Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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": "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,
}
# 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()
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
日本語の概要は準備中です。原文の説明を表示しています。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
日本語の概要は準備中です。原文の説明を表示しています。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
日本語の概要は準備中です。原文の説明を表示しています。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
日本語の概要は準備中です。原文の説明を表示しています。