external/anthropic-cybersecurity-skills/skills/implementing-vulnerability-management-with-greenbone/SKILL.md
Deploy and operate Greenbone/OpenVAS vulnerability management using the python-gvm library over the Greenbone Management Protocol (GMP) to connect via Unix socket or TLS, create scan targets and configs, execute scans, and parse the XML scan reports into actionable findings. Use when automating OpenVAS/GVM scan creation and execution, or programmatically retrieving and parsing vulnerability scan reports.
npx skillsauth add seikaikyo/dash-skills implementing-vulnerability-management-with-greenboneInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
python-gvm (pip install python-gvm)pip install python-gvmUnixSocketConnection or TLSConnectiongmp.authenticate(username, password)gmp.create_target(name, hosts=[...], port_list_id=...)gmp.create_task(name, config_id, target_id, scanner_id)gmp.start_task(task_id)gmp.get_task(task_id)gmp.get_report(report_id, report_format_id=...)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.
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.