implementing-vulnerability-management-with-greenbone
Deploy and operate Greenbone/OpenVAS vulnerability management using the python-gvm library to create scan targets, execute vulnerability scans, and parse scan reports via GMP protocol.
Best use case
implementing-vulnerability-management-with-greenbone is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Deploy and operate Greenbone/OpenVAS vulnerability management using the python-gvm library to create scan targets, execute vulnerability scans, and parse scan reports via GMP protocol.
Teams using implementing-vulnerability-management-with-greenbone should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/implementing-vulnerability-management-with-greenbone/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How implementing-vulnerability-management-with-greenbone Compares
| Feature / Agent | implementing-vulnerability-management-with-greenbone | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Deploy and operate Greenbone/OpenVAS vulnerability management using the python-gvm library to create scan targets, execute vulnerability scans, and parse scan reports via GMP protocol.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Implementing Vulnerability Management with Greenbone ## Overview Greenbone Vulnerability Management (GVM) is the open-source framework behind OpenVAS, providing comprehensive vulnerability scanning with over 100,000 Network Vulnerability Tests (NVTs). The python-gvm library provides a Python API to interact with GVM through the Greenbone Management Protocol (GMP), enabling programmatic creation of scan targets, task management, scan execution, and report retrieval. This skill covers connecting to GVM via Unix socket or TLS, authenticating, creating scan configs and targets, launching scans, and parsing XML-based vulnerability reports to produce actionable findings. ## When to Use - When deploying or configuring implementing vulnerability management with greenbone 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 - Greenbone Community Edition or Greenbone Enterprise Appliance installed - Python 3.9+ with `python-gvm` (`pip install python-gvm`) - GMP access credentials (username/password) - Network connectivity to GVM daemon (Unix socket or TCP/TLS) - Understanding of CVSS scoring and vulnerability classification ## Steps 1. Install python-gvm: `pip install python-gvm` 2. Establish a GMP connection via `UnixSocketConnection` or `TLSConnection` 3. Authenticate with `gmp.authenticate(username, password)` 4. Create a target with `gmp.create_target(name, hosts=[...], port_list_id=...)` 5. Create a scan task with `gmp.create_task(name, config_id, target_id, scanner_id)` 6. Start the scan with `gmp.start_task(task_id)` 7. Monitor scan progress with `gmp.get_task(task_id)` 8. Retrieve results with `gmp.get_report(report_id, report_format_id=...)` 9. Parse the XML report for vulnerabilities, CVSS scores, and affected hosts 10. Generate a JSON summary report with severity distribution and remediation priorities ## Expected Output A JSON report containing total vulnerabilities found, severity breakdown (critical/high/medium/low), per-host findings with CVE references and CVSS scores, and scan metadata including duration and NVT feed version.
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