[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADPMC08VZ39Q7J168MS1HV":3,"skill-same:01M6ADPMC08VZ39Q7J168MS1HV":134},{"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":26,"publishedAt":46,"linkOnly":47,"markdownContent":48,"markdownBody":49,"frontMatter":50,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":68,"repositoryHtmlUrl":69,"repositoryHomepageUrl":70,"ownerHtmlUrl":71,"ownerBlogUrl":72,"ownerDescription":73,"updatedAt":74,"install":75,"resources":88},"01M6ADPMC08VZ39Q7J168MS1HV","analyzing-malicious-pdf-with-peepdf",null,"Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects. Use when triaging a suspicious PDF attachment from a phishing email, analyzing a PDF-based exploit document, or building detection signatures for weaponized PDF threats.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",36078,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-malicious-pdf-with-peepdf\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45],"malicious","analyzing malicious pdf with peepdf","PDF","reverse-engineering","dfir","pdf-parser","pdfid","peepdf","malware-analysis","phishing","malware","suspicious","static-analysis","engineering","email","documents","javascript","cybersecurity","static analysis","2026-11-10 10:12:30",false,"---\nname: analyzing-malicious-pdf-with-peepdf\ndescription: Perform static analysis of malicious PDF documents using peepdf, pdfid,\n  and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.\n  Use when triaging a suspicious PDF attachment from a phishing email, analyzing a\n  PDF-based exploit document, or building detection signatures for weaponized PDF\n  threats.\ndomain: cybersecurity\nsubdomain: malware-analysis\ntags:\n- malware-analysis\n- pdf\n- peepdf\n- pdfid\n- pdf-parser\n- static-analysis\n- reverse-engineering\n- dfir\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- DE.AE-02\n- RS.AN-03\n- ID.RA-01\n- DE.CM-01\nmitre_attack:\n- T1204.002\n- T1059.007\n- T1027\n- T1106\n---\n\n# Analyzing Malicious PDF with peepdf\n\n## When to Use\n\n- When triaging suspicious PDF attachments from phishing emails\n- During malware analysis of PDF-based exploit documents\n- When extracting embedded JavaScript, shellcode, or executables from PDFs\n- For forensic examination of weaponized document artifacts\n- When building detection signatures for PDF-based threats\n\n## Prerequisites\n\n- Python 3.8+ with peepdf-3 installed (pip install peepdf-3)\n- pdfid.py and pdf-parser.py from Didier Stevens suite\n- Isolated analysis environment (VM or sandbox)\n- Optional: PyV8 for JavaScript emulation within peepdf\n- Optional: Pylibemu for shellcode analysis\n\n## Workflow\n\n1. **Triage with pdfid**: Scan PDF for suspicious keywords (\u002FJS, \u002FJavaScript, \u002FOpenAction, \u002FLaunch, \u002FEmbeddedFile).\n2. **Interactive Analysis**: Open PDF in peepdf interactive mode to explore object structure.\n3. **Identify Suspicious Objects**: Locate objects containing JavaScript, streams, or encoded data.\n4. **Extract Content**: Dump suspicious streams and decode filters (FlateDecode, ASCIIHexDecode).\n5. **Deobfuscate JavaScript**: Analyze extracted JS for shellcode, heap sprays, or exploit code.\n6. **Check VirusTotal**: Use peepdf vtcheck to cross-reference file hash with AV detections.\n7. **Generate IOCs**: Extract URLs, domains, hashes, and shellcode signatures.\n\n## Key Concepts\n\n| Concept | Description |\n|---------|-------------|\n| \u002FOpenAction | Automatic action executed when PDF is opened |\n| \u002FJavaScript \u002FJS | Embedded JavaScript code in PDF objects |\n| \u002FLaunch | Action that launches external applications |\n| \u002FEmbeddedFile | File embedded within the PDF structure |\n| FlateDecode | zlib compression filter used to hide content |\n| Object Streams | PDF objects stored in compressed streams |\n\n## Tools & Systems\n\n| Tool | Purpose |\n|------|---------|\n| peepdf \u002F peepdf-3 | Interactive PDF analysis with JS emulation |\n| pdfid.py | Quick triage scanning for suspicious keywords |\n| pdf-parser.py | Deep object-level PDF parsing |\n| VirusTotal | Hash lookup and AV detection cross-reference |\n| CyberChef | Decode and transform extracted payloads |\n\n## Output Format\n\n```\nAnalysis Report: PDF-MAL-[DATE]-[SEQ]\nFile: [filename.pdf]\nSHA-256: [hash]\nSuspicious Keywords: [\u002FJS, \u002FOpenAction, etc.]\nObjects with JavaScript: [Object IDs]\nExtracted URLs: [List]\nShellcode Detected: [Yes\u002FNo]\nEmbedded Files: [Count and types]\nVirusTotal Detections: [X\u002FY engines]\nRisk Level: [Critical\u002FHigh\u002FMedium\u002FLow]\n```\n","# Analyzing Malicious PDF with peepdf\n\n## When to Use\n\n- When triaging suspicious PDF attachments from phishing emails\n- During malware analysis of PDF-based exploit documents\n- When extracting embedded JavaScript, shellcode, or executables from PDFs\n- For forensic examination of weaponized document artifacts\n- When building detection signatures for PDF-based threats\n\n## Prerequisites\n\n- Python 3.8+ with peepdf-3 installed (pip install peepdf-3)\n- pdfid.py and pdf-parser.py from Didier Stevens suite\n- Isolated analysis environment (VM or sandbox)\n- Optional: PyV8 for JavaScript emulation within peepdf\n- Optional: Pylibemu for shellcode analysis\n\n## Workflow\n\n1. **Triage with pdfid**: Scan PDF for suspicious keywords (\u002FJS, \u002FJavaScript, \u002FOpenAction, \u002FLaunch, \u002FEmbeddedFile).\n2. **Interactive Analysis**: Open PDF in peepdf interactive mode to explore object structure.\n3. **Identify Suspicious Objects**: Locate objects containing JavaScript, streams, or encoded data.\n4. **Extract Content**: Dump suspicious streams and decode filters (FlateDecode, ASCIIHexDecode).\n5. **Deobfuscate JavaScript**: Analyze extracted JS for shellcode, heap sprays, or exploit code.\n6. **Check VirusTotal**: Use peepdf vtcheck to cross-reference file hash with AV detections.\n7. **Generate IOCs**: Extract URLs, domains, hashes, and shellcode signatures.\n\n## Key Concepts\n\n| Concept | Description |\n|---------|-------------|\n| \u002FOpenAction | Automatic action executed when PDF is opened |\n| \u002FJavaScript \u002FJS | Embedded JavaScript code in PDF objects |\n| \u002FLaunch | Action that launches external applications |\n| \u002FEmbeddedFile | File embedded within the PDF structure |\n| FlateDecode | zlib compression filter used to hide content |\n| Object Streams | PDF objects stored in compressed streams |\n\n## Tools & Systems\n\n| Tool | Purpose |\n|------|---------|\n| peepdf \u002F peepdf-3 | Interactive PDF analysis with JS emulation |\n| pdfid.py | Quick triage scanning for suspicious keywords |\n| pdf-parser.py | Deep object-level PDF parsing |\n| VirusTotal | Hash lookup and AV detection cross-reference |\n| CyberChef | Decode and transform extracted payloads |\n\n## Output Format\n\n```\nAnalysis Report: PDF-MAL-[DATE]-[SEQ]\nFile: [filename.pdf]\nSHA-256: [hash]\nSuspicious Keywords: [\u002FJS, \u002FOpenAction, etc.]\nObjects with JavaScript: [Object IDs]\nExtracted URLs: [List]\nShellcode Detected: [Yes\u002FNo]\nEmbedded Files: [Count and types]\nVirusTotal Detections: [X\u002FY engines]\nRisk Level: [Critical\u002FHigh\u002FMedium\u002FLow]\n```\n",{"name":5,"tags":51,"author":53,"domain":44,"license":15,"version":54,"nist_csf":55,"subdomain":35,"description":7,"mitre_attack":60},[35,52,34,33,32,39,30,31],"pdf","mahipal","1.0",[56,57,58,59],"DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01",[61,62,63,64],"T1204.002","T1059.007","T1027","T1106","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fanalyzing-malicious-pdf-with-peepdf",4414,"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 analyzing-malicious-pdf-with-peepdf",{"tool":81,"command":82},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-malicious-pdf-with-peepdf",{"tool":84,"command":85},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill analyzing-malicious-pdf-with-peepdf","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-malicious-pdf-with-peepdf\u002FSKILL.md",true,[89,95,100,104,108,112,116,120,124,128],{"path":90,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":93,"sourceHtmlUrl":94},"agents\u002Fopenai.yaml","REFERENCE","参考文档",247,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Fagents\u002Fopenai.yaml",{"path":96,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":98,"sourceHtmlUrl":99},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-malicious-pdf-with-peepdf\u002FLICENSE",{"path":101,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":102,"sourceHtmlUrl":103},"references\u002Fapi-reference.md",3318,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-malicious-pdf-with-peepdf\u002Freferences\u002Fapi-reference.md",{"path":105,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":106,"sourceHtmlUrl":107},"references\u002Finsights.md",40462,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Freferences\u002Finsights.md",{"path":109,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":110,"sourceHtmlUrl":111},"references\u002Fparticipant.md",5217,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Freferences\u002Fparticipant.md",{"path":113,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":114,"sourceHtmlUrl":115},"references\u002Freport.md",2400,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Freferences\u002Freport.md",{"path":117,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":118,"sourceHtmlUrl":119},"references\u002Fstudy-plan.md",7152,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Freferences\u002Fstudy-plan.md",{"path":121,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":122,"sourceHtmlUrl":123},"references\u002Fsynthesis.md",6558,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Freferences\u002Fsynthesis.md",{"path":125,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":126,"sourceHtmlUrl":127},"references\u002Ftasks.md",40321,"https:\u002F\u002Fgithub.com\u002Fnodetool-ai\u002Fnodetool\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fux-research\u002Freferences\u002Ftasks.md",{"path":129,"resourceType":130,"resourceTypeDesc":131,"sizeBytes":132,"sourceHtmlUrl":133},"scripts\u002Fagent.py","SCRIPT","脚本",8427,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fanalyzing-malicious-pdf-with-peepdf\u002Fscripts\u002Fagent.py",[135,162,186,214,239,266],{"skillNo":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":142,"publishedAt":46},"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",[141],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[143,144,145,146,147,44,148,149,150,151,152,153,154,155,156,157,158,159,160,161],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","security","incident response","identity","pr","code","artifacts","ci","supply-chain","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"skillNo":163,"name":164,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":169,"publishedAt":46},"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",[168],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[170,158,171,172,147,173,44,150,174,175,176,177,178,179,180,181,182,183,184,185],"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":187,"name":188,"nameZh":6,"description":189,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":190,"categories":191,"keywords":196,"publishedAt":46},"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",[192,195],{"categoryNo":193,"categoryName":194,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[180,197,198,199,200,44,201,202,174,203,204,205,206,207,208,209,210,211,212,213],"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":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":221,"publishedAt":46},"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",[220],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[222,223,224,44,225,226,227,228,31,229,230,231,232,233,234,235,177,236,237,238],"windows","kape","triaging windows with kape","registry","browser","logs","windows-forensics","mft","mftecmd","data","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":240,"name":241,"nameZh":6,"description":242,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":243,"categories":244,"keywords":246,"publishedAt":46},"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",[245],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[247,248,249,44,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265],"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":267,"name":268,"nameZh":6,"description":269,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":270,"categories":271,"keywords":273,"publishedAt":46},"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",[272],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[147,274,44,275,276,277,278,279,280,281,282,209,283,210,284,285,286,287,288,289],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]