building-vulnerability-dashboard-with-defectdojo

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/building-vulnerability-dashboard-with-defectdojo
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summary

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

skill.md
name
building-vulnerability-dashboard-with-defectdojo
description
Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
domain
cybersecurity
subdomain
vulnerability-management
tags
- defectdojo - vulnerability-management - dashboard - deduplication - scanner-integration - devsecops - jira
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- ID.RA-01 - ID.RA-02 - ID.IM-02 - ID.RA-06

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.

When to Use

  • When deploying or configuring building vulnerability dashboard with defectdojo capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

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

# 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

# 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

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

# 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)

ScannerType StringFormat
NessusNessus ScanCSV/XML
OpenVASOpenVAS CSVCSV
QualysQualys ScanXML
OWASP ZAPZAP ScanXML/JSON
Burp SuiteBurp XMLXML
TrivyTrivy ScanJSON
SemgrepSemgrep JSON ReportJSON
SnykSnyk ScanJSON
SonarQubeSonarQube ScanJSON
CheckovCheckov ScanJSON

CI/CD Integration (GitHub Actions)

# .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

# 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,
}

Metrics and Dashboards

Key Metrics API Queries

# 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

how to use building-vulnerability-dashboard-with-defectdojo

How to use building-vulnerability-dashboard-with-defectdojo on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add building-vulnerability-dashboard-with-defectdojo
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/building-vulnerability-dashboard-with-defectdojo

The skills CLI fetches building-vulnerability-dashboard-with-defectdojo from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/building-vulnerability-dashboard-with-defectdojo

Reload or restart Cursor to activate building-vulnerability-dashboard-with-defectdojo. Access the skill through slash commands (e.g., /building-vulnerability-dashboard-with-defectdojo) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.553 reviews
  • Charlotte Chen· Dec 28, 2024

    building-vulnerability-dashboard-with-defectdojo fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ganesh Mohane· Dec 16, 2024

    Keeps context tight: building-vulnerability-dashboard-with-defectdojo is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Noah Torres· Dec 16, 2024

    building-vulnerability-dashboard-with-defectdojo has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ama Perez· Nov 23, 2024

    building-vulnerability-dashboard-with-defectdojo reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Fatima Verma· Nov 19, 2024

    Registry listing for building-vulnerability-dashboard-with-defectdojo matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sakshi Patil· Nov 7, 2024

    building-vulnerability-dashboard-with-defectdojo has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Abebe· Nov 7, 2024

    Keeps context tight: building-vulnerability-dashboard-with-defectdojo is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Oct 26, 2024

    Solid pick for teams standardizing on skills: building-vulnerability-dashboard-with-defectdojo is focused, and the summary matches what you get after install.

  • Hiroshi Malhotra· Oct 26, 2024

    building-vulnerability-dashboard-with-defectdojo is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Hana Li· Oct 14, 2024

    Registry listing for building-vulnerability-dashboard-with-defectdojo matched our evaluation — installs cleanly and behaves as described in the markdown.

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