Agent skill

building-vulnerability-dashboard-with-defectdojo

Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.

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SKILL.md

Building Vulnerability Dashboard with DefectDojo

Overview

DefectDojo is an open-source application vulnerability management platform that aggregates findings from 200+ security tools, deduplicates results, tracks remediation progress, and provides executive dashboards. It serves as a central hub for vulnerability management, integrating with CI/CD pipelines, Jira for ticketing, and Slack for notifications. DefectDojo supports OWASP-based categorization and provides REST API for automation.

Prerequisites

  • Docker and Docker Compose
  • 4GB+ RAM, 2+ CPU cores, 20GB+ disk
  • PostgreSQL 12+ (included in Docker deployment)
  • Python 3.9+ for API integration scripts
  • Jira instance (optional, for ticket integration)

Deployment

Docker Compose Deployment

bash
# Clone DefectDojo repository
git clone https://github.com/DefectDojo/django-DefectDojo.git
cd django-DefectDojo

# Start with Docker Compose (production mode)
./dc-up-d.sh

# Alternative: manual Docker Compose
docker compose up -d

# Check service status
docker compose ps

# View initial admin credentials
docker compose logs initializer 2>&1 | grep "Admin password"

# Access DefectDojo at http://localhost:8080

Environment Configuration

bash
# Key environment variables in docker-compose.yml
DD_DATABASE_ENGINE=django.db.backends.postgresql
DD_DATABASE_HOST=postgres
DD_DATABASE_PORT=5432
DD_DATABASE_NAME=defectdojo
DD_DATABASE_USER=defectdojo
DD_DATABASE_PASSWORD=<secure_password>
DD_ALLOWED_HOSTS=*
DD_SECRET_KEY=<random_64_char_key>
DD_CREDENTIAL_AES_256_KEY=<random_128_bit_key>
DD_SOCIAL_AUTH_GOOGLE_OAUTH2_ENABLED=True

Organizational Structure

Hierarchy

Product Type (Business Unit)
  └── Product (Application/Service)
       └── Engagement (Assessment/Sprint)
            └── Test (Scanner Run)
                 └── Finding (Individual Vulnerability)

Setup via API

python
import requests

DD_URL = "http://localhost:8080/api/v2"
API_KEY = "your_api_key_here"
HEADERS = {"Authorization": f"Token {API_KEY}", "Content-Type": "application/json"}

# Create Product Type
resp = requests.post(f"{DD_URL}/product_types/", headers=HEADERS, json={
    "name": "Web Applications",
    "description": "Customer-facing web application portfolio"
})
product_type_id = resp.json()["id"]

# Create Product
resp = requests.post(f"{DD_URL}/products/", headers=HEADERS, json={
    "name": "Customer Portal",
    "description": "Main customer-facing web application",
    "prod_type": product_type_id,
    "sla_configuration": 1,
})
product_id = resp.json()["id"]

# Create Engagement
resp = requests.post(f"{DD_URL}/engagements/", headers=HEADERS, json={
    "name": "Q1 2024 Security Assessment",
    "product": product_id,
    "target_start": "2024-01-01",
    "target_end": "2024-03-31",
    "engagement_type": "CI/CD",
    "status": "In Progress",
})
engagement_id = resp.json()["id"]

Scanner Integration

Import Scan Results via API

bash
# Upload Nessus scan results
curl -X POST "${DD_URL}/reimport-scan/" \
  -H "Authorization: Token ${API_KEY}" \
  -F "scan_type=Nessus Scan" \
  -F "file=@nessus_report.csv" \
  -F "product_name=Customer Portal" \
  -F "engagement_name=Q1 2024 Security Assessment" \
  -F "auto_create_context=true" \
  -F "deduplication_on_engagement=true"

# Upload OWASP ZAP results
curl -X POST "${DD_URL}/reimport-scan/" \
  -H "Authorization: Token ${API_KEY}" \
  -F "scan_type=ZAP Scan" \
  -F "file=@zap_report.xml" \
  -F "product_name=Customer Portal" \
  -F "engagement_name=Q1 2024 Security Assessment" \
  -F "auto_create_context=true"

# Upload Trivy container scan
curl -X POST "${DD_URL}/reimport-scan/" \
  -H "Authorization: Token ${API_KEY}" \
  -F "scan_type=Trivy Scan" \
  -F "file=@trivy_results.json" \
  -F "product_name=Customer Portal" \
  -F "engagement_name=Q1 2024 Security Assessment" \
  -F "auto_create_context=true"

Supported Scanner Types (Partial List)

Scanner Type String Format
Nessus Nessus Scan CSV/XML
OpenVAS OpenVAS CSV CSV
Qualys Qualys Scan XML
OWASP ZAP ZAP Scan XML/JSON
Burp Suite Burp XML XML
Trivy Trivy Scan JSON
Semgrep Semgrep JSON Report JSON
Snyk Snyk Scan JSON
SonarQube SonarQube Scan JSON
Checkov Checkov Scan JSON

CI/CD Integration (GitHub Actions)

yaml
# .github/workflows/security-scan.yml
name: Security Scan
on: [push]
jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run Semgrep
        run: |
          pip install semgrep
          semgrep --config auto --json -o semgrep_results.json .
      - name: Upload to DefectDojo
        run: |
          curl -X POST "${{ secrets.DD_URL }}/api/v2/reimport-scan/" \
            -H "Authorization: Token ${{ secrets.DD_API_KEY }}" \
            -F "scan_type=Semgrep JSON Report" \
            -F "file=@semgrep_results.json" \
            -F "product_name=${{ github.event.repository.name }}" \
            -F "engagement_name=CI/CD" \
            -F "auto_create_context=true"

Jira Integration

python
# Configure Jira integration in DefectDojo settings
jira_config = {
    "url": "https://company.atlassian.net",
    "username": "jira-bot@company.com",
    "password": "jira_api_token",
    "default_issue_type": "Bug",
    "critical_mapping_severity": "Blocker",
    "high_mapping_severity": "Critical",
    "medium_mapping_severity": "Major",
    "low_mapping_severity": "Minor",
    "finding_text": "**Vulnerability**: {{ finding.title }}\n**Severity**: {{ finding.severity }}\n**CVE**: {{ finding.cve }}\n**Description**: {{ finding.description }}",
    "accepted_mapping_resolution": "Done",
    "close_status_key": 6,
}

Metrics and Dashboards

Key Metrics API Queries

python
# Get finding counts by severity
resp = requests.get(f"{DD_URL}/findings/?limit=0&active=true",
                    headers=HEADERS)
findings = resp.json()

# Get SLA breach counts
resp = requests.get(f"{DD_URL}/findings/?limit=0&active=true&sla_breached=true",
                    headers=HEADERS)

# Get product-level metrics
resp = requests.get(f"{DD_URL}/products/{product_id}/",
                    headers=HEADERS)
product_data = resp.json()

References

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