Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add 26zl/cybersec-toolkit --skill building-vulnerability-dashboard-with-defectdojogit clone --depth 1 https://github.com/26zl/cybersec-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/26zl/cybersec-toolkit/building-vulnerability-dashboard-with-defectdojo)<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/building-vulnerability-dashboard-with-defectdojo"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/building-vulnerability-dashboard-with-defectdojo/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/building-vulnerability-dashboard-with-defectdojo"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/building-vulnerability-dashboard-with-defectdojo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 109 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 116 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 125 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.02001 |
| Opus 5 | $0.00018 | $0.01001 |
| Sonnet 5 | $0.00007 | $0.00400 |
| Haiku 4.5 | $0.00004 | $0.00200 |
Grade A, and why
building-vulnerability-dashboard-with-defectdojo scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
resp = requests.post(f"{DD_URL}/product_types/", headers=HEADERS, json={ Copies of this mod
2 near-identical copies found in the catalogue:
- building-vulnerability-dashboard-with-defectdojo — 91% identical, 31 lines differ
- building-vulnerability-dashboard-with-defectdojo — 86% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 253 lines · 37 tokens per session scan A ffac7a59f453
building-vulnerability-dashboard-with-defectdojo is a skill published in the GitHub repository 26zl/cybersec-toolkit (54 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 2,001 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
building-vulnerability-dashboard-with-defectdojo
Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
building-vulnerability-dashboard-with-defectdojo
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…
building-vulnerability-dashboard-with-defectdojo
Deploy DefectDojo as a centralized vulnerability management dashboard with scanner integrations, deduplication, metrics tracking, and Jira ticketing workflows.
integrating-sast-into-github-actions-pipeline
This skill covers integrating Static Application Security Testing (SAST) tools—CodeQL and Semgrep—into GitHub Actions CI/CD pipelines. It addresses configuring automated code scanning on pull requests and pushes, tuning rules to reduce false positives, uploading SARIF results to GitHub Advanced Security, and…
scanning-containers-with-trivy-in-cicd
This skill covers integrating Aqua Security's Trivy scanner into CI/CD pipelines for comprehensive container image vulnerability detection. It addresses scanning Docker images for OS package and application dependency CVEs, detecting misconfigurations in Dockerfiles, scanning filesystem and git repositories, and…
scanning-kubernetes-manifests-with-kubesec
Perform security risk analysis on Kubernetes resource manifests using Kubesec to identify misconfigurations, privilege escalation risks, and deviations from security best practices.