external/anthropic-cybersecurity-skills/skills/building-vulnerability-dashboard-with-defectdojo/SKILL.md
Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
npx skillsauth add seikaikyo/dash-skills building-vulnerability-dashboard-with-defectdojoInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
tools
需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。
development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
testing
Reference for writing and editing agent skills well — the vocabulary and principles that make a skill predictable. Consult when authoring, reviewing, or pruning a SKILL.md.