implementing-vulnerability-management-with-greenbone

name	implementing-vulnerability-management-with-greenbone
description	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. Use when deploying and operate greenbone/openvas vulnerability management using the python-gvm library.
domain	cybersecurity
subdomain	vulnerability-management
tags	["openvas","greenbone","vulnerability-scanning","gmp","python-gvm","vulnerability-management","compliance"]
version	1.0
author	oyi77
license	Apache-2.0
nist_csf	["ID.RA-01","ID.RA-02","ID.IM-02","ID.RA-06"]

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

Trigger phrases:

• "implementing vulnerability management with greenbone"

• "Deploy and operate Greenbone/OpenVAS vulnerability management using the python-g"

• 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

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text)  k, v  IOC_PATTERNS.items()}