Files
mukul975 efca3ec611 feat: add NIST CSF 2.0 nist_csf field to all 754 cybersecurity skills
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions)
based on subdomain and content analysis. Restores 11 skills corrupted during
prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields.

All 754 skills now carry structured mappings for all 5 security frameworks:
- MITRE ATT&CK (in tags)
- MITRE ATLAS v5.5 (atlas_techniques)
- MITRE D3FEND v1.3 (d3fend_techniques)
- NIST AI RMF 1.0 (nist_ai_rmf)
- NIST CSF 2.0 (nist_csf)
2026-04-06 11:17:40 +02:00

2.8 KiB

name, description, domain, subdomain, tags, version, author, license, nist_csf
name description domain subdomain tags version author license nist_csf
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. cybersecurity vulnerability-management
openvas
greenbone
vulnerability-scanning
gmp
python-gvm
vulnerability-management
compliance
1.0 mahipal Apache-2.0
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

  • 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.