[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FXZSAM7WVA6850DCKAFGP":3,"skill-same:01M71FXZSAM7WVA6850DCKAFGP":57},{"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":25,"linkOnly":26,"markdownContent":27,"markdownBody":28,"frontMatter":29,"refName":30,"commitSha":31,"skillDirectory":32,"forksCount":14,"repositoryHtmlUrl":33,"repositoryHomepageUrl":6,"ownerHtmlUrl":34,"ownerBlogUrl":6,"ownerDescription":35,"updatedAt":36,"install":37,"resources":50},"01M71FXZSAM7WVA6850DCKAFGP","soc-detection-sigma",null,"Soc Detection Sigma.","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\u002Fsoc-detection-sigma\u002FSKILL.md",[],[19,20,21,22,23,24],"soc","sigma","detection","detection sigma","soc detection sigma","cybersecurity","2026-11-10 10:12:30",false,"---\nname: soc-detection-sigma\ndescription: \"Soc Detection Sigma.\"\ndomain: cybersecurity\n---\n\n--|\n| **Sigma** | Vendor-agnostic detection rule format (YAML-based) that compiles to SIEM-specific queries via backends |\n| **pySigma** | Python library replacing legacy sigmac for rule conversion, validation, and pipeline processing |\n| **Backend** | pySigma plugin that translates Sigma detection logic into a target platform query language (SPL, KQL, Lucene) |\n| **Pipeline** | Field mapping configuration that translates generic Sigma field names to SIEM-specific field names |\n| **Logsource** | Sigma rule section defining the category (process_creation, network_connection) and product (windows, linux) of the target data |\n| **Detection-as-Code** | Practice of managing detection rules in version control with CI\u002FCD testing and automated deployment |\n\n## Tools & Systems\n\n- **SigmaHQ**: Official Sigma rule repository with 3,000+ community-maintained detection rules on GitHub\n- **pySigma**: Python-based Sigma rule processing framework with modular backends and pipelines\n- **ATT&CK Navigator**: MITRE tool for visualizing detection coverage mapped to ATT&CK techniques\n- **Uncoder.IO**: Web-based Sigma rule converter supporting 30+ SIEM platforms for quick translation\n\n## Common Scenarios\n\n- **New CVE Detection**: Write Sigma rule for exploitation indicators (e.g., Log4Shell JNDI lookup patterns in web logs)\n- **Hunting Rule Promotion**: Convert ad-hoc Splunk hunting query into Sigma rule for ongoing automated detection\n- **Multi-SIEM Migration**: Converting 500+ Splunk correlation searches to Sigma for migration to Elastic Security\n- **Purple Team Output**: Convert red team findings into Sigma rules for immediate defensive coverage\n- **Threat Intel Operationalization**: Transform IOC-based threat reports into behavioral Sigma rules\n\n## Output Format\n\n```\nSIGMA RULE DEPLOYMENT REPORT\n━━━━━━━━━━━━━━━━━━━━━━━━━━━\nRule ID:      0d894093-71bc-43c3-8d63-bf520e73a7c5\nTitle:        Mimikatz Credential Dumping via LSASS Access\nATT&CK:       T1003.001 - LSASS Memory\nSeverity:     High\nStatus:       Deployed to Production\n\nConversions:\n  Splunk SPL:    PASS — Saved search \"sigma_lsass_access\" created\n  Elastic EQL:   PASS — Detection rule ID elastic-0d894093 enabled\n  Sentinel KQL:  PASS — Analytics rule deployed via ARM template\n\nTesting:\n  True Positives:    4\u002F4 test cases matched\n  False Positives:   2 in 7-day backtest (svchost edge case — filter added)\n  Performance:       Avg execution 3.2s on 50M events\u002Fday\n```\n","--|\n| **Sigma** | Vendor-agnostic detection rule format (YAML-based) that compiles to SIEM-specific queries via backends |\n| **pySigma** | Python library replacing legacy sigmac for rule conversion, validation, and pipeline processing |\n| **Backend** | pySigma plugin that translates Sigma detection logic into a target platform query language (SPL, KQL, Lucene) |\n| **Pipeline** | Field mapping configuration that translates generic Sigma field names to SIEM-specific field names |\n| **Logsource** | Sigma rule section defining the category (process_creation, network_connection) and product (windows, linux) of the target data |\n| **Detection-as-Code** | Practice of managing detection rules in version control with CI\u002FCD testing and automated deployment |\n\n## Tools & Systems\n\n- **SigmaHQ**: Official Sigma rule repository with 3,000+ community-maintained detection rules on GitHub\n- **pySigma**: Python-based Sigma rule processing framework with modular backends and pipelines\n- **ATT&CK Navigator**: MITRE tool for visualizing detection coverage mapped to ATT&CK techniques\n- **Uncoder.IO**: Web-based Sigma rule converter supporting 30+ SIEM platforms for quick translation\n\n## Common Scenarios\n\n- **New CVE Detection**: Write Sigma rule for exploitation indicators (e.g., Log4Shell JNDI lookup patterns in web logs)\n- **Hunting Rule Promotion**: Convert ad-hoc Splunk hunting query into Sigma rule for ongoing automated detection\n- **Multi-SIEM Migration**: Converting 500+ Splunk correlation searches to Sigma for migration to Elastic Security\n- **Purple Team Output**: Convert red team findings into Sigma rules for immediate defensive coverage\n- **Threat Intel Operationalization**: Transform IOC-based threat reports into behavioral Sigma rules\n\n## Output Format\n\n```\nSIGMA RULE DEPLOYMENT REPORT\n━━━━━━━━━━━━━━━━━━━━━━━━━━━\nRule ID:      0d894093-71bc-43c3-8d63-bf520e73a7c5\nTitle:        Mimikatz Credential Dumping via LSASS Access\nATT&CK:       T1003.001 - LSASS Memory\nSeverity:     High\nStatus:       Deployed to Production\n\nConversions:\n  Splunk SPL:    PASS — Saved search \"sigma_lsass_access\" created\n  Elastic EQL:   PASS — Detection rule ID elastic-0d894093 enabled\n  Sentinel KQL:  PASS — Analytics rule deployed via ARM template\n\nTesting:\n  True Positives:    4\u002F4 test cases matched\n  False Positives:   2 in 7-day backtest (svchost edge case — filter added)\n  Performance:       Avg execution 3.2s on 50M events\u002Fday\n```\n",{"name":5,"domain":24,"description":7},"main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fsoc-detection-sigma","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":38,"prompt":48,"zipAvailable":49},[39,42,45],{"tool":40,"command":41},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill soc-detection-sigma",{"tool":43,"command":44},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill soc-detection-sigma",{"tool":46,"command":47},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill soc-detection-sigma","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fsoc-detection-sigma\u002FSKILL.md",true,[51],{"path":52,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":55,"sourceHtmlUrl":56},"index.json","REFERENCE","参考文档",476,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fsoc-detection-sigma\u002Findex.json",[58,83,106,128,150,166],{"skillNo":59,"name":60,"nameZh":6,"description":61,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":62,"categories":63,"keywords":64,"publishedAt":25},"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",[],[65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,24,82],"services","detect","services wmi persistence detect","wmi","persistence","de","cm","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","process-forensics",{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":25},"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",[],[90,65,91,68,92,93,94,24,95,96,97,98,99,100,70,101,102,103,104,105],"exploit","services wmi exec exploit","exec","remote","traffic","Bash","analysis","team","across","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":25},"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",[],[113,114,115,116,117,118,24,95,119,96,120,121,70,103,122,123,124,125,126,127],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","analyze","uncover","software","activity","digital-forensics","windows-registry","regripper","sonnet",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":134,"publishedAt":25},"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",[],[66,135,136,137,138,139,140,71,141,24,82,142,143,144,145,146,147,148,149,70],"processes token impersonate detect","token","processes","attacks","windows","escalation","techniques","privilege-escalation","seimpersonate","token-impersonation","printspoofer","exploitation","potato","impersonation","via",{"skillNo":151,"name":152,"nameZh":6,"description":153,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":156,"publishedAt":25},"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",[],[157,158,66,159,137,139,160,71,161,141,24,82,96,162,163,164,165,149,70,72],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":172,"publishedAt":25},"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",[],[173,66,137,174,160,71,175,176,24,82,177,178,179,180,181,182,70,72,183,184],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","with","mismatched","headers"]