[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M73ES30A6RHRVAB3QDBWSQVX":3,"skill-same:01M73ES30A6RHRVAB3QDBWSQVX":92},{"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":16,"sourceHtmlUrl":17,"categories":18,"keywords":19,"publishedAt":20,"linkOnly":21,"markdownContent":22,"markdownBody":23,"frontMatter":24,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":53,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":56,"updatedAt":57,"install":58,"resources":71},"01M73ES30A6RHRVAB3QDBWSQVX","performing-osint-with-spiderfoot",null,"Automate OSINT collection using SpiderFoot REST API and CLI for target profiling, module-based reconnaissance, and structured result analysis across 200+ data sources","Horonomos-laps\u002FYana-AI","Horonomos-laps","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F355299122?v=4","01M76B3QPXE88ET2SQPDPVATZT"," Horonomos-laps","01M72ZQRJPCYPSSWT4D00VJR2A",13,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fperforming-osint-with-spiderfoot\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fperforming-osint-with-spiderfoot\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: performing-osint-with-spiderfoot\ndescription: Automate OSINT collection using SpiderFoot REST API and CLI for target\n  profiling, module-based reconnaissance, and structured result analysis across 200+\n  data sources\ndomain: cybersecurity\nsubdomain: threat-intelligence\ntags:\n- osint\n- spiderfoot\n- reconnaissance\n- threat-intelligence\n- attack-surface\n- target-profiling\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- ID.RA-01\n- ID.RA-05\n- DE.CM-01\n- DE.AE-02\nmitre_attack:\n- T1591\n- T1592\n- T1593\n- T1589\n- T1595\nsource: https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\nsource_commit: 04450304b12645cb2b974ab96d28c0664758a88d\n---\n\n# Performing OSINT with SpiderFoot\n\n## Overview\n\nSpiderFoot is an open-source OSINT automation tool with 200+ modules that integrates with data sources for threat intelligence and attack surface mapping. This skill uses the SpiderFoot REST API and CLI (sf.py\u002Fspiderfoot-cli) to create and manage scans, select modules by use case (footprint, investigate, passive), parse structured results for domains, IPs, email addresses, leaked credentials, and DNS records, and generate target intelligence profiles.\n\n\n## When to Use\n\n- When conducting security assessments that involve performing osint with spiderfoot\n- When following incident response procedures for related security events\n- When performing scheduled security testing or auditing activities\n- When validating security controls through hands-on testing\n\n## Prerequisites\n\n- SpiderFoot 4.0+ installed or SpiderFoot HX cloud account\n- Python 3.8+ with requests library\n- SpiderFoot server running on default port 5001\n- Optional: API keys for VirusTotal, Shodan, HaveIBeenPwned modules\n\n## Steps\n\n1. Connect to SpiderFoot REST API or use CLI interface\n2. Create a new scan with target specification (domain, IP, email, name)\n3. Select scan modules by use case (all, footprint, investigate, passive)\n4. Monitor scan progress via API polling\n5. Retrieve and parse scan results by data element type\n6. Extract key findings: subdomains, IPs, emails, leaked credentials\n7. Generate structured OSINT intelligence report\n\n## Expected Output\n\nJSON report containing OSINT findings organized by data type (domains, IPs, emails, credentials, DNS records), module source attribution, and target profile summary with risk indicators.\n","# Performing OSINT with SpiderFoot\n\n## Overview\n\nSpiderFoot is an open-source OSINT automation tool with 200+ modules that integrates with data sources for threat intelligence and attack surface mapping. This skill uses the SpiderFoot REST API and CLI (sf.py\u002Fspiderfoot-cli) to create and manage scans, select modules by use case (footprint, investigate, passive), parse structured results for domains, IPs, email addresses, leaked credentials, and DNS records, and generate target intelligence profiles.\n\n\n## When to Use\n\n- When conducting security assessments that involve performing osint with spiderfoot\n- When following incident response procedures for related security events\n- When performing scheduled security testing or auditing activities\n- When validating security controls through hands-on testing\n\n## Prerequisites\n\n- SpiderFoot 4.0+ installed or SpiderFoot HX cloud account\n- Python 3.8+ with requests library\n- SpiderFoot server running on default port 5001\n- Optional: API keys for VirusTotal, Shodan, HaveIBeenPwned modules\n\n## Steps\n\n1. Connect to SpiderFoot REST API or use CLI interface\n2. Create a new scan with target specification (domain, IP, email, name)\n3. Select scan modules by use case (all, footprint, investigate, passive)\n4. Monitor scan progress via API polling\n5. Retrieve and parse scan results by data element type\n6. Extract key findings: subdomains, IPs, emails, leaked credentials\n7. Generate structured OSINT intelligence report\n\n## Expected Output\n\nJSON report containing OSINT findings organized by data type (domains, IPs, emails, credentials, DNS records), module source attribution, and target profile summary with risk indicators.\n",{"name":5,"tags":25,"author":32,"domain":33,"source":34,"license":15,"version":35,"nist_csf":36,"subdomain":29,"description":7,"mitre_attack":41,"source_commit":47},[26,27,28,29,30,31],"osint","spiderfoot","reconnaissance","threat-intelligence","attack-surface","target-profiling","mahipal","cybersecurity","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills","1.0",[37,38,39,40],"ID.RA-01","ID.RA-05","DE.CM-01","DE.AE-02",[42,43,44,45,46],"T1591","T1592","T1593","T1589","T1595","04450304b12645cb2b974ab96d28c0664758a88d","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa","core\u002Fskills\u002Fperforming-osint-with-spiderfoot",1,"https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI","https:\u002F\u002Fyana.vutam.link\u002F","https:\u002F\u002Fgithub.com\u002FHoronomos-laps","https:\u002F\u002Fyana.vutam.link","An open-source governed runtime & execution environment for multi-agent AI systems.","2026-11-11 23:56:26",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill performing-osint-with-spiderfoot",{"tool":64,"command":65},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill performing-osint-with-spiderfoot",{"tool":67,"command":68},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill performing-osint-with-spiderfoot","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fperforming-osint-with-spiderfoot\u002FSKILL.md",true,[72,76,82,88],{"path":73,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":75,"sourceHtmlUrl":16},"LICENSE","许可证",11255,{"path":77,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":80,"sourceHtmlUrl":81},"references\u002Fapi-reference.md","REFERENCE","参考文档",1954,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fperforming-osint-with-spiderfoot\u002Freferences\u002Fapi-reference.md",{"path":83,"resourceType":84,"resourceTypeDesc":85,"sizeBytes":86,"sourceHtmlUrl":87},"scripts\u002Fagent.py","SCRIPT","脚本",6914,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fperforming-osint-with-spiderfoot\u002Fscripts\u002Fagent.py",{"path":89,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":90,"sourceHtmlUrl":91},"SKILL.es.md",2092,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fperforming-osint-with-spiderfoot\u002FSKILL.es.md",[93,101,108,116,124,132],{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":97,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":100,"publishedAt":20},"01M735GKET5YVYKAY62W2P5YXB","openai--sentry--sentry","Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.","MIT","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fopenai--sentry--sentry\u002FSKILL.md",[],[],{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":107,"publishedAt":20},"01M73DCAP83T17HY7SMGK7MGFE","ito-basket-compare","Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. 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Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FSKILL.md",[],[],{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":128,"sourceHtmlUrl":129,"categories":130,"keywords":131,"publishedAt":20},"01M734AFNXD06Z78QRK0VKGT7Q","implementing-microsegmentation-with-guardicore","Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FSKILL.md",[],[],{"skillNo":133,"name":134,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":137,"publishedAt":20},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]