[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71DR9S1ZSXGZQNHMSZJC42Q":3,"skill-same:01M71DR9S1ZSXGZQNHMSZJC42Q":93},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":66,"commitSha":67,"skillDirectory":68,"forksCount":14,"repositoryHtmlUrl":69,"repositoryHomepageUrl":6,"ownerHtmlUrl":70,"ownerBlogUrl":6,"ownerDescription":71,"updatedAt":72,"install":73,"resources":86},"01M71DR9S1ZSXGZQNHMSZJC42Q","ics-asset-management-claroty-assess-audit",null,"This skill covers performing vulnerability assessments in OT environments using the Claroty xDome platform for comprehensive asset discovery, risk scoring, vulnerability correlation, and remediation prioritization. It addresses passive vulnerability identification through traffic analysis, active safe querying of OT devices, integration with CVE databases and ICS-CERT advisories, and risk-based prioritization that accounts for operational impact and compensating controls.","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\u002Findustrial\u002Fics\u002Fasset-management\u002Fclaroty\u002Fassess\u002Faudit\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"management","ics asset management claroty assess audit","asset","assess","claroty","ics","audit","analysis","xdome","vulnerability","prioritization","Bash","cybersecurity","cm","databases","scoring","impact","de","traffic","assessment","2026-11-10 10:12:30",false,"---\nname: ics-asset-management-claroty-assess-audit\ndescription: This skill covers performing vulnerability assessments in OT environments using the Claroty xDome platform for comprehensive asset discovery, risk scoring, vulnerability correlation, and remediation prioritization. It addresses passive vulnerability identification through traffic analysis, active safe querying of OT devices, integration with CVE databases and ICS-CERT advisories, and risk-based prioritization that accounts for operational impact and compensating controls.\ndomain: cybersecurity\nsubdomain: ot-ics-security\ntags:\n- ot-security\n- ics\n- scada\n- industrial-control\n- iec62443\n- vulnerability-assessment\n- claroty\nnist_csf:\n- PR.IR-01\n- DE.CM-01\n- ID.AM-05\n- GV.OC-02\nmodel: sonnet\nmaxTurns: 20\ntools: [Read, Bash, Glob, Grep]\nmitre_attack:\n- T0855\n- T1082\ncapec: []\n---\n\n# Performing OT Vulnerability Assessment with Claroty\n\n## When to Use\n\n- When conducting scheduled OT vulnerability assessments per IEC 62443 or NERC CIP requirements\n- When deploying Claroty xDome for the first time and performing initial asset discovery and risk assessment\n- When correlating newly published ICS-CERT advisories against your OT asset inventory\n- When prioritizing OT vulnerability remediation with limited maintenance windows\n- When generating compliance evidence for CIP-010-4 vulnerability assessment requirements\n\n**Do not use** for active vulnerability scanning of PLCs and safety systems (see performing-ot-network-security-assessment for passive approaches), for IT-only vulnerability management (see standard vulnerability scanners), or for penetration testing (see performing-ics-penetration-testing).\n\n## Prerequisites\n\n- Claroty xDome or CTD (Continuous Threat Detection) deployed with sensors on OT network\n- Network SPAN\u002FTAP access for passive asset discovery\n- CISA ICS-CERT advisory subscription for vulnerability tracking\n- Asset inventory with firmware versions for all OT devices\n- Change management process for patch deployment during maintenance windows\n\n## Workflow\n\n### Step 1: Configure Asset Discovery and Vulnerability Correlation\n\nConfigure Claroty to perform passive and active-safe discovery to build complete asset inventory with firmware versions for vulnerability correlation.\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"OT Vulnerability Assessment Manager.\n\nCorrelates OT asset inventory with ICS-CERT advisories and CVE data\nto identify, prioritize, and track OT vulnerabilities. Designed to\nintegrate with Claroty xDome API or standalone operation.\n\"\"\"\n\nimport json\nimport sys\nfrom collections import defaultdict\nfrom dataclasses import dataclass, field, asdict\nfrom datetime import datetime\n\nimport requests\n\n\n@dataclass\nclass OTAsset:\n    asset_id: str\n    name: str\n    vendor: str\n    model: str\n    firmware_version: str\n    asset_type: str  # PLC, HMI, RTU, historian, switch, etc.\n    purdue_level: str\n    ip_address: str\n    protocol: str\n    criticality: str  # critical, high, medium, low\n    zone: str\n\n\n@dataclass\nclass OTVulnerability:\n    vuln_id: str\n    cve_id: str\n    title: str\n    severity: str  # critical, high, medium, low\n    cvss_score: float\n    affected_vendor: str\n    affected_product: str\n    affected_versions: str\n    description: str\n    ics_cert_advisory: str = \"\"\n    remediation: str = \"\"\n    patch_available: bool = False\n    compensating_controls: str = \"\"\n\n\n@dataclass\nclass RiskAssessment:\n    asset: OTAsset\n    vulnerability: OTVulnerability\n    risk_score: float = 0.0\n    risk_rating: str = \"\"\n    exploitability: str = \"\"\n    operational_impact: str = \"\"\n    compensating_controls: list = field(default_factory=list)\n    remediation_priority: int = 0\n\n\nclass OTVulnerabilityAssessment:\n    \"\"\"OT vulnerability assessment and prioritization engine.\"\"\"\n\n    def __init__(self):\n        self.assets = []\n        self.vulnerabilities = []\n        self.risk_assessments = []\n\n    def load_assets(self, assets_data):\n        \"\"\"Load asset inventory from Claroty export or manual inventory.\"\"\"\n        for a in assets_data:\n            self.assets.append(OTAsset(**a))\n        print(f\"[*] Loaded {len(self.assets)} OT assets\")\n\n    def fetch_ics_advisories(self):\n        \"\"\"Fetch latest ICS-CERT advisories from CISA.\"\"\"\n        print(\"[*] Fetching ICS-CERT advisories from CISA...\")\n        try:\n            # CISA Known Exploited Vulnerabilities catalog\n            url = \"https:\u002F\u002Fwww.cisa.gov\u002Fsites\u002Fdefault\u002Ffiles\u002Ffeeds\u002Fknown_exploited_vulnerabilities.json\"\n            resp = requests.get(url, timeout=30)\n            resp.raise_for_status()\n            data = resp.json()\n\n            ics_vulns = []\n            for vuln in data.get(\"vulnerabilities\", []):\n                # Filter for ICS-relevant vendors\n                ics_vendors = [\n                    \"siemens\", \"schneider\", \"rockwell\", \"honeywell\",\n                    \"abb\", \"ge\", \"emerson\", \"yokogawa\", \"omron\",\n                    \"mitsubishi\", \"phoenix\", \"moxa\", \"advantech\",\n                ]\n                vendor = vuln.get(\"vendorProject\", \"\").lower()\n                if any(v in vendor for v in ics_vendors):\n                    ics_vulns.append(vuln)\n\n            print(f\"  Found {len(ics_vulns)} ICS-relevant known exploited vulnerabilities\")\n            return ics_vulns\n\n        except Exception as e:\n            print(f\"[WARN] Could not fetch advisories: {e}\")\n            return []\n\n    def correlate_vulnerabilities(self):\n        \"\"\"Match vulnerabilities to assets based on vendor\u002Fmodel\u002Ffirmware.\"\"\"\n        print(\"[*] Correlating vulnerabilities to assets...\")\n\n        for asset in self.assets:\n            for vuln in self.vulnerabilities:\n                if (vuln.affected_vendor.lower() in asset.vendor.lower() and\n                    vuln.affected_product.lower() in asset.model.lower()):\n                    # Check firmware version if specified\n                    ra = RiskAssessment(asset=asset, vulnerability=vuln)\n                    self._calculate_risk_score(ra)\n                    self.risk_assessments.append(ra)\n\n        print(f\"  Correlated {len(self.risk_assessments)} asset-vulnerability pairs\")\n\n    def _calculate_risk_score(self, ra):\n        \"\"\"Calculate OT-specific risk score considering operational impact.\"\"\"\n        # Base score from CVSS\n        base = ra.vulnerability.cvss_score\n\n        # Criticality multiplier based on asset function\n        criticality_weights = {\n            \"critical\": 1.5,  # SIS, safety systems\n            \"high\": 1.3,      # PLCs, primary control\n            \"medium\": 1.0,    # HMIs, historians\n            \"low\": 0.7,       # non-critical support systems\n        }\n        criticality = criticality_weights.get(ra.asset.criticality, 1.0)\n\n        # Purdue level proximity factor (lower levels = higher risk)\n        level_weights = {\n            \"Level 0-1\": 1.5,\n            \"Level 2\": 1.3,\n            \"Level 3\": 1.0,\n            \"Level 3.5\": 0.8,\n            \"Level 4\": 0.6,\n        }\n        level_factor = level_weights.get(ra.asset.purdue_level, 1.0)\n\n        # Network exposure reduction if compensating controls exist\n        comp_reduction = 0.8 if ra.compensating_controls else 1.0\n\n        ra.risk_score = round(base * criticality * level_factor * comp_reduction, 1)\n        ra.risk_score = min(ra.risk_score, 10.0)\n\n        if ra.risk_score >= 9.0:\n            ra.risk_rating = \"critical\"\n            ra.remediation_priority = 1\n        elif ra.risk_score >= 7.0:\n            ra.risk_rating = \"high\"\n            ra.remediation_priority = 2\n        elif ra.risk_score >= 4.0:\n            ra.risk_rating = \"medium\"\n            ra.remediation_priority = 3\n        else:\n            ra.risk_rating = \"low\"\n            ra.remediation_priority = 4\n\n    def generate_report(self):\n        \"\"\"Generate vulnerability assessment report.\"\"\"\n        # Sort by risk score descending\n        sorted_ra = sorted(self.risk_assessments, key=lambda x: -x.risk_score)\n\n        report = []\n        report.append(\"=\" * 70)\n        report.append(\"OT VULNERABILITY ASSESSMENT REPORT\")\n        report.append(f\"Date: {datetime.now().isoformat()}\")\n        report.append(f\"Assets: {len(self.assets)} | Vulnerabilities: {len(self.vulnerabilities)}\")\n        report.append(f\"Risk Assessments: {len(self.risk_assessments)}\")\n        report.append(\"=\" * 70)\n\n        for sev in [\"critical\", \"high\", \"medium\", \"low\"]:\n            findings = [ra for ra in sorted_ra if ra.risk_rating == sev]\n            if findings:\n                report.append(f\"\\n--- {sev.upper()} RISK ({len(findings)}) ---\")\n                for ra in findings[:10]:\n                    report.append(f\"\\n  Risk Score: {ra.risk_score}\u002F10.0\")\n                    report.append(f\"  Asset: {ra.asset.name} ({ra.asset.vendor} {ra.asset.model})\")\n                    report.append(f\"  Zone: {ra.asset.zone} ({ra.asset.purdue_level})\")\n                    report.append(f\"  CVE: {ra.vulnerability.cve_id} (CVSS: {ra.vulnerability.cvss_score})\")\n                    report.append(f\"  Title: {ra.vulnerability.title}\")\n                    if ra.vulnerability.patch_available:\n                        report.append(f\"  Patch: Available - schedule for next maintenance window\")\n                    else:\n                        report.append(f\"  Patch: Not available - apply compensating controls\")\n\n        return \"\\n\".join(report)\n\n    def export_json(self, output_file):\n        \"\"\"Export assessment to JSON.\"\"\"\n        data = {\n            \"assessment_date\": datetime.now().isoformat(),\n            \"asset_count\": len(self.assets),\n            \"vulnerability_count\": len(self.vulnerabilities),\n            \"risk_assessments\": [\n                {\n                    \"asset_name\": ra.asset.name,\n                    \"asset_ip\": ra.asset.ip_address,\n                    \"cve\": ra.vulnerability.cve_id,\n                    \"risk_score\": ra.risk_score,\n                    \"risk_rating\": ra.risk_rating,\n                    \"priority\": ra.remediation_priority,\n                }\n                for ra in sorted(self.risk_assessments, key=lambda x: -x.risk_score)\n            ],\n        }\n        with open(output_file, \"w\") as f:\n            json.dump(data, f, indent=2)\n\n\nif __name__ == \"__main__\":\n    assessment = OTVulnerabilityAssessment()\n    advisories = assessment.fetch_ics_advisories()\n    print(f\"Fetched {len(advisories)} ICS advisories from CISA KEV catalog\")\n```\n\n## Key Concepts\n\n| Term | Definition |\n|------|------------|\n| Claroty xDome | Cyber-physical systems protection platform providing asset discovery, vulnerability management, and threat detection for OT\u002FIoT environments |\n| Passive Discovery | Identifying OT assets by analyzing network traffic without sending any packets, safe for production environments |\n| Safe Active Query | Querying OT devices using native industrial protocols at safe rates to collect detailed asset information without disrupting operations |\n| OT Risk Score | Risk rating that factors CVSS base score, asset criticality, Purdue level, and compensating controls for OT-appropriate prioritization |\n| ICS-CERT Advisory | CISA-published security advisories for industrial control system vulnerabilities with vendor-specific remediation guidance |\n| Virtual Patching | Deploying IPS\u002Ffirewall rules to block exploitation of known vulnerabilities when firmware patches cannot be immediately applied |\n\n## Tools & Systems\n\n- **Claroty xDome**: Comprehensive OT\u002FIoT asset discovery, vulnerability management, and continuous threat detection platform\n- **Claroty CTD**: Continuous Threat Detection sensor for passive network monitoring in OT environments\n- **CISA ICS-CERT**: US government advisory service publishing ICS vulnerability notifications and mitigation guidance\n- **Dragos Platform**: Alternative OT security platform with asset visibility and vulnerability management capabilities\n- **Nozomi Networks Guardian**: OT monitoring platform with vulnerability correlation and risk scoring\n\n## Output Format\n\n```\nOT Vulnerability Assessment Report\n=====================================\nTool: Claroty xDome \u002F Manual Assessment\nDate: YYYY-MM-DD\nAssets Scanned: [N]\n\nRISK SUMMARY:\n  Critical Risk: [N] vulnerabilities on [N] assets\n  High Risk: [N] vulnerabilities on [N] assets\n  Medium Risk: [N] vulnerabilities on [N] assets\n  Low Risk: [N] vulnerabilities on [N] assets\n\nTOP RISKS:\n  [Risk Score] [CVE-ID] on [Asset Name] ([Zone])\n    Remediation: [Patch\u002FCompensating Control]\n    Timeline: [Next maintenance window \u002F Immediate]\n```\n","# Performing OT Vulnerability Assessment with Claroty\n\n## When to Use\n\n- When conducting scheduled OT vulnerability assessments per IEC 62443 or NERC CIP requirements\n- When deploying Claroty xDome for the first time and performing initial asset discovery and risk assessment\n- When correlating newly published ICS-CERT advisories against your OT asset inventory\n- When prioritizing OT vulnerability remediation with limited maintenance windows\n- When generating compliance evidence for CIP-010-4 vulnerability assessment requirements\n\n**Do not use** for active vulnerability scanning of PLCs and safety systems (see performing-ot-network-security-assessment for passive approaches), for IT-only vulnerability management (see standard vulnerability scanners), or for penetration testing (see performing-ics-penetration-testing).\n\n## Prerequisites\n\n- Claroty xDome or CTD (Continuous Threat Detection) deployed with sensors on OT network\n- Network SPAN\u002FTAP access for passive asset discovery\n- CISA ICS-CERT advisory subscription for vulnerability tracking\n- Asset inventory with firmware versions for all OT devices\n- Change management process for patch deployment during maintenance windows\n\n## Workflow\n\n### Step 1: Configure Asset Discovery and Vulnerability Correlation\n\nConfigure Claroty to perform passive and active-safe discovery to build complete asset inventory with firmware versions for vulnerability correlation.\n\n```python\n#!\u002Fusr\u002Fbin\u002Fenv python3\n\"\"\"OT Vulnerability Assessment Manager.\n\nCorrelates OT asset inventory with ICS-CERT advisories and CVE data\nto identify, prioritize, and track OT vulnerabilities. Designed to\nintegrate with Claroty xDome API or standalone operation.\n\"\"\"\n\nimport json\nimport sys\nfrom collections import defaultdict\nfrom dataclasses import dataclass, field, asdict\nfrom datetime import datetime\n\nimport requests\n\n\n@dataclass\nclass OTAsset:\n    asset_id: str\n    name: str\n    vendor: str\n    model: str\n    firmware_version: str\n    asset_type: str  # PLC, HMI, RTU, historian, switch, etc.\n    purdue_level: str\n    ip_address: str\n    protocol: str\n    criticality: str  # critical, high, medium, low\n    zone: str\n\n\n@dataclass\nclass OTVulnerability:\n    vuln_id: str\n    cve_id: str\n    title: str\n    severity: str  # critical, high, medium, low\n    cvss_score: float\n    affected_vendor: str\n    affected_product: str\n    affected_versions: str\n    description: str\n    ics_cert_advisory: str = \"\"\n    remediation: str = \"\"\n    patch_available: bool = False\n    compensating_controls: str = \"\"\n\n\n@dataclass\nclass RiskAssessment:\n    asset: OTAsset\n    vulnerability: OTVulnerability\n    risk_score: float = 0.0\n    risk_rating: str = \"\"\n    exploitability: str = \"\"\n    operational_impact: str = \"\"\n    compensating_controls: list = field(default_factory=list)\n    remediation_priority: int = 0\n\n\nclass OTVulnerabilityAssessment:\n    \"\"\"OT vulnerability assessment and prioritization engine.\"\"\"\n\n    def __init__(self):\n        self.assets = []\n        self.vulnerabilities = []\n        self.risk_assessments = []\n\n    def load_assets(self, assets_data):\n        \"\"\"Load asset inventory from Claroty export or manual inventory.\"\"\"\n        for a in assets_data:\n            self.assets.append(OTAsset(**a))\n        print(f\"[*] Loaded {len(self.assets)} OT assets\")\n\n    def fetch_ics_advisories(self):\n        \"\"\"Fetch latest ICS-CERT advisories from CISA.\"\"\"\n        print(\"[*] Fetching ICS-CERT advisories from CISA...\")\n        try:\n            # CISA Known Exploited Vulnerabilities catalog\n            url = \"https:\u002F\u002Fwww.cisa.gov\u002Fsites\u002Fdefault\u002Ffiles\u002Ffeeds\u002Fknown_exploited_vulnerabilities.json\"\n            resp = requests.get(url, timeout=30)\n            resp.raise_for_status()\n            data = resp.json()\n\n            ics_vulns = []\n            for vuln in data.get(\"vulnerabilities\", []):\n                # Filter for ICS-relevant vendors\n                ics_vendors = [\n                    \"siemens\", \"schneider\", \"rockwell\", \"honeywell\",\n                    \"abb\", \"ge\", \"emerson\", \"yokogawa\", \"omron\",\n                    \"mitsubishi\", \"phoenix\", \"moxa\", \"advantech\",\n                ]\n                vendor = vuln.get(\"vendorProject\", \"\").lower()\n                if any(v in vendor for v in ics_vendors):\n                    ics_vulns.append(vuln)\n\n            print(f\"  Found {len(ics_vulns)} ICS-relevant known exploited vulnerabilities\")\n            return ics_vulns\n\n        except Exception as e:\n            print(f\"[WARN] Could not fetch advisories: {e}\")\n            return []\n\n    def correlate_vulnerabilities(self):\n        \"\"\"Match vulnerabilities to assets based on vendor\u002Fmodel\u002Ffirmware.\"\"\"\n        print(\"[*] Correlating vulnerabilities to assets...\")\n\n        for asset in self.assets:\n            for vuln in self.vulnerabilities:\n                if (vuln.affected_vendor.lower() in asset.vendor.lower() and\n                    vuln.affected_product.lower() in asset.model.lower()):\n                    # Check firmware version if specified\n                    ra = RiskAssessment(asset=asset, vulnerability=vuln)\n                    self._calculate_risk_score(ra)\n                    self.risk_assessments.append(ra)\n\n        print(f\"  Correlated {len(self.risk_assessments)} asset-vulnerability pairs\")\n\n    def _calculate_risk_score(self, ra):\n        \"\"\"Calculate OT-specific risk score considering operational impact.\"\"\"\n        # Base score from CVSS\n        base = ra.vulnerability.cvss_score\n\n        # Criticality multiplier based on asset function\n        criticality_weights = {\n            \"critical\": 1.5,  # SIS, safety systems\n            \"high\": 1.3,      # PLCs, primary control\n            \"medium\": 1.0,    # HMIs, historians\n            \"low\": 0.7,       # non-critical support systems\n        }\n        criticality = criticality_weights.get(ra.asset.criticality, 1.0)\n\n        # Purdue level proximity factor (lower levels = higher risk)\n        level_weights = {\n            \"Level 0-1\": 1.5,\n            \"Level 2\": 1.3,\n            \"Level 3\": 1.0,\n            \"Level 3.5\": 0.8,\n            \"Level 4\": 0.6,\n        }\n        level_factor = level_weights.get(ra.asset.purdue_level, 1.0)\n\n        # Network exposure reduction if compensating controls exist\n        comp_reduction = 0.8 if ra.compensating_controls else 1.0\n\n        ra.risk_score = round(base * criticality * level_factor * comp_reduction, 1)\n        ra.risk_score = min(ra.risk_score, 10.0)\n\n        if ra.risk_score >= 9.0:\n            ra.risk_rating = \"critical\"\n            ra.remediation_priority = 1\n        elif ra.risk_score >= 7.0:\n            ra.risk_rating = \"high\"\n            ra.remediation_priority = 2\n        elif ra.risk_score >= 4.0:\n            ra.risk_rating = \"medium\"\n            ra.remediation_priority = 3\n        else:\n            ra.risk_rating = \"low\"\n            ra.remediation_priority = 4\n\n    def generate_report(self):\n        \"\"\"Generate vulnerability assessment report.\"\"\"\n        # Sort by risk score descending\n        sorted_ra = sorted(self.risk_assessments, key=lambda x: -x.risk_score)\n\n        report = []\n        report.append(\"=\" * 70)\n        report.append(\"OT VULNERABILITY ASSESSMENT REPORT\")\n        report.append(f\"Date: {datetime.now().isoformat()}\")\n        report.append(f\"Assets: {len(self.assets)} | Vulnerabilities: {len(self.vulnerabilities)}\")\n        report.append(f\"Risk Assessments: {len(self.risk_assessments)}\")\n        report.append(\"=\" * 70)\n\n        for sev in [\"critical\", \"high\", \"medium\", \"low\"]:\n            findings = [ra for ra in sorted_ra if ra.risk_rating == sev]\n            if findings:\n                report.append(f\"\\n--- {sev.upper()} RISK ({len(findings)}) ---\")\n                for ra in findings[:10]:\n                    report.append(f\"\\n  Risk Score: {ra.risk_score}\u002F10.0\")\n                    report.append(f\"  Asset: {ra.asset.name} ({ra.asset.vendor} {ra.asset.model})\")\n                    report.append(f\"  Zone: {ra.asset.zone} ({ra.asset.purdue_level})\")\n                    report.append(f\"  CVE: {ra.vulnerability.cve_id} (CVSS: {ra.vulnerability.cvss_score})\")\n                    report.append(f\"  Title: {ra.vulnerability.title}\")\n                    if ra.vulnerability.patch_available:\n                        report.append(f\"  Patch: Available - schedule for next maintenance window\")\n                    else:\n                        report.append(f\"  Patch: Not available - apply compensating controls\")\n\n        return \"\\n\".join(report)\n\n    def export_json(self, output_file):\n        \"\"\"Export assessment to JSON.\"\"\"\n        data = {\n            \"assessment_date\": datetime.now().isoformat(),\n            \"asset_count\": len(self.assets),\n            \"vulnerability_count\": len(self.vulnerabilities),\n            \"risk_assessments\": [\n                {\n                    \"asset_name\": ra.asset.name,\n                    \"asset_ip\": ra.asset.ip_address,\n                    \"cve\": ra.vulnerability.cve_id,\n                    \"risk_score\": ra.risk_score,\n                    \"risk_rating\": ra.risk_rating,\n                    \"priority\": ra.remediation_priority,\n                }\n                for ra in sorted(self.risk_assessments, key=lambda x: -x.risk_score)\n            ],\n        }\n        with open(output_file, \"w\") as f:\n            json.dump(data, f, indent=2)\n\n\nif __name__ == \"__main__\":\n    assessment = OTVulnerabilityAssessment()\n    advisories = assessment.fetch_ics_advisories()\n    print(f\"Fetched {len(advisories)} ICS advisories from CISA KEV catalog\")\n```\n\n## Key Concepts\n\n| Term | Definition |\n|------|------------|\n| Claroty xDome | Cyber-physical systems protection platform providing asset discovery, vulnerability management, and threat detection for OT\u002FIoT environments |\n| Passive Discovery | Identifying OT assets by analyzing network traffic without sending any packets, safe for production environments |\n| Safe Active Query | Querying OT devices using native industrial protocols at safe rates to collect detailed asset information without disrupting operations |\n| OT Risk Score | Risk rating that factors CVSS base score, asset criticality, Purdue level, and compensating controls for OT-appropriate prioritization |\n| ICS-CERT Advisory | CISA-published security advisories for industrial control system vulnerabilities with vendor-specific remediation guidance |\n| Virtual Patching | Deploying IPS\u002Ffirewall rules to block exploitation of known vulnerabilities when firmware patches cannot be immediately applied |\n\n## Tools & Systems\n\n- **Claroty xDome**: Comprehensive OT\u002FIoT asset discovery, vulnerability management, and continuous threat detection platform\n- **Claroty CTD**: Continuous Threat Detection sensor for passive network monitoring in OT environments\n- **CISA ICS-CERT**: US government advisory service publishing ICS vulnerability notifications and mitigation guidance\n- **Dragos Platform**: Alternative OT security platform with asset visibility and vulnerability management capabilities\n- **Nozomi Networks Guardian**: OT monitoring platform with vulnerability correlation and risk scoring\n\n## Output Format\n\n```\nOT Vulnerability Assessment Report\n=====================================\nTool: Claroty xDome \u002F Manual Assessment\nDate: YYYY-MM-DD\nAssets Scanned: [N]\n\nRISK SUMMARY:\n  Critical Risk: [N] vulnerabilities on [N] assets\n  High Risk: [N] vulnerabilities on [N] assets\n  Medium Risk: [N] vulnerabilities on [N] assets\n  Low Risk: [N] vulnerabilities on [N] assets\n\nTOP RISKS:\n  [Risk Score] [CVE-ID] on [Asset Name] ([Zone])\n    Remediation: [Patch\u002FCompensating Control]\n    Timeline: [Next maintenance window \u002F Immediate]\n```\n",{"name":5,"tags":44,"capec":50,"model":51,"tools":52,"domain":31,"maxTurns":56,"nist_csf":57,"subdomain":62,"description":7,"mitre_attack":63},[45,24,46,47,48,49,23],"ot-security","scada","industrial-control","iec62443","vulnerability-assessment",[],"sonnet",[53,30,54,55],"Read","Glob","Grep",20,[58,59,60,61],"PR.IR-01","DE.CM-01","ID.AM-05","GV.OC-02","ot-ics-security",[64,65],"T0855","T1082","main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Findustrial\u002Fics\u002Fasset-management\u002Fclaroty\u002Fassess\u002Faudit","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":74,"prompt":84,"zipAvailable":85},[75,78,81],{"tool":76,"command":77},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill ics-asset-management-claroty-assess-audit",{"tool":79,"command":80},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill ics-asset-management-claroty-assess-audit",{"tool":82,"command":83},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill ics-asset-management-claroty-assess-audit","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Findustrial\u002Fics\u002Fasset-management\u002Fclaroty\u002Fassess\u002Faudit\u002FSKILL.md",true,[87],{"path":88,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":91,"sourceHtmlUrl":92},"index.json","REFERENCE","参考文档",744,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Findustrial\u002Fics\u002Fasset-management\u002Fclaroty\u002Fassess\u002Faudit\u002Findex.json",[94,117,137,158,180,196],{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":100,"publishedAt":39},"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",[],[101,102,103,104,105,36,32,106,107,108,109,110,111,112,113,114,115,31,116],"services","detect","services wmi persistence detect","wmi","persistence","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","process-forensics",{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":121,"categories":122,"keywords":123,"publishedAt":39},"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",[],[124,101,125,104,126,127,37,31,30,26,128,129,130,131,36,132,133,134,135,136],"exploit","services wmi exec exploit","exec","remote","team","across","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":143,"publishedAt":39},"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",[],[144,145,146,147,148,149,31,30,150,26,151,152,36,134,153,154,155,156,157,51],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","analyze","uncover","software","activity","digital-forensics","windows-registry","regripper",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":164,"publishedAt":39},"01M71HACR4A8XTWTTSXK4124AA","processes-token-impersonate-detect","Detect Windows token impersonation and privilege abuse including SeImpersonatePrivilege exploitation via Potato attacks and token stealing techniques.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Ftoken\u002Fimpersonate\u002Fdetect\u002FSKILL.md",[],[102,165,166,167,168,169,170,32,171,31,116,172,173,174,175,176,177,178,179,36],"processes token impersonate detect","token","processes","attacks","windows","escalation","techniques","privilege-escalation","seimpersonate","token-impersonation","printspoofer","exploitation","potato","impersonation","via",{"skillNo":181,"name":182,"nameZh":6,"description":183,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":184,"categories":185,"keywords":186,"publishedAt":39},"01M71HAABSB4Z6QFSXEG00R4RK","processes-thread-injection-detect","Detect Windows thread injection techniques including CreateRemoteThread, QueueUserAPC, 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",[],[187,188,102,189,167,169,190,32,191,171,31,116,26,192,193,194,195,179,36,106],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":197,"name":198,"nameZh":6,"description":199,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":200,"categories":201,"keywords":202,"publishedAt":39},"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",[],[203,102,167,204,190,32,205,206,31,116,207,208,209,210,211,212,36,106,213,214],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","with","mismatched","headers"]