[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADSS29BMZKSB83VW4XFQJS":3,"skill-same:01M6ADSS29BMZKSB83VW4XFQJS":123},{"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":37,"linkOnly":38,"markdownContent":39,"markdownBody":40,"frontMatter":41,"refName":68,"commitSha":69,"skillDirectory":70,"forksCount":71,"repositoryHtmlUrl":72,"repositoryHomepageUrl":73,"ownerHtmlUrl":74,"ownerBlogUrl":75,"ownerDescription":76,"updatedAt":77,"install":78,"resources":91},"01M6ADSS29BMZKSB83VW4XFQJS","analyzing-supply-chain-malware-artifacts",null,"Investigate supply chain attack artifacts including trojanized software updates, compromised build pipelines, and sideloaded dependencies to identify intrusion vectors and scope of compromise.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35925,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\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],"artifacts","malware","analyzing","analyzing supply chain malware artifacts","cybersecurity","component","malware-analysis","supply-chain","trojanized-software","solarwinds","3cx","dependency-confusion","software-integrity","2026-11-10 10:12:30",false,"---\nname: analyzing-supply-chain-malware-artifacts\ndescription: Investigate supply chain attack artifacts including trojanized software\n  updates, compromised build pipelines, and sideloaded dependencies to identify intrusion\n  vectors and scope of compromise.\ndomain: cybersecurity\nsubdomain: malware-analysis\ntags:\n- supply-chain\n- malware-analysis\n- trojanized-software\n- solarwinds\n- 3cx\n- dependency-confusion\n- software-integrity\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\natlas_techniques:\n- AML.T0010\nnist_ai_rmf:\n- GOVERN-5.2\n- MAP-1.6\n- MANAGE-2.2\nd3fend_techniques:\n- Platform Hardening\n- Hardware Component Inventory\n- Restore Object\n- Electromagnetic Radiation Hardening\n- RF Shielding\nnist_csf:\n- DE.AE-02\n- RS.AN-03\n- ID.RA-01\n- DE.CM-01\nmitre_attack:\n- T1195.002\n- T1195.001\n- T1554\n- T1553.002\n- T1027\n---\n# Analyzing Supply Chain Malware Artifacts\n\n## Overview\n\nSupply chain attacks compromise legitimate software distribution channels to deliver malware through trusted update mechanisms. Notable examples include SolarWinds SUNBURST (2020, affecting 18,000+ customers), 3CX SmoothOperator (2023, a cascading supply chain attack originating from Trading Technologies), and numerous npm\u002FPyPI package poisoning campaigns. Analysis involves comparing trojanized binaries against legitimate versions, identifying injected code in build artifacts, examining code signing anomalies, and tracing the infection chain from initial compromise through payload delivery. As of 2025, supply chain attacks account for 30% of all breaches, a 100% increase from prior years.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing supply chain malware artifacts\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Python 3.9+ with `pefile`, `ssdeep`, `hashlib`\n- Binary diff tools (BinDiff, Diaphora)\n- Code signing verification tools (sigcheck, codesign)\n- Software composition analysis (SCA) tools\n- Access to legitimate software versions for comparison\n- Package repository monitoring (npm, PyPI, NuGet)\n\n## Workflow\n\n### Step 1: Binary Comparison Analysis\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"Compare trojanized binary against legitimate version.\"\"\"\nimport hashlib\nimport pefile\nimport sys\nimport json\n\n\ndef compare_pe_files(legitimate_path, suspect_path):\n    \"\"\"Compare PE file structures between legitimate and suspect versions.\"\"\"\n    legit_pe = pefile.PE(legitimate_path)\n    suspect_pe = pefile.PE(suspect_path)\n\n    report = {\"differences\": [], \"suspicious_sections\": [], \"import_changes\": []}\n\n    # Compare sections\n    legit_sections = {s.Name.rstrip(b'\\x00').decode(): {\n        \"size\": s.SizeOfRawData,\n        \"entropy\": s.get_entropy(),\n        \"characteristics\": s.Characteristics,\n    } for s in legit_pe.sections}\n\n    suspect_sections = {s.Name.rstrip(b'\\x00').decode(): {\n        \"size\": s.SizeOfRawData,\n        \"entropy\": s.get_entropy(),\n        \"characteristics\": s.Characteristics,\n    } for s in suspect_pe.sections}\n\n    # Find new or modified sections\n    for name, props in suspect_sections.items():\n        if name not in legit_sections:\n            report[\"suspicious_sections\"].append({\n                \"name\": name, \"reason\": \"New section not in legitimate version\",\n                \"size\": props[\"size\"], \"entropy\": round(props[\"entropy\"], 2),\n            })\n        elif abs(props[\"size\"] - legit_sections[name][\"size\"]) > 1024:\n            report[\"suspicious_sections\"].append({\n                \"name\": name, \"reason\": \"Section size significantly changed\",\n                \"legit_size\": legit_sections[name][\"size\"],\n                \"suspect_size\": props[\"size\"],\n            })\n\n    # Compare imports\n    legit_imports = set()\n    if hasattr(legit_pe, 'DIRECTORY_ENTRY_IMPORT'):\n        for entry in legit_pe.DIRECTORY_ENTRY_IMPORT:\n            for imp in entry.imports:\n                if imp.name:\n                    legit_imports.add(f\"{entry.dll.decode()}!{imp.name.decode()}\")\n\n    suspect_imports = set()\n    if hasattr(suspect_pe, 'DIRECTORY_ENTRY_IMPORT'):\n        for entry in suspect_pe.DIRECTORY_ENTRY_IMPORT:\n            for imp in entry.imports:\n                if imp.name:\n                    suspect_imports.add(f\"{entry.dll.decode()}!{imp.name.decode()}\")\n\n    new_imports = suspect_imports - legit_imports\n    if new_imports:\n        report[\"import_changes\"] = list(new_imports)\n\n    # Check code signing\n    report[\"legit_signed\"] = bool(legit_pe.OPTIONAL_HEADER.DATA_DIRECTORY[4].Size)\n    report[\"suspect_signed\"] = bool(suspect_pe.OPTIONAL_HEADER.DATA_DIRECTORY[4].Size)\n\n    return report\n\n\ndef hash_file(filepath):\n    \"\"\"Calculate multiple hashes for a file.\"\"\"\n    hashes = {}\n    with open(filepath, 'rb') as f:\n        data = f.read()\n    for algo in ['md5', 'sha1', 'sha256']:\n        h = hashlib.new(algo)\n        h.update(data)\n        hashes[algo] = h.hexdigest()\n    return hashes\n\n\nif __name__ == \"__main__\":\n    if len(sys.argv) \u003C 3:\n        print(f\"Usage: {sys.argv[0]} \u003Clegitimate_binary> \u003Csuspect_binary>\")\n        sys.exit(1)\n    report = compare_pe_files(sys.argv[1], sys.argv[2])\n    print(json.dumps(report, indent=2))\n```\n\n## Validation Criteria\n\n- Trojanized components identified through binary diffing\n- Injected code isolated and analyzed separately\n- Code signing anomalies documented\n- Infection timeline reconstructed from build artifacts\n- Downstream impact scope assessed across affected systems\n- IOCs extracted for detection and blocking\n\n## References\n\n- [ReversingLabs - 3CX Supply Chain Analysis](https:\u002F\u002Fwww.reversinglabs.com\u002Fblog\u002Fwhat-went-wrong-with-the-3cx-software-supply-chain-attack-and-how-it-could-have-been-prevented)\n- [Fortinet - SolarWinds Supply Chain Attack](https:\u002F\u002Fwww.fortinet.com\u002Fresources\u002Fcyberglossary\u002Fsolarwinds-cyber-attack)\n- [Picus - 3CX SmoothOperator Analysis](https:\u002F\u002Fwww.picussecurity.com\u002Fresource\u002Fblog\u002Fsmoothoperator-analysis-of-3cxdesktopapp-supply-chain-attack)\n- [MITRE ATT&CK T1195 - Supply Chain Compromise](https:\u002F\u002Fattack.mitre.org\u002Ftechniques\u002FT1195\u002F)\n","# Analyzing Supply Chain Malware Artifacts\n\n## Overview\n\nSupply chain attacks compromise legitimate software distribution channels to deliver malware through trusted update mechanisms. Notable examples include SolarWinds SUNBURST (2020, affecting 18,000+ customers), 3CX SmoothOperator (2023, a cascading supply chain attack originating from Trading Technologies), and numerous npm\u002FPyPI package poisoning campaigns. Analysis involves comparing trojanized binaries against legitimate versions, identifying injected code in build artifacts, examining code signing anomalies, and tracing the infection chain from initial compromise through payload delivery. As of 2025, supply chain attacks account for 30% of all breaches, a 100% increase from prior years.\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing supply chain malware artifacts\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Python 3.9+ with `pefile`, `ssdeep`, `hashlib`\n- Binary diff tools (BinDiff, Diaphora)\n- Code signing verification tools (sigcheck, codesign)\n- Software composition analysis (SCA) tools\n- Access to legitimate software versions for comparison\n- Package repository monitoring (npm, PyPI, NuGet)\n\n## Workflow\n\n### Step 1: Binary Comparison Analysis\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"Compare trojanized binary against legitimate version.\"\"\"\nimport hashlib\nimport pefile\nimport sys\nimport json\n\n\ndef compare_pe_files(legitimate_path, suspect_path):\n    \"\"\"Compare PE file structures between legitimate and suspect versions.\"\"\"\n    legit_pe = pefile.PE(legitimate_path)\n    suspect_pe = pefile.PE(suspect_path)\n\n    report = {\"differences\": [], \"suspicious_sections\": [], \"import_changes\": []}\n\n    # Compare sections\n    legit_sections = {s.Name.rstrip(b'\\x00').decode(): {\n        \"size\": s.SizeOfRawData,\n        \"entropy\": s.get_entropy(),\n        \"characteristics\": s.Characteristics,\n    } for s in legit_pe.sections}\n\n    suspect_sections = {s.Name.rstrip(b'\\x00').decode(): {\n        \"size\": s.SizeOfRawData,\n        \"entropy\": s.get_entropy(),\n        \"characteristics\": s.Characteristics,\n    } for s in suspect_pe.sections}\n\n    # Find new or modified sections\n    for name, props in suspect_sections.items():\n        if name not in legit_sections:\n            report[\"suspicious_sections\"].append({\n                \"name\": name, \"reason\": \"New section not in legitimate version\",\n                \"size\": props[\"size\"], \"entropy\": round(props[\"entropy\"], 2),\n            })\n        elif abs(props[\"size\"] - legit_sections[name][\"size\"]) > 1024:\n            report[\"suspicious_sections\"].append({\n                \"name\": name, \"reason\": \"Section size significantly changed\",\n                \"legit_size\": legit_sections[name][\"size\"],\n                \"suspect_size\": props[\"size\"],\n            })\n\n    # Compare imports\n    legit_imports = set()\n    if hasattr(legit_pe, 'DIRECTORY_ENTRY_IMPORT'):\n        for entry in legit_pe.DIRECTORY_ENTRY_IMPORT:\n            for imp in entry.imports:\n                if imp.name:\n                    legit_imports.add(f\"{entry.dll.decode()}!{imp.name.decode()}\")\n\n    suspect_imports = set()\n    if hasattr(suspect_pe, 'DIRECTORY_ENTRY_IMPORT'):\n        for entry in suspect_pe.DIRECTORY_ENTRY_IMPORT:\n            for imp in entry.imports:\n                if imp.name:\n                    suspect_imports.add(f\"{entry.dll.decode()}!{imp.name.decode()}\")\n\n    new_imports = suspect_imports - legit_imports\n    if new_imports:\n        report[\"import_changes\"] = list(new_imports)\n\n    # Check code signing\n    report[\"legit_signed\"] = bool(legit_pe.OPTIONAL_HEADER.DATA_DIRECTORY[4].Size)\n    report[\"suspect_signed\"] = bool(suspect_pe.OPTIONAL_HEADER.DATA_DIRECTORY[4].Size)\n\n    return report\n\n\ndef hash_file(filepath):\n    \"\"\"Calculate multiple hashes for a file.\"\"\"\n    hashes = {}\n    with open(filepath, 'rb') as f:\n        data = f.read()\n    for algo in ['md5', 'sha1', 'sha256']:\n        h = hashlib.new(algo)\n        h.update(data)\n        hashes[algo] = h.hexdigest()\n    return hashes\n\n\nif __name__ == \"__main__\":\n    if len(sys.argv) \u003C 3:\n        print(f\"Usage: {sys.argv[0]} \u003Clegitimate_binary> \u003Csuspect_binary>\")\n        sys.exit(1)\n    report = compare_pe_files(sys.argv[1], sys.argv[2])\n    print(json.dumps(report, indent=2))\n```\n\n## Validation Criteria\n\n- Trojanized components identified through binary diffing\n- Injected code isolated and analyzed separately\n- Code signing anomalies documented\n- Infection timeline reconstructed from build artifacts\n- Downstream impact scope assessed across affected systems\n- IOCs extracted for detection and blocking\n\n## References\n\n- [ReversingLabs - 3CX Supply Chain Analysis](https:\u002F\u002Fwww.reversinglabs.com\u002Fblog\u002Fwhat-went-wrong-with-the-3cx-software-supply-chain-attack-and-how-it-could-have-been-prevented)\n- [Fortinet - SolarWinds Supply Chain Attack](https:\u002F\u002Fwww.fortinet.com\u002Fresources\u002Fcyberglossary\u002Fsolarwinds-cyber-attack)\n- [Picus - 3CX SmoothOperator Analysis](https:\u002F\u002Fwww.picussecurity.com\u002Fresource\u002Fblog\u002Fsmoothoperator-analysis-of-3cxdesktopapp-supply-chain-attack)\n- [MITRE ATT&CK T1195 - Supply Chain Compromise](https:\u002F\u002Fattack.mitre.org\u002Ftechniques\u002FT1195\u002F)\n",{"name":5,"tags":42,"author":43,"domain":28,"license":15,"version":44,"nist_csf":45,"subdomain":30,"description":7,"nist_ai_rmf":50,"mitre_attack":54,"atlas_techniques":60,"d3fend_techniques":62},[31,30,32,33,34,35,36],"mahipal","1.0",[46,47,48,49],"DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01",[51,52,53],"GOVERN-5.2","MAP-1.6","MANAGE-2.2",[55,56,57,58,59],"T1195.002","T1195.001","T1554","T1553.002","T1027",[61],"AML.T0010",[63,64,65,66,67],"Platform Hardening","Hardware Component Inventory","Restore Object","Electromagnetic Radiation Hardening","RF Shielding","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fanalyzing-supply-chain-malware-artifacts",4384,"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":79,"prompt":89,"zipAvailable":90},[80,83,86],{"tool":81,"command":82},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-supply-chain-malware-artifacts",{"tool":84,"command":85},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-supply-chain-malware-artifacts",{"tool":87,"command":88},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-supply-chain-malware-artifacts","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002FSKILL.md",true,[92,98,103,109,113,117],{"path":93,"resourceType":94,"resourceTypeDesc":95,"sizeBytes":96,"sourceHtmlUrl":97},"assets\u002Ftemplate.md","ASSET","资产文件",421,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002Fassets\u002Ftemplate.md",{"path":99,"resourceType":99,"resourceTypeDesc":100,"sizeBytes":101,"sourceHtmlUrl":102},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002FLICENSE",{"path":104,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":107,"sourceHtmlUrl":108},"references\u002Fapi-reference.md","REFERENCE","参考文档",2181,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002Freferences\u002Fapi-reference.md",{"path":110,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":111,"sourceHtmlUrl":112},"references\u002Fstandards.md",309,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002Freferences\u002Fstandards.md",{"path":114,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":115,"sourceHtmlUrl":116},"references\u002Fworkflows.md",468,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002Freferences\u002Fworkflows.md",{"path":118,"resourceType":119,"resourceTypeDesc":120,"sizeBytes":121,"sourceHtmlUrl":122},"scripts\u002Fagent.py","SCRIPT","脚本",5733,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-supply-chain-malware-artifacts\u002Fscripts\u002Fagent.py",[124,149,173,201,227,254],{"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":6,"sourceHtmlUrl":128,"categories":129,"keywords":131,"publishedAt":37},"01M6AGDM3HJXTKXX15ZZ0ZVCJ3","verifying-build-provenance-with-slsa-sigstore","Verifies 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",[130],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[132,133,134,135,136,28,137,138,139,140,24,141,31,142,143,144,145,146,147,148],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","security","incident response","identity","pr","code","ci","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":153,"categories":154,"keywords":156,"publishedAt":37},"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",[155],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[157,145,158,159,136,160,28,139,161,162,163,164,165,166,167,168,169,170,171,172],"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":174,"name":175,"nameZh":6,"description":176,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":177,"categories":178,"keywords":183,"publishedAt":37},"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",[179,182],{"categoryNo":180,"categoryName":181,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[167,184,185,186,187,28,188,189,161,190,191,192,193,194,195,196,197,198,199,200],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","detection","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":202,"name":203,"nameZh":6,"description":204,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":205,"categories":206,"keywords":208,"publishedAt":37},"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",[207],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[209,210,211,28,212,213,214,215,216,217,218,219,220,221,222,223,164,224,225,226],"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":228,"name":229,"nameZh":6,"description":230,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":231,"categories":232,"keywords":234,"publishedAt":37},"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",[233],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[235,236,237,28,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253],"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":255,"name":256,"nameZh":6,"description":257,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":258,"categories":259,"keywords":261,"publishedAt":37},"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",[260],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[136,262,28,263,264,265,266,267,268,269,270,196,271,197,272,273,274,275,276,277],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]