                    "Package": vuln.get('PkgName'),
                    "Version": vuln.get('InstalledVersion'),
                    "CVE_ID": vuln.get('VulnerabilityID'),
                    "Severity": vuln.get('Severity', 'UNKNOWN'),
                    "CVSS_Score": extract_cvss_score(vuln),
                    "Fixed_Version": vuln.get('FixedVersion', 'N/A'),
                    "Title": vuln.get('Title', 'No description'),
                    "Url": vuln.get('PrimaryURL', '')
                }
                records.append(record)
    
    return records

def extract_cvss_score(vuln):
    """Extract CVSS score (from cvss-score-extraction skill)."""
    cvss = vuln.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'

Complete Vulnerability CSV Report Generator

import json
import csv
import sys

def generate_vulnerability_csv_report(
    json_input, 
    csv_output, 
    severity_filter=['HIGH', 'CRITICAL']
):
    """
    Generate filtered CSV security report from Trivy JSON output.
    
    Args:
        json_input: Path to Trivy JSON report
        csv_output: Path for output CSV file
        severity_filter: List of severity levels to include
    """
    # Read JSON
    try:
        with open(json_input, 'r', encoding='utf-8') as f:
            data = json.load(f)
    except FileNotFoundError:
        print(f"[!] Error: Could not find {json_input}")
        sys.exit(1)
    
    # Extract and filter vulnerabilities
    vulnerabilities = []
    
    if 'Results' in data:
        for result in data['Results']:
            for vuln in result.get('Vulnerabilities', []):
                severity = vuln.get('Severity', 'UNKNOWN')
                
                # Apply severity filter
                if severity in severity_filter:
                    vulnerabilities.append({
                        "Package": vuln.get('PkgName'),
                        "Version": vuln.get('InstalledVersion'),
                        "CVE_ID": vuln.get('VulnerabilityID'),
                        "Severity": severity,
                        "CVSS_Score": get_cvss_score(vuln),
                        "Fixed_Version": vuln.get('FixedVersion', 'N/A'),
                        "Title": vuln.get('Title', 'No description'),
                        "Url": vuln.get('PrimaryURL', '')
                    })
    
    # Write CSV
    if vulnerabilities:
        headers = ["Package", "Version", "CVE_ID", "Severity", 
                   "CVSS_Score", "Fixed_Version", "Title", "Url"]
        
        with open(csv_output, 'w', newline='', encoding='utf-8') as f:
            writer = csv.DictWriter(f, fieldnames=headers)
            writer.writeheader()
            writer.writerows(vulnerabilities)
        
        print(f"\n[SUCCESS] Found {len(vulnerabilities)} "
              f"{'/'.join(severity_filter)} vulnerabilities")
        print(f"[SUCCESS] Report saved to: {csv_output}")
    else:
        print(f"\n[SUCCESS] No {'/'.join(severity_filter)} vulnerabilities found")

def get_cvss_score(vuln_data):
    """Extract CVSS 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'

# Usage
if __name__ == "__main__":
    generate_vulnerability_csv_report(
        json_input='trivy_report.json',
        csv_output='security_audit.csv',
        severity_filter=['CRITICAL', 'HIGH']
    )

Advanced Patterns

Pattern 1: Adding Metadata Row

import csv
from datetime import datetime

# Add metadata as first row
metadata = {
    "Package": f"Scan Date: {datetime.now().isoformat()}",
    "Version": "Tool: Trivy v0.40.0",
    "CVE_ID": "Target: package-lock.json",
    "Severity": "", "CVSS_Score": "", "Fixed_Version": "", 
    "Title": "", "Url": ""
}

with open('report.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=headers)
    writer.writeheader()
    writer.writerow(metadata)  # Metadata row
    writer.writerow({})  # Blank separator
    writer.writerows(vulnerabilities)  # Actual data

Pattern 2: Multi-Target Reports

def generate_multi_target_report(json_input, csv_output):
    """Include target/file name in each row."""
    with open(json_input, 'r') as f:
        data = json.load(f)
    
    vulnerabilities = []
    
    for result in data.get('Results', []):
        target = result.get('Target', 'Unknown')
        
        for vuln in result.get('Vulnerabilities', []):
            record = {
                "Target": target,  # Add target column
                "Package": vuln.get('PkgName'),
                # ... other fields
            }
            vulnerabilities.append(record)
    
    headers = ["Target", "Package", "Version", ...]  # Target first
    # Write CSV as before

Pattern 3: Summary Statistics

def print_report_summary(vulnerabilities):
    """Print summary before writing CSV."""
    from collections import Counter
    
    severity_counts = Counter(v['Severity'] for v in vulnerabilities)
    
    print("\nVulnerability Summary:")
    print(f"  CRITICAL: {severity_counts.get('CRITICAL', 0)}")
    print(f"  HIGH:     {severity_counts.get('HIGH', 0)}")
    print(f"  Total:    {len(vulnerabilities)}")

Error Handling

Handling Missing or Malformed Data

def safe_get_field(vuln, field, default='N/A'):
    """Safely extract field with default fallback."""
    value = vuln.get(field, default)
    # Ensure value is not None
    return value if value is not None else default

# Usage in field mapping
record = {
    "Package": safe_get_field(vuln, 'PkgName', 'Unknown'),
    "Fixed_Version": safe_get_field(vuln, 'FixedVersion', 'N/A'),
    # ...
}

Best Practices

Always write headers: Makes CSV self-documenting
Use UTF-8 encoding: Handles international characters
Set newline='': Prevents blank lines on Windows
Validate data: Check for None/null values before writing
Add timestamp: Include scan date for tracking
Document schema: Maintain a data dictionary
Test with edge cases: Empty results, missing fields

Agent Skills: Vulnerability CSV Report Generation

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