[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AF3DYYDY0N5KAY6RXN730R":3,"skill-same:01M6AF3DYYDY0N5KAY6RXN730R":116},{"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":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":62,"ownerHtmlUrl":63,"ownerBlogUrl":64,"ownerDescription":65,"updatedAt":66,"install":67,"resources":80},"01M6AF3DYYDY0N5KAY6RXN730R","implementing-diamond-model-analysis",null,"The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads, and generate pivot-ready intelligence.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35990,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fimplementing-diamond-model-analysis\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],"implementing diamond model analysis","cybersecurity","infrastructure","core","generate","framework","mitre-attack","threat-intelligence","cti","ioc","stix","intrusion-analysis","analyzing","diamond-model","2026-11-10 10:12:30",false,"---\nname: implementing-diamond-model-analysis\ndescription: The Diamond Model of Intrusion Analysis provides a structured framework\n  for analyzing cyber intrusions by examining four core features - Adversary, Capability,\n  Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically\n  to classify and correlate intrusion events, build activity threads, and generate\n  pivot-ready intelligence.\ndomain: cybersecurity\nsubdomain: threat-intelligence\ntags:\n- threat-intelligence\n- cti\n- ioc\n- mitre-attack\n- stix\n- diamond-model\n- intrusion-analysis\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- ID.RA-01\n- ID.RA-05\n- DE.CM-01\n- DE.AE-02\nmitre_attack:\n- T1591\n- T1592\n- T1593\n- T1589\n- T0816\n---\n# Implementing Diamond Model Analysis\n\n## Overview\n\nThe Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features: Adversary, Capability, Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads linking related events, create activity-attack graphs, and generate pivot-ready intelligence from intrusion data.\n\n\n## When to Use\n\n- When deploying or configuring implementing diamond model analysis capabilities in your environment\n- When establishing security controls aligned to compliance requirements\n- When building or improving security architecture for this domain\n- When conducting security assessments that require this implementation\n\n## Prerequisites\n\n- Python 3.9+ with `networkx`, `stix2`, `graphviz` libraries\n- Understanding of the Diamond Model core and meta-features\n- Access to threat intelligence data (MISP\u002FOpenCTI events)\n- Familiarity with MITRE ATT&CK for capability mapping\n\n## Key Concepts\n\n### Diamond Model Core Features\n- **Adversary**: The threat actor or operator conducting the intrusion\n- **Capability**: The tools, techniques, and malware used (maps to ATT&CK)\n- **Infrastructure**: C2 servers, domains, email addresses, hosting providers\n- **Victim**: Target organization, system, person, or data asset\n\n### Meta-Features\n- **Timestamp**: When the event occurred\n- **Phase**: Kill chain stage (recon, delivery, exploitation, etc.)\n- **Result**: Success, failure, or unknown\n- **Direction**: Adversary-to-infrastructure, infrastructure-to-victim, etc.\n- **Methodology**: Social engineering, technical exploit, insider threat\n- **Resources**: Financial, human, technical resources required\n\n### Activity Threads and Groups\n- **Activity Thread**: Sequence of Diamond events from a single adversary operation\n- **Activity Group**: Cluster of threads attributed to the same adversary\n\n## Workflow\n\n### Step 1: Define Diamond Event Data Structure\n\n```python\nfrom dataclasses import dataclass, field\nfrom datetime import datetime\nfrom typing import Optional\nimport json\nimport uuid\n\n@dataclass\nclass DiamondEvent:\n    adversary: str = \"\"\n    capability: str = \"\"\n    infrastructure: str = \"\"\n    victim: str = \"\"\n    timestamp: str = \"\"\n    phase: str = \"\"\n    result: str = \"\"\n    direction: str = \"\"\n    methodology: str = \"\"\n    confidence: int = 0\n    notes: str = \"\"\n    event_id: str = field(default_factory=lambda: str(uuid.uuid4())[:8])\n    mitre_techniques: list = field(default_factory=list)\n    iocs: list = field(default_factory=list)\n\n    def to_dict(self):\n        return {\n            \"event_id\": self.event_id,\n            \"adversary\": self.adversary,\n            \"capability\": self.capability,\n            \"infrastructure\": self.infrastructure,\n            \"victim\": self.victim,\n            \"timestamp\": self.timestamp,\n            \"phase\": self.phase,\n            \"result\": self.result,\n            \"direction\": self.direction,\n            \"methodology\": self.methodology,\n            \"confidence\": self.confidence,\n            \"mitre_techniques\": self.mitre_techniques,\n            \"iocs\": self.iocs,\n            \"notes\": self.notes,\n        }\n```\n\n### Step 2: Build Activity Thread from Events\n\n```python\nimport networkx as nx\n\nclass DiamondAnalysis:\n    def __init__(self):\n        self.events = []\n        self.graph = nx.DiGraph()\n\n    def add_event(self, event: DiamondEvent):\n        self.events.append(event)\n        self.graph.add_node(event.event_id, **event.to_dict())\n\n    def build_activity_thread(self):\n        \"\"\"Link events chronologically into activity threads.\"\"\"\n        sorted_events = sorted(self.events, key=lambda e: e.timestamp)\n        for i in range(len(sorted_events) - 1):\n            self.graph.add_edge(\n                sorted_events[i].event_id,\n                sorted_events[i + 1].event_id,\n                relationship=\"followed_by\",\n            )\n\n    def find_pivots(self):\n        \"\"\"Find pivot points where events share infrastructure or capabilities.\"\"\"\n        pivots = {\"infrastructure\": {}, \"capability\": {}, \"adversary\": {}}\n\n        for event in self.events:\n            if event.infrastructure:\n                pivots[\"infrastructure\"].setdefault(event.infrastructure, []).append(event.event_id)\n            if event.capability:\n                pivots[\"capability\"].setdefault(event.capability, []).append(event.event_id)\n            if event.adversary:\n                pivots[\"adversary\"].setdefault(event.adversary, []).append(event.event_id)\n\n        return {\n            k: {pk: pv for pk, pv in v.items() if len(pv) > 1}\n            for k, v in pivots.items()\n        }\n\n    def generate_report(self):\n        return {\n            \"total_events\": len(self.events),\n            \"unique_adversaries\": len(set(e.adversary for e in self.events if e.adversary)),\n            \"unique_victims\": len(set(e.victim for e in self.events if e.victim)),\n            \"unique_infrastructure\": len(set(e.infrastructure for e in self.events if e.infrastructure)),\n            \"pivots\": self.find_pivots(),\n            \"events\": [e.to_dict() for e in self.events],\n        }\n```\n\n## Validation Criteria\n\n- Diamond events capture all four core features with meta-features\n- Activity threads link related events chronologically\n- Pivot analysis identifies shared infrastructure and capabilities across events\n- Graph visualization renders the activity-attack graph correctly\n- Events map to MITRE ATT&CK techniques for capability classification\n\n## References\n\n- [Diamond Model Paper](https:\u002F\u002Fwww.activeresponse.org\u002Fwp-content\u002Fuploads\u002F2013\u002F07\u002Fdiamond.pdf)\n- [MITRE ATT&CK](https:\u002F\u002Fattack.mitre.org\u002F)\n- [STIX 2.1 Campaign Object](https:\u002F\u002Fdocs.oasis-open.org\u002Fcti\u002Fstix\u002Fv2.1\u002Fstix-v2.1.html)\n","# Implementing Diamond Model Analysis\n\n## Overview\n\nThe Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features: Adversary, Capability, Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads linking related events, create activity-attack graphs, and generate pivot-ready intelligence from intrusion data.\n\n\n## When to Use\n\n- When deploying or configuring implementing diamond model analysis capabilities in your environment\n- When establishing security controls aligned to compliance requirements\n- When building or improving security architecture for this domain\n- When conducting security assessments that require this implementation\n\n## Prerequisites\n\n- Python 3.9+ with `networkx`, `stix2`, `graphviz` libraries\n- Understanding of the Diamond Model core and meta-features\n- Access to threat intelligence data (MISP\u002FOpenCTI events)\n- Familiarity with MITRE ATT&CK for capability mapping\n\n## Key Concepts\n\n### Diamond Model Core Features\n- **Adversary**: The threat actor or operator conducting the intrusion\n- **Capability**: The tools, techniques, and malware used (maps to ATT&CK)\n- **Infrastructure**: C2 servers, domains, email addresses, hosting providers\n- **Victim**: Target organization, system, person, or data asset\n\n### Meta-Features\n- **Timestamp**: When the event occurred\n- **Phase**: Kill chain stage (recon, delivery, exploitation, etc.)\n- **Result**: Success, failure, or unknown\n- **Direction**: Adversary-to-infrastructure, infrastructure-to-victim, etc.\n- **Methodology**: Social engineering, technical exploit, insider threat\n- **Resources**: Financial, human, technical resources required\n\n### Activity Threads and Groups\n- **Activity Thread**: Sequence of Diamond events from a single adversary operation\n- **Activity Group**: Cluster of threads attributed to the same adversary\n\n## Workflow\n\n### Step 1: Define Diamond Event Data Structure\n\n```python\nfrom dataclasses import dataclass, field\nfrom datetime import datetime\nfrom typing import Optional\nimport json\nimport uuid\n\n@dataclass\nclass DiamondEvent:\n    adversary: str = \"\"\n    capability: str = \"\"\n    infrastructure: str = \"\"\n    victim: str = \"\"\n    timestamp: str = \"\"\n    phase: str = \"\"\n    result: str = \"\"\n    direction: str = \"\"\n    methodology: str = \"\"\n    confidence: int = 0\n    notes: str = \"\"\n    event_id: str = field(default_factory=lambda: str(uuid.uuid4())[:8])\n    mitre_techniques: list = field(default_factory=list)\n    iocs: list = field(default_factory=list)\n\n    def to_dict(self):\n        return {\n            \"event_id\": self.event_id,\n            \"adversary\": self.adversary,\n            \"capability\": self.capability,\n            \"infrastructure\": self.infrastructure,\n            \"victim\": self.victim,\n            \"timestamp\": self.timestamp,\n            \"phase\": self.phase,\n            \"result\": self.result,\n            \"direction\": self.direction,\n            \"methodology\": self.methodology,\n            \"confidence\": self.confidence,\n            \"mitre_techniques\": self.mitre_techniques,\n            \"iocs\": self.iocs,\n            \"notes\": self.notes,\n        }\n```\n\n### Step 2: Build Activity Thread from Events\n\n```python\nimport networkx as nx\n\nclass DiamondAnalysis:\n    def __init__(self):\n        self.events = []\n        self.graph = nx.DiGraph()\n\n    def add_event(self, event: DiamondEvent):\n        self.events.append(event)\n        self.graph.add_node(event.event_id, **event.to_dict())\n\n    def build_activity_thread(self):\n        \"\"\"Link events chronologically into activity threads.\"\"\"\n        sorted_events = sorted(self.events, key=lambda e: e.timestamp)\n        for i in range(len(sorted_events) - 1):\n            self.graph.add_edge(\n                sorted_events[i].event_id,\n                sorted_events[i + 1].event_id,\n                relationship=\"followed_by\",\n            )\n\n    def find_pivots(self):\n        \"\"\"Find pivot points where events share infrastructure or capabilities.\"\"\"\n        pivots = {\"infrastructure\": {}, \"capability\": {}, \"adversary\": {}}\n\n        for event in self.events:\n            if event.infrastructure:\n                pivots[\"infrastructure\"].setdefault(event.infrastructure, []).append(event.event_id)\n            if event.capability:\n                pivots[\"capability\"].setdefault(event.capability, []).append(event.event_id)\n            if event.adversary:\n                pivots[\"adversary\"].setdefault(event.adversary, []).append(event.event_id)\n\n        return {\n            k: {pk: pv for pk, pv in v.items() if len(pv) > 1}\n            for k, v in pivots.items()\n        }\n\n    def generate_report(self):\n        return {\n            \"total_events\": len(self.events),\n            \"unique_adversaries\": len(set(e.adversary for e in self.events if e.adversary)),\n            \"unique_victims\": len(set(e.victim for e in self.events if e.victim)),\n            \"unique_infrastructure\": len(set(e.infrastructure for e in self.events if e.infrastructure)),\n            \"pivots\": self.find_pivots(),\n            \"events\": [e.to_dict() for e in self.events],\n        }\n```\n\n## Validation Criteria\n\n- Diamond events capture all four core features with meta-features\n- Activity threads link related events chronologically\n- Pivot analysis identifies shared infrastructure and capabilities across events\n- Graph visualization renders the activity-attack graph correctly\n- Events map to MITRE ATT&CK techniques for capability classification\n\n## References\n\n- [Diamond Model Paper](https:\u002F\u002Fwww.activeresponse.org\u002Fwp-content\u002Fuploads\u002F2013\u002F07\u002Fdiamond.pdf)\n- [MITRE ATT&CK](https:\u002F\u002Fattack.mitre.org\u002F)\n- [STIX 2.1 Campaign Object](https:\u002F\u002Fdocs.oasis-open.org\u002Fcti\u002Fstix\u002Fv2.1\u002Fstix-v2.1.html)\n",{"name":5,"tags":43,"author":44,"domain":25,"license":15,"version":45,"nist_csf":46,"subdomain":31,"description":7,"mitre_attack":51},[31,32,33,30,34,37,35],"mahipal","1.0",[47,48,49,50],"ID.RA-01","ID.RA-05","DE.CM-01","DE.AE-02",[52,53,54,55,56],"T1591","T1592","T1593","T1589","T0816","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fimplementing-diamond-model-analysis",4395,"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":68,"prompt":78,"zipAvailable":79},[69,72,75],{"tool":70,"command":71},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills 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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",[123],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[125,126,127,128,129,25,130,131,132,133,134,135,136,137,138,139,140,141,142,143],"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":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":151,"publishedAt":38},"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",[150],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[152,140,153,154,129,155,25,132,156,157,158,159,160,161,162,163,164,165,166,167],"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":169,"name":170,"nameZh":6,"description":171,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":172,"categories":173,"keywords":178,"publishedAt":38},"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",[174,177],{"categoryNo":175,"categoryName":176,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[162,179,180,181,182,25,26,183,156,184,185,186,187,188,189,190,191,192,193,194],"backup","recovery","validating backup integrity for recovery","testing","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","detection","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":196,"name":197,"nameZh":6,"description":198,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":199,"categories":200,"keywords":202,"publishedAt":38},"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",[201],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[203,204,205,25,206,207,208,209,210,211,212,213,214,215,216,217,159,218,219,220],"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":222,"name":223,"nameZh":6,"description":224,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":225,"categories":226,"keywords":228,"publishedAt":38},"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",[227],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[229,29,230,25,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246],"vulnerabilities","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":248,"name":249,"nameZh":6,"description":250,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":251,"categories":252,"keywords":254,"publishedAt":38},"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",[253],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[129,255,25,256,257,33,258,259,260,261,262,190,263,191,264,265,266,267,268,269],"triaging security incident","siem","file","soc","NIST-800-61","NIST","severity","edr","execution","analysis","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]