[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71GESEQT45924AS7P9VNVC7":3,"skill-same:01M71GESEQT45924AS7P9VNVC7":107},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":14,"repositoryHtmlUrl":47,"repositoryHomepageUrl":6,"ownerHtmlUrl":48,"ownerBlogUrl":6,"ownerDescription":49,"updatedAt":50,"install":51,"resources":64},"01M71GESEQT45924AS7P9VNVC7","SKILL.md-",null,">\n  Deploy and operate Greenbone\u002FOpenVAS vulnerability management using the python-gvm library to create scan targets, execute vulnerability scans, and parse scan reports via GMP protocol.","DCx7C5\u002Fai-marketplace","DCx7C5","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42419559?v=4","01M71C01G2AZV3NTNGWAWSHJPP","DC","01M71C01GQW6G50S2BYMS7PP3E",0,"MIT","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"skill md","targets","deploy","library","execute","python-gvm","gmp","protocol","greenbone","openvas","via","create","reports","gvm","vulnerability","python","scan","parse","vulnerability management","operate","2026-11-10 10:12:30",false,"---\nname: SKILL.md-\ndescription: \">\\n  Deploy and operate Greenbone\u002FOpenVAS vulnerability management using\\\n  \\ the python-gvm library to create scan targets, execute vulnerability scans, and\\\n  \\ parse scan reports via GMP protocol.\"\n---\n# Implementing Vulnerability Management with Greenbone\n\n## Overview\n\nGreenbone 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.\n\n\n## When to Use\n\n- When deploying or configuring implementing vulnerability management with greenbone capabilities in your environment\n- When establishing security controls aligned to compliance requirements\n- When building or improving security architecture for this domain\n- When conducting security assessments that require this implementation\n\n## Prerequisites\n\n- Greenbone Community Edition or Greenbone Enterprise Appliance installed\n- Python 3.9+ with `python-gvm` (`pip install python-gvm`)\n- GMP access credentials (username\u002Fpassword)\n- Network connectivity to GVM daemon (Unix socket or TCP\u002FTLS)\n- Understanding of CVSS scoring and vulnerability classification\n\n## Steps\n\n1. Install python-gvm: `pip install python-gvm`\n2. Establish a GMP connection via `UnixSocketConnection` or `TLSConnection`\n3. Authenticate with `gmp.authenticate(username, password)`\n4. Create a target with `gmp.create_target(name, hosts=[...], port_list_id=...)`\n5. Create a scan task with `gmp.create_task(name, config_id, target_id, scanner_id)`\n6. Start the scan with `gmp.start_task(task_id)`\n7. Monitor scan progress with `gmp.get_task(task_id)`\n8. Retrieve results with `gmp.get_report(report_id, report_format_id=...)`\n9. Parse the XML report for vulnerabilities, CVSS scores, and affected hosts\n10. Generate a JSON summary report with severity distribution and remediation priorities\n\n## Expected Output\n\nA JSON report containing total vulnerabilities found, severity breakdown (critical\u002Fhigh\u002Fmedium\u002Flow), per-host findings with CVE references and CVSS scores, and scan metadata including duration and NVT feed version.\n\n\n---\n\n## CyberSecSuite Integration\n\n```bash\n# Open a case before starting investigation\nmcp__cybersec__case_open --title \"vulnerability\" --type investigation\n\n# Persist findings to PostgreSQL\nmcp__cybersec__add_finding --title \"...\" --severity high --description \"...\"\n\n# Log IOCs\nmcp__cybersec__add_ioc --type domain --value \"...\" --confidence 0.9\n\n# Map to MITRE\nmcp__cybersec__suggest_mitre --description \"...\"\n```\n\n**Agent:** `@cybersec-agent` → delegates to appropriate specialist\n","# Implementing Vulnerability Management with Greenbone\n\n## Overview\n\nGreenbone 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.\n\n\n## When to Use\n\n- When deploying or configuring implementing vulnerability management with greenbone capabilities in your environment\n- When establishing security controls aligned to compliance requirements\n- When building or improving security architecture for this domain\n- When conducting security assessments that require this implementation\n\n## Prerequisites\n\n- Greenbone Community Edition or Greenbone Enterprise Appliance installed\n- Python 3.9+ with `python-gvm` (`pip install python-gvm`)\n- GMP access credentials (username\u002Fpassword)\n- Network connectivity to GVM daemon (Unix socket or TCP\u002FTLS)\n- Understanding of CVSS scoring and vulnerability classification\n\n## Steps\n\n1. Install python-gvm: `pip install python-gvm`\n2. Establish a GMP connection via `UnixSocketConnection` or `TLSConnection`\n3. Authenticate with `gmp.authenticate(username, password)`\n4. Create a target with `gmp.create_target(name, hosts=[...], port_list_id=...)`\n5. Create a scan task with `gmp.create_task(name, config_id, target_id, scanner_id)`\n6. Start the scan with `gmp.start_task(task_id)`\n7. Monitor scan progress with `gmp.get_task(task_id)`\n8. Retrieve results with `gmp.get_report(report_id, report_format_id=...)`\n9. Parse the XML report for vulnerabilities, CVSS scores, and affected hosts\n10. Generate a JSON summary report with severity distribution and remediation priorities\n\n## Expected Output\n\nA JSON report containing total vulnerabilities found, severity breakdown (critical\u002Fhigh\u002Fmedium\u002Flow), per-host findings with CVE references and CVSS scores, and scan metadata including duration and NVT feed version.\n\n\n---\n\n## CyberSecSuite Integration\n\n```bash\n# Open a case before starting investigation\nmcp__cybersec__case_open --title \"vulnerability\" --type investigation\n\n# Persist findings to PostgreSQL\nmcp__cybersec__add_finding --title \"...\" --severity high --description \"...\"\n\n# Log IOCs\nmcp__cybersec__add_ioc --type domain --value \"...\" --confidence 0.9\n\n# Map to MITRE\nmcp__cybersec__suggest_mitre --description \"...\"\n```\n\n**Agent:** `@cybersec-agent` → delegates to appropriate specialist\n",{"name":5,"description":7},"main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fvuln","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill SKILL.md-",{"tool":57,"command":58},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill SKILL.md-",{"tool":60,"command":61},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill SKILL.md-","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002FSKILL.md",true,[65,71,75,79,83,87,91,94,98,104],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"exploit\u002Findex.json","REFERENCE","参考文档",652,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fexploit\u002Findex.json",{"path":72,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":73,"sourceHtmlUrl":74},"index.json",4700,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Findex.json",{"path":76,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":77,"sourceHtmlUrl":78},"management\u002Findex.json",1274,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fmanagement\u002Findex.json",{"path":80,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":81,"sourceHtmlUrl":82},"prioritization\u002Findex.json",1258,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fprioritization\u002Findex.json",{"path":84,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002Fapi-reference.md",2531,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Freferences\u002Fapi-reference.md",{"path":88,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":89,"sourceHtmlUrl":90},"references\u002Findex.json",84,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Freferences\u002Findex.json",{"path":92,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":81,"sourceHtmlUrl":93},"remediation\u002Findex.json","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fremediation\u002Findex.json",{"path":95,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":96,"sourceHtmlUrl":97},"scanning\u002Findex.json",2426,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fscanning\u002Findex.json",{"path":99,"resourceType":100,"resourceTypeDesc":101,"sizeBytes":102,"sourceHtmlUrl":103},"scripts\u002Fagent.py","SCRIPT","脚本",6040,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fscripts\u002Fagent.py",{"path":105,"resourceType":100,"resourceTypeDesc":101,"sizeBytes":89,"sourceHtmlUrl":106},"scripts\u002Findex.json","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fvuln\u002Fscripts\u002Findex.json",[108,134,157,179,200,216],{"skillNo":109,"name":110,"nameZh":6,"description":111,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":114,"publishedAt":39},"01M71HAPZ01KQ30RKTB0FFSQ05","services-wmi-persistence-detect","Detect WMI event subscription persistence by enumerating ActiveScriptEventConsumer, CommandLineEventConsumer, and permanent subscriptions in the WMI repository.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fpersistence\u002Fdetect\u002FSKILL.md",[],[115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133],"services","detect","services wmi persistence detect","wmi","persistence","de","cm","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","cybersecurity","process-forensics",{"skillNo":135,"name":136,"nameZh":6,"description":137,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":138,"categories":139,"keywords":140,"publishedAt":39},"01M71HAK6JTTTS229T17WJMMCG","services-wmi-exec-exploit","Perform lateral movement across Windows networks using WMI-based remote execution techniques including Impacket wmiexec.py, CrackMapExec, and native WMI commands for stealthy post-exploitation during red team engagements.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fexec\u002Fexploit\u002FSKILL.md",[],[141,115,142,118,143,144,145,132,146,147,148,149,150,151,120,152,153,154,155,156],"exploit","services wmi exec exploit","exec","remote","traffic","Bash","analysis","team","across","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":163,"publishedAt":39},"01M71HAG6MHKNQV8KDZKMT4886","registry-artifact-extract","Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and evidence of system compromise.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fregistry\u002Fartifact\u002Fextract\u002FSKILL.md",[],[164,165,166,167,168,169,132,146,170,147,171,172,120,154,173,174,175,176,177,178],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","analyze","uncover","software","activity","digital-forensics","windows-registry","regripper","sonnet",{"skillNo":180,"name":181,"nameZh":6,"description":182,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":183,"categories":184,"keywords":185,"publishedAt":39},"01M71HACR4A8XTWTTSXK4124AA","processes-token-impersonate-detect","Detect Windows token impersonation and privilege abuse including SeImpersonatePrivilege exploitation via Potato attacks and token stealing techniques.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Ftoken\u002Fimpersonate\u002Fdetect\u002FSKILL.md",[],[116,186,187,188,189,190,191,121,192,132,133,193,194,195,196,197,198,199,29,120],"processes token impersonate detect","token","processes","attacks","windows","escalation","techniques","privilege-escalation","seimpersonate","token-impersonation","printspoofer","exploitation","potato","impersonation",{"skillNo":201,"name":202,"nameZh":6,"description":203,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":204,"categories":205,"keywords":206,"publishedAt":39},"01M71HAABSB4Z6QFSXEG00R4RK","processes-thread-injection-detect","Detect Windows thread injection techniques including CreateRemoteThread, QueueUserAPC, NtCreateThreadEx, and thread hijacking via process memory analysis.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fthread\u002Finjection\u002Fdetect\u002FSKILL.md",[],[207,208,116,209,188,190,210,121,211,192,132,133,147,212,213,214,215,29,120,122],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":217,"name":218,"nameZh":6,"description":219,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":220,"categories":221,"keywords":222,"publishedAt":39},"01M71HA7H311V5G14WMX58HQSS","processes-hollow-technique-detect","Detect process hollowing (RunPE) by identifying processes with mismatched image paths between PEB and VAD tree, or unmapped PE headers in memory.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fhollow\u002Ftechnique\u002Fdetect\u002FSKILL.md",[],[223,116,188,224,210,121,225,226,132,133,227,228,229,230,231,232,120,122,233,234],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","with","mismatched","headers"]