[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71DWG8CS75T03XDG6EYM2CS":3,"skill-same:01M71DWG8CS75T03XDG6EYM2CS":55},{"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":23,"linkOnly":24,"markdownContent":25,"markdownBody":26,"frontMatter":27,"refName":28,"commitSha":29,"skillDirectory":30,"forksCount":14,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M71DWG8CS75T03XDG6EYM2CS","intel-mitre-threatmodel",null,"Intel Mitre Threatmodel.","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\u002Fintel-mitre-threatmodel\u002FSKILL.md",[],[19,20,21,22],"threatmodel","intel","intel mitre threatmodel","cybersecurity","2026-11-10 10:12:30",false,"---\nname: intel-mitre-threatmodel\ndescription: \"Intel Mitre Threatmodel.\"\ndomain: cybersecurity\n---\n\n--|\n| **MITRE ATT&CK** | Knowledge base of adversary tactics, techniques, and procedures based on real-world observations |\n| **TTP** | Tactics, Techniques, and Procedures — the behavioral patterns of adversary groups |\n| **ATT&CK Navigator** | Web tool for visualizing ATT&CK matrices as layered heatmaps showing coverage or threat profiles |\n| **Gap Analysis** | Process of comparing threat actor TTPs against detection coverage to identify blind spots |\n| **Threat-Informed Defense** | Security strategy prioritizing defenses based on actual adversary behaviors rather than theoretical risks |\n| **Adversary Emulation** | Controlled simulation of threat actor TTPs to validate detection and response capabilities |\n\n## Tools & Systems\n\n- **MITRE ATT&CK Navigator**: Web-based visualization tool for creating and overlaying ATT&CK technique layers\n- **MITRE Caldera**: Automated adversary emulation platform for testing detection coverage at scale\n- **Atomic Red Team**: Open-source library of ATT&CK technique tests for security control validation\n- **CTID ATT&CK Workbench**: MITRE tool for customizing ATT&CK knowledge base with organizational context\n- **Tidal Cyber**: Commercial platform for threat-informed defense planning using ATT&CK framework\n\n## Common Scenarios\n\n- **Annual Threat Assessment**: Map top 5 threat actors to ATT&CK, overlay against detection, produce gap analysis\n- **Cloud Migration Planning**: Model cloud-specific threats (T1078.004, T1537) and plan detection coverage\n- **M&A Security Assessment**: Threat model the acquired company's environment against relevant threat actors\n- **Budget Justification**: Use gap analysis to demonstrate detection blind spots requiring tool investment\n- **Purple Team Planning**: Select adversary emulation scenarios based on highest-priority gaps from threat model\n\n## Output Format\n\n```\nTHREAT MODEL ASSESSMENT — Financial Services Division\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nDate:             2024-03-15\nThreat Actors:    FIN7, APT38, Lazarus Group\nTechniques Total: 87 unique techniques across all actors\n\nDETECTION COVERAGE:\n  Covered:     56\u002F87 (64%)\n  Gaps:        31\u002F87 (36%)\n\n  Tactic Coverage Breakdown:\n    Initial Access:      78%  ████████░░\n    Execution:           82%  █████████░\n    Persistence:         71%  ████████░░\n    Priv Escalation:     65%  ███████░░░\n    Defense Evasion:     52%  ██████░░░░  \u003C-- Priority gap\n    Credential Access:   58%  ██████░░░░  \u003C-- Priority gap\n    Discovery:           45%  █████░░░░░\n    Lateral Movement:    61%  ███████░░░\n    Collection:          50%  ██████░░░░\n    Exfiltration:        55%  ██████░░░░\n    C2:                  67%  ███████░░░\n\nTOP PRIORITY GAPS (30-day remediation):\n  1. T1055 Process Injection — used by all 3 actors, 0 detections\n  2. T1003.006 DCSync — used by FIN7 and Lazarus, 0 detections\n  3. T1070.004 File Deletion — evidence destruction, 0 detections\n\nINVESTMENT RECOMMENDATION:\n  Closing top 10 gaps requires: 2 detection engineer FTEs, 60 days\n  Expected coverage improvement: 64% -> 76%\n```\n","--|\n| **MITRE ATT&CK** | Knowledge base of adversary tactics, techniques, and procedures based on real-world observations |\n| **TTP** | Tactics, Techniques, and Procedures — the behavioral patterns of adversary groups |\n| **ATT&CK Navigator** | Web tool for visualizing ATT&CK matrices as layered heatmaps showing coverage or threat profiles |\n| **Gap Analysis** | Process of comparing threat actor TTPs against detection coverage to identify blind spots |\n| **Threat-Informed Defense** | Security strategy prioritizing defenses based on actual adversary behaviors rather than theoretical risks |\n| **Adversary Emulation** | Controlled simulation of threat actor TTPs to validate detection and response capabilities |\n\n## Tools & Systems\n\n- **MITRE ATT&CK Navigator**: Web-based visualization tool for creating and overlaying ATT&CK technique layers\n- **MITRE Caldera**: Automated adversary emulation platform for testing detection coverage at scale\n- **Atomic Red Team**: Open-source library of ATT&CK technique tests for security control validation\n- **CTID ATT&CK Workbench**: MITRE tool for customizing ATT&CK knowledge base with organizational context\n- **Tidal Cyber**: Commercial platform for threat-informed defense planning using ATT&CK framework\n\n## Common Scenarios\n\n- **Annual Threat Assessment**: Map top 5 threat actors to ATT&CK, overlay against detection, produce gap analysis\n- **Cloud Migration Planning**: Model cloud-specific threats (T1078.004, T1537) and plan detection coverage\n- **M&A Security Assessment**: Threat model the acquired company's environment against relevant threat actors\n- **Budget Justification**: Use gap analysis to demonstrate detection blind spots requiring tool investment\n- **Purple Team Planning**: Select adversary emulation scenarios based on highest-priority gaps from threat model\n\n## Output Format\n\n```\nTHREAT MODEL ASSESSMENT — Financial Services Division\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\nDate:             2024-03-15\nThreat Actors:    FIN7, APT38, Lazarus Group\nTechniques Total: 87 unique techniques across all actors\n\nDETECTION COVERAGE:\n  Covered:     56\u002F87 (64%)\n  Gaps:        31\u002F87 (36%)\n\n  Tactic Coverage Breakdown:\n    Initial Access:      78%  ████████░░\n    Execution:           82%  █████████░\n    Persistence:         71%  ████████░░\n    Priv Escalation:     65%  ███████░░░\n    Defense Evasion:     52%  ██████░░░░  \u003C-- Priority gap\n    Credential Access:   58%  ██████░░░░  \u003C-- Priority gap\n    Discovery:           45%  █████░░░░░\n    Lateral Movement:    61%  ███████░░░\n    Collection:          50%  ██████░░░░\n    Exfiltration:        55%  ██████░░░░\n    C2:                  67%  ███████░░░\n\nTOP PRIORITY GAPS (30-day remediation):\n  1. T1055 Process Injection — used by all 3 actors, 0 detections\n  2. T1003.006 DCSync — used by FIN7 and Lazarus, 0 detections\n  3. T1070.004 File Deletion — evidence destruction, 0 detections\n\nINVESTMENT RECOMMENDATION:\n  Closing top 10 gaps requires: 2 detection engineer FTEs, 60 days\n  Expected coverage improvement: 64% -> 76%\n```\n",{"name":5,"domain":22,"description":7},"main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fintel-mitre-threatmodel","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill intel-mitre-threatmodel",{"tool":41,"command":42},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill intel-mitre-threatmodel",{"tool":44,"command":45},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill intel-mitre-threatmodel","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fintel-mitre-threatmodel\u002FSKILL.md",true,[49],{"path":50,"resourceType":51,"resourceTypeDesc":52,"sizeBytes":53,"sourceHtmlUrl":54},"index.json","REFERENCE","参考文档",492,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fintel-mitre-threatmodel\u002Findex.json",[56,81,104,126,148,164],{"skillNo":57,"name":58,"nameZh":6,"description":59,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":60,"categories":61,"keywords":62,"publishedAt":23},"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",[],[63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,22,80],"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":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":23},"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",[],[88,63,89,66,90,91,92,22,93,94,95,96,97,98,68,99,100,101,102,103],"exploit","services wmi exec exploit","exec","remote","traffic","Bash","analysis","team","across","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":110,"publishedAt":23},"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",[],[111,112,113,114,115,116,22,93,117,94,118,119,68,101,120,121,122,123,124,125],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","analyze","uncover","software","activity","digital-forensics","windows-registry","regripper","sonnet",{"skillNo":127,"name":128,"nameZh":6,"description":129,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":130,"categories":131,"keywords":132,"publishedAt":23},"01M71HACR4A8XTWTTSXK4124AA","processes-token-impersonate-detect","Detect Windows token impersonation and privilege abuse including SeImpersonatePrivilege exploitation via Potato 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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",[],[155,156,64,157,135,137,158,69,159,139,22,80,94,160,161,162,163,147,68,70],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":168,"categories":169,"keywords":170,"publishedAt":23},"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",[],[171,64,135,172,158,69,173,174,22,80,175,176,177,178,179,180,68,70,181,182],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","with","mismatched","headers"]