skills/building-vulnerability-dashboard-with-defectdojo/SKILL.md
Deploy DefectDojo as a centralized vulnerability management dashboard that ingests findings from 200+ security scanners, deduplicates results, tracks remediation metrics, and integrates with CI/CD, Jira ticketing, and Slack notifications via its REST API. Use when consolidating scanner output into one dashboard or automating vulnerability ticketing and executive reporting.
npx skillsauth add mukul975/cyber-skills building-vulnerability-dashboard-with-defectdojoInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
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.
# 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
# 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
Product Type (Business Unit)
└── Product (Application/Service)
└── Engagement (Assessment/Sprint)
└── Test (Scanner Run)
└── Finding (Individual Vulnerability)
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"]
# 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 ${API_KEY}" \
-F "scan_type=Trivy Scan" \
-F "file=@trivy_results.json" \
-F "product_name=Customer Portal" \
-F "engagement_name=Q1 2024 Security Assessment" \
-F "auto_create_context=true"
| Scanner | Type String | Format | |---------|------------|--------| | Nessus | Nessus Scan | CSV/XML | | OpenVAS | OpenVAS CSV | CSV | | Qualys | Qualys Scan | XML | | OWASP ZAP | ZAP Scan | XML/JSON | | Burp Suite | Burp XML | XML | | Trivy | Trivy Scan | JSON | | Semgrep | Semgrep JSON Report | JSON | | Snyk | Snyk Scan | JSON | | SonarQube | SonarQube Scan | JSON | | Checkov | Checkov Scan | JSON |
# .github/workflows/security-scan.yml
name: Security Scan
on: [push]
jobs:
scan:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Run Semgrep
run: |
pip install semgrep
semgrep --config auto --json -o semgrep_results.json .
- name: Upload to DefectDojo
run: |
curl -X POST "${{ 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"
# Configure Jira integration in DefectDojo settings
jira_config = {
"url": "https://company.atlassian.net",
"username": "[email protected]",
"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,
}
# 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()
development
Detect Pass-the-Hash (T1550.002) attacks by analyzing NTLM authentication patterns, flagging Type 3 logons using NTLM where Kerberos would be expected, and correlating with credential-dumping indicators. Use when threat hunting for lateral movement via stolen NTLM hashes, triaging EDR/SIEM alerts on suspicious NTLM logons, scoping compromise during incident response, or validating detection coverage in a purple team exercise.
testing
Detect and respond to OAuth token theft and replay in Microsoft Entra ID (Azure AD), covering access token theft, refresh token replay, Primary Refresh Token (PRT) abuse, pass-the-cookie attacks, and Token Protection conditional access policies. Use for impossible-travel or anomalous token-usage alerts, suspected session hijacking, sign-in log analysis, or configuring token-binding defenses in Azure/M365.
development
Detect NTLM relay attacks (T1557.001) by correlating Windows Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB/LDAP signing, and flagging NTLMv2-to-NTLMv1 downgrades. Use for hunting credential relay in NTLM-enabled AD, investigating auth-source anomalies, building SIEM correlation rules, or responding to PetitPotam/DFSCoerce/PrinterBug alerts.
data-ai
Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.