[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AEESA4ASJ0FPVKAJXWZQME":3,"skill-same:01M6AEESA4ASJ0FPVKAJXWZQME":156},{"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":23,"publishedAt":40,"linkOnly":41,"markdownContent":42,"markdownBody":43,"frontMatter":44,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":68,"repositoryHtmlUrl":69,"repositoryHomepageUrl":70,"ownerHtmlUrl":71,"ownerBlogUrl":72,"ownerDescription":73,"updatedAt":74,"install":75,"resources":88},"01M6AEESA4ASJ0FPVKAJXWZQME","detecting-mimikatz-execution-patterns",null,"Detect Mimikatz credential-dumping activity via command-line pattern matching, LSASS access signatures, binary\u002Fhash indicators, and in-memory detection of known Mimikatz modules. Use when threat hunting for T1003 credential access, triaging EDR\u002FSIEM alerts on LSASS access, scoping compromise during incident response, or validating detection coverage in a purple team exercise.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35884,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fdetecting-mimikatz-execution-patterns\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],"mimikatz","detecting mimikatz execution patterns","memory","cybersecurity","incident response","siem","threat hunting","web","mitre-attack","threat-hunting","proactive-detection","credential-dumping","detection","edr","lsass","t1003","2026-11-10 10:12:30",false,"---\nname: detecting-mimikatz-execution-patterns\ndescription: Detect Mimikatz credential-dumping activity via command-line pattern matching, LSASS access signatures, binary\u002Fhash indicators, and in-memory detection of known Mimikatz modules. Use when threat hunting for T1003 credential access, triaging EDR\u002FSIEM alerts on LSASS access, scoping compromise during incident response, or validating detection coverage in a purple team exercise.\ndomain: cybersecurity\nsubdomain: threat-hunting\ntags:\n- threat-hunting\n- mitre-attack\n- mimikatz\n- credential-dumping\n- edr\n- t1003\n- proactive-detection\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nd3fend_techniques:\n- Execution Isolation\n- Process Termination\n- Hardware-based Process Isolation\n- Web Session Access Mediation\n- Process Suspension\nnist_csf:\n- DE.CM-01\n- DE.AE-02\n- DE.AE-07\n- ID.RA-05\nmitre_attack:\n- T1046\n- T1057\n- T1082\n- T1083\n- T1003\n---\n\n# Detecting Mimikatz Execution Patterns\n\n## When to Use\n\n- When proactively hunting for indicators of detecting mimikatz execution patterns in the environment\n- After threat intelligence indicates active campaigns using these techniques\n- During incident response to scope compromise related to these techniques\n- When EDR or SIEM alerts trigger on related indicators\n- During periodic security assessments and purple team exercises\n\n## Prerequisites\n\n- EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)\n- SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)\n- Sysmon deployed with comprehensive configuration\n- Windows Security Event Log forwarding enabled\n- Threat intelligence feeds for IOC correlation\n\n## Workflow\n\n1. **Formulate Hypothesis**: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.\n2. **Identify Data Sources**: Determine which logs and telemetry are needed to validate or refute the hypothesis.\n3. **Execute Queries**: Run detection queries against SIEM and EDR platforms to collect relevant events.\n4. **Analyze Results**: Examine query results for anomalies, correlating across multiple data sources.\n5. **Validate Findings**: Distinguish true positives from false positives through contextual analysis.\n6. **Correlate Activity**: Link findings to broader attack chains and threat actor TTPs.\n7. **Document and Report**: Record findings, update detection rules, and recommend response actions.\n\n## Key Concepts\n\n| Concept | Description |\n|---------|-------------|\n| T1003.001 | LSASS Memory |\n| T1003.006 | DCSync |\n| T1558.003 | Kerberoasting |\n| T1558.001 | Golden Ticket |\n\n## Tools & Systems\n\n| Tool | Purpose |\n|------|---------|\n| CrowdStrike Falcon | EDR telemetry and threat detection |\n| Microsoft Defender for Endpoint | Advanced hunting with KQL |\n| Splunk Enterprise | SIEM log analysis with SPL queries |\n| Elastic Security | Detection rules and investigation timeline |\n| Sysmon | Detailed Windows event monitoring |\n| Velociraptor | Endpoint artifact collection and hunting |\n| Sigma Rules | Cross-platform detection rule format |\n\n## Common Scenarios\n\n1. **Scenario 1**: Standard sekurlsa::logonpasswords credential dump\n2. **Scenario 2**: PowerShell Invoke-Mimikatz reflective loading\n3. **Scenario 3**: DCSync from non-DC host\n4. **Scenario 4**: Golden ticket creation for persistence\n\n## Output Format\n\n```\nHunt ID: TH-DETECT-[DATE]-[SEQ]\nTechnique: T1003.001\nHost: [Hostname]\nUser: [Account context]\nEvidence: [Log entries, process trees, network data]\nRisk Level: [Critical\u002FHigh\u002FMedium\u002FLow]\nConfidence: [High\u002FMedium\u002FLow]\nRecommended Action: [Containment, investigation, monitoring]\n```\n","# Detecting Mimikatz Execution Patterns\n\n## When to Use\n\n- When proactively hunting for indicators of detecting mimikatz execution patterns in the environment\n- After threat intelligence indicates active campaigns using these techniques\n- During incident response to scope compromise related to these techniques\n- When EDR or SIEM alerts trigger on related indicators\n- During periodic security assessments and purple team exercises\n\n## Prerequisites\n\n- EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)\n- SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)\n- Sysmon deployed with comprehensive configuration\n- Windows Security Event Log forwarding enabled\n- Threat intelligence feeds for IOC correlation\n\n## Workflow\n\n1. **Formulate Hypothesis**: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.\n2. **Identify Data Sources**: Determine which logs and telemetry are needed to validate or refute the hypothesis.\n3. **Execute Queries**: Run detection queries against SIEM and EDR platforms to collect relevant events.\n4. **Analyze Results**: Examine query results for anomalies, correlating across multiple data sources.\n5. **Validate Findings**: Distinguish true positives from false positives through contextual analysis.\n6. **Correlate Activity**: Link findings to broader attack chains and threat actor TTPs.\n7. **Document and Report**: Record findings, update detection rules, and recommend response actions.\n\n## Key Concepts\n\n| Concept | Description |\n|---------|-------------|\n| T1003.001 | LSASS Memory |\n| T1003.006 | DCSync |\n| T1558.003 | Kerberoasting |\n| T1558.001 | Golden Ticket |\n\n## Tools & Systems\n\n| Tool | Purpose |\n|------|---------|\n| CrowdStrike Falcon | EDR telemetry and threat detection |\n| Microsoft Defender for Endpoint | Advanced hunting with KQL |\n| Splunk Enterprise | SIEM log analysis with SPL queries |\n| Elastic Security | Detection rules and investigation timeline |\n| Sysmon | Detailed Windows event monitoring |\n| Velociraptor | Endpoint artifact collection and hunting |\n| Sigma Rules | Cross-platform detection rule format |\n\n## Common Scenarios\n\n1. **Scenario 1**: Standard sekurlsa::logonpasswords credential dump\n2. **Scenario 2**: PowerShell Invoke-Mimikatz reflective loading\n3. **Scenario 3**: DCSync from non-DC host\n4. **Scenario 4**: Golden ticket creation for persistence\n\n## Output Format\n\n```\nHunt ID: TH-DETECT-[DATE]-[SEQ]\nTechnique: T1003.001\nHost: [Hostname]\nUser: [Account context]\nEvidence: [Log entries, process trees, network data]\nRisk Level: [Critical\u002FHigh\u002FMedium\u002FLow]\nConfidence: [High\u002FMedium\u002FLow]\nRecommended Action: [Containment, investigation, monitoring]\n```\n",{"name":5,"tags":45,"author":46,"domain":27,"license":15,"version":47,"nist_csf":48,"subdomain":33,"description":7,"mitre_attack":53,"d3fend_techniques":59},[33,32,24,35,37,39,34],"mahipal","1.0",[49,50,51,52],"DE.CM-01","DE.AE-02","DE.AE-07","ID.RA-05",[54,55,56,57,58],"T1046","T1057","T1082","T1083","T1003",[60,61,62,63,64],"Execution Isolation","Process Termination","Hardware-based Process Isolation","Web Session Access Mediation","Process Suspension","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fdetecting-mimikatz-execution-patterns",4379,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills","https:\u002F\u002Fmahipal.engineer\u002FAnthropic-Cybersecurity-Skills\u002F","https:\u002F\u002Fgithub.com\u002Fmukul975","Mahipal.engineer","🔐 Cybersecurity | 💻 Dev | 📷 Street Photographer\r\n🎓 MSc | 📚 Research & AI Security","2026-08-31 12:32:44",{"source":8,"skillName":5,"commands":76,"prompt":86,"zipAvailable":87},[77,80,83],{"tool":78,"command":79},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill detecting-mimikatz-execution-patterns",{"tool":81,"command":82},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill detecting-mimikatz-execution-patterns",{"tool":84,"command":85},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill 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artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI\u002FCD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fverifying-build-provenance-with-slsa-sigstore\u002FSKILL.md",[163],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[165,166,167,168,169,27,28,170,171,172,173,174,175,176,177,178,179,180,181,182],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","security","identity","pr","code","artifacts","ci","supply-chain","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":190,"publishedAt":40},"01M6AGDGBPWYVZ2F11GFKJ4HZ9","validating-tpm-measured-boot-attestation","Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote\u002Ftpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware\u002Fkernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-tpm-measured-boot-attestation\u002FSKILL.md",[189],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[191,179,192,193,169,194,27,171,195,196,197,198,199,200,201,202,203,204,205,206],"boot","TPM","validating tpm measured boot attestation","policy","verification","ZeRO","firmware","Tools","measured-boot","PCR","integrity","secrets","remote-attestation","tpm2-tools","integrity-verification","trusted-computing",{"skillNo":208,"name":209,"nameZh":6,"description":210,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":211,"categories":212,"keywords":217,"publishedAt":40},"01M6AGDCW0Y4FXZ3362GT1941M","validating-backup-integrity-for-recovery","Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable\u002Fair-gapped backups for silent corruption or tampering.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-backup-integrity-for-recovery\u002FSKILL.md",[213,216],{"categoryNo":214,"categoryName":215,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[201,218,219,220,221,27,222,223,195,224,225,226,227,228,36,229,230,231,232,233],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":235,"name":236,"nameZh":6,"description":237,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":238,"categories":239,"keywords":241,"publishedAt":40},"01M6AGD9GBG2KZ336AE763J3WH","triaging-windows-with-kape","Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment\u002Ftriage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-windows-with-kape\u002FSKILL.md",[240],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[242,243,244,27,245,246,247,248,249,250,251,252,253,254,255,256,198,257,258,259],"windows","kape","triaging windows with kape","registry","browser","logs","windows-forensics","dfir","mft","mftecmd","data","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":261,"name":262,"nameZh":6,"description":263,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":264,"categories":265,"keywords":267,"publishedAt":40},"01M6AGD5PW5J4EVZM958WD74ZQ","triaging-vulnerabilities-with-ssvc-framework","Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track\u002FTrack*\u002FAttend\u002FAct decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-vulnerabilities-with-ssvc-framework\u002FSKILL.md",[266],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[268,269,270,27,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286],"vulnerabilities","framework","triaging vulnerabilities with ssvc framework","status","planning","CISA","vulnerability-management","risk-management","nessus","qualys","openvas","cvss","remediation","risk","vulnerability","api","prioritization","ssvc","decision-tree",{"skillNo":288,"name":289,"nameZh":6,"description":290,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":291,"categories":292,"keywords":294,"publishedAt":40},"01M6AGD24TTQQM4CXG69E3B9TJ","triaging-security-incident","Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM\u002FEDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-security-incident\u002FSKILL.md",[293],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[169,295,27,29,296,297,298,299,300,301,37,229,302,230,303,304,305,306,307,308],"triaging security incident","file","ioc","soc","NIST-800-61","NIST","severity","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]