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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.

Security & Compliance|v1|Updated 7/14/2026|GitHub source
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# 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.
#mukul-cybersecurity-skills#security#cybersecurity#vulnerability#managementpythonpipgreenbone

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