--- name: performing-ot-vulnerability-assessment-with-claroty-daceda11f5fa description: '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. ' domain: cybersecurity subdomain: ot-ics-security tags: - ot-security - ics - scada - industrial-control - iec62443 - vulnerability-assessment - claroty version: 1.0.0 author: Krishna Kumar (xalgord) license: Apache-2.0 nist_csf: - PR.IR-01 - DE.CM-01 - ID.AM-05 - GV.OC-02 --- # Performing OT Vulnerability Assessment with Claroty ## When to Use - When conducting scheduled OT vulnerability assessments per IEC 62443 or NERC CIP requirements - When deploying Claroty xDome for the first time and performing initial asset discovery and risk assessment - When correlating newly published ICS-CERT advisories against your OT asset inventory - When prioritizing OT vulnerability remediation with limited maintenance windows - When generating compliance evidence for CIP-010-4 vulnerability assessment requirements **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). ## Most Often Missed & How to Confirm Claroty-based vuln assessments miss real exposure when correlation is sloppy or active checks are misused. Confirm safely: - **Firmware-blind correlation:** matching vendor+model but ignoring the firmware band flags patched devices as vulnerable (false positive) and misses vulnerable ones recorded under a different model string. Confirm the exact firmware via passive parse or a safe native query, not just the CMDB. - **Passive can't see dormant assets:** a vulnerable standby controller silent on the wire won't correlate. Don't conclude it's not exposed — confirm via the comms map and physical inventory. - **Active confirmation done unsafely:** never validate a CVE by exploiting or aggressively scanning a live PLC. Use Claroty's safe native query, rate-limited, in a maintenance window, with SIS excluded. - **KEV/ICS-CERT context dropped:** a CVSS 7 in CISA KEV sitting at Level 1 outranks a CVSS 9 on an isolated L4 host. Confirm the OT risk score factored Purdue level, criticality, and compensating controls. - **Positive signal:** a finding is actionable when the asset's confirmed firmware falls in the advisory's affected range AND the device is reachable from a plausible attacker position. - **Don't conclude "remediated"** until the asset re-reports a fixed firmware after the window, or the named compensating control is verified live in the firewall/IPS config. ## Prerequisites - Claroty xDome or CTD (Continuous Threat Detection) deployed with sensors on OT network - Network SPAN/TAP access for passive asset discovery - CISA ICS-CERT advisory subscription for vulnerability tracking - Asset inventory with firmware versions for all OT devices - Change management process for patch deployment during maintenance windows ## Workflow ### Step 1: Configure Asset Discovery and Vulnerability Correlation Configure Claroty to perform passive and active-safe discovery to build complete asset inventory with firmware versions for vulnerability correlation. ```python #!/usr/bin/env python3 """OT Vulnerability Assessment Manager. Correlates OT asset inventory with ICS-CERT advisories and CVE data to identify, prioritize, and track OT vulnerabilities. Designed to integrate with Claroty xDome API or standalone operation. """ import json import sys from collections import defaultdict from dataclasses import dataclass, field, asdict from datetime import datetime import requests @dataclass class OTAsset: asset_id: str name: str vendor: str model: str firmware_version: str asset_type: str # PLC, HMI, RTU, historian, switch, etc. purdue_level: str ip_address: str protocol: str criticality: str # critical, high, medium, low zone: str @dataclass class OTVulnerability: vuln_id: str cve_id: str title: str severity: str # critical, high, medium, low cvss_score: float affected_vendor: str affected_product: str affected_versions: str description: str ics_cert_advisory: str = "" remediation: str = "" patch_available: bool = False compensating_controls: str = "" @dataclass class RiskAssessment: asset: OTAsset vulnerability: OTVulnerability risk_score: float = 0.0 risk_rating: str = "" exploitability: str = "" operational_impact: str = "" compensating_controls: list = field(default_factory=list) remediation_priority: int = 0 class OTVulnerabilityAssessment: """OT vulnerability assessment and prioritization engine.""" def __init__(self): self.assets = [] self.vulnerabilities = [] self.risk_assessments = [] def load_assets(self, assets_data): """Load asset inventory from Claroty export or manual inventory.""" for a in assets_data: self.assets.append(OTAsset(**a)) print(f"[*] Loaded {len(self.assets)} OT assets") def fetch_ics_advisories(self): """Fetch latest ICS-CERT advisories from CISA.""" print("[*] Fetching ICS-CERT advisories from CISA...") try: # CISA Known Exploited Vulnerabilities catalog url = "https://www.cisa.gov/sites/default/files/feeds/known_exploited_vulnerabilities.json" resp = requests.get(url, timeout=30) resp.raise_for_status() data = resp.json() ics_vulns = [] for vuln in data.get("vulnerabilities", []): # Filter for ICS-relevant vendors ics_vendors = [ "siemens", "schneider", "rockwell", "honeywell", "abb", "ge", "emerson", "yokogawa", "omron", "mitsubishi", "phoenix", "moxa", "advantech", ] vendor = vuln.get("vendorProject", "").lower() if any(v in vendor for v in ics_vendors): ics_vulns.append(vuln) print(f" Found {len(ics_vulns)} ICS-relevant known exploited vulnerabilities") return ics_vulns except Exception as e: print(f"[WARN] Could not fetch advisories: {e}") return [] def correlate_vulnerabilities(self): """Match vulnerabilities to assets based on vendor/model/firmware.""" print("[*] Correlating vulnerabilities to assets...") for asset in self.assets: for vuln in self.vulnerabilities: if (vuln.affected_vendor.lower() in asset.vendor.lower() and vuln.affected_product.lower() in asset.model.lower()): # Check firmware version if specified ra = RiskAssessment(asset=asset, vulnerability=vuln) self._calculate_risk_score(ra) self.risk_assessments.append(ra) print(f" Correlated {len(self.risk_assessments)} asset-vulnerability pairs") def _calculate_risk_score(self, ra): """Calculate OT-specific risk score considering operational impact.""" # Base score from CVSS base = ra.vulnerability.cvss_score # Criticality multiplier based on asset function criticality_weights = { "critical": 1.5, # SIS, safety systems "high": 1.3, # PLCs, primary control "medium": 1.0, # HMIs, historians "low": 0.7, # non-critical support systems } criticality = criticality_weights.get(ra.asset.criticality, 1.0) # Purdue level proximity factor (lower levels = higher risk) level_weights = { "Level 0-1": 1.5, "Level 2": 1.3, "Level 3": 1.0, "Level 3.5": 0.8, "Level 4": 0.6, } level_factor = level_weights.get(ra.asset.purdue_level, 1.0) # Network exposure reduction if compensating controls exist comp_reduction = 0.8 if ra.compensating_controls else 1.0 ra.risk_score = round(base * criticality * level_factor * comp_reduction, 1) ra.risk_score = min(ra.risk_score, 10.0) if ra.risk_score >= 9.0: ra.risk_rating = "critical" ra.remediation_priority = 1 elif ra.risk_score >= 7.0: ra.risk_rating = "high" ra.remediation_priority = 2 elif ra.risk_score >= 4.0: ra.risk_rating = "medium" ra.remediation_priority = 3 else: ra.risk_rating = "low" ra.remediation_priority = 4 def generate_report(self): """Generate vulnerability assessment report.""" # Sort by risk score descending sorted_ra = sorted(self.risk_assessments, key=lambda x: -x.risk_score) report = [] report.append("=" * 70) report.append("OT VULNERABILITY ASSESSMENT REPORT") report.append(f"Date: {datetime.now().isoformat()}") report.append(f"Assets: {len(self.assets)} | Vulnerabilities: {len(self.vulnerabilities)}") report.append(f"Risk Assessments: {len(self.risk_assessments)}") report.append("=" * 70) for sev in ["critical", "high", "medium", "low"]: findings = [ra for ra in sorted_ra if ra.risk_rating == sev] if findings: report.append(f"\n--- {sev.upper()} RISK ({len(findings)}) ---") for ra in findings[:10]: report.append(f"\n Risk Score: {ra.risk_score}/10.0") report.append(f" Asset: {ra.asset.name} ({ra.asset.vendor} {ra.asset.model})") report.append(f" Zone: {ra.asset.zone} ({ra.asset.purdue_level})") report.append(f" CVE: {ra.vulnerability.cve_id} (CVSS: {ra.vulnerability.cvss_score})") report.append(f" Title: {ra.vulnerability.title}") if ra.vulnerability.patch_available: report.append(f" Patch: Available - schedule for next maintenance window") else: report.append(f" Patch: Not available - apply compensating controls") return "\n".join(report) def export_json(self, output_file): """Export assessment to JSON.""" data = { "assessment_date": datetime.now().isoformat(), "asset_count": len(self.assets), "vulnerability_count": len(self.vulnerabilities), "risk_assessments": [ { "asset_name": ra.asset.name, "asset_ip": ra.asset.ip_address, "cve": ra.vulnerability.cve_id, "risk_score": ra.risk_score, "risk_rating": ra.risk_rating, "priority": ra.remediation_priority, } for ra in sorted(self.risk_assessments, key=lambda x: -x.risk_score) ], } with open(output_file, "w") as f: json.dump(data, f, indent=2) if __name__ == "__main__": assessment = OTVulnerabilityAssessment() advisories = assessment.fetch_ics_advisories() print(f"Fetched {len(advisories)} ICS advisories from CISA KEV catalog") ``` ## Key Concepts | Term | Definition | |------|------------| | Claroty xDome | Cyber-physical systems protection platform providing asset discovery, vulnerability management, and threat detection for OT/IoT environments | | Passive Discovery | Identifying OT assets by analyzing network traffic without sending any packets, safe for production environments | | Safe Active Query | Querying OT devices using native industrial protocols at safe rates to collect detailed asset information without disrupting operations | | OT Risk Score | Risk rating that factors CVSS base score, asset criticality, Purdue level, and compensating controls for OT-appropriate prioritization | | ICS-CERT Advisory | CISA-published security advisories for industrial control system vulnerabilities with vendor-specific remediation guidance | | Virtual Patching | Deploying IPS/firewall rules to block exploitation of known vulnerabilities when firmware patches cannot be immediately applied | ## Tools & Systems - **Claroty xDome**: Comprehensive OT/IoT asset discovery, vulnerability management, and continuous threat detection platform - **Claroty CTD**: Continuous Threat Detection sensor for passive network monitoring in OT environments - **CISA ICS-CERT**: US government advisory service publishing ICS vulnerability notifications and mitigation guidance - **Dragos Platform**: Alternative OT security platform with asset visibility and vulnerability management capabilities - **Nozomi Networks Guardian**: OT monitoring platform with vulnerability correlation and risk scoring ## Output Format ``` OT Vulnerability Assessment Report ===================================== Tool: Claroty xDome / Manual Assessment Date: YYYY-MM-DD Assets Scanned: [N] RISK SUMMARY: Critical Risk: [N] vulnerabilities on [N] assets High Risk: [N] vulnerabilities on [N] assets Medium Risk: [N] vulnerabilities on [N] assets Low Risk: [N] vulnerabilities on [N] assets TOP RISKS: [Risk Score] [CVE-ID] on [Asset Name] ([Zone]) Remediation: [Patch/Compensating Control] Timeline: [Next maintenance window / Immediate] ``` --- Source attribution: xalgord Original project: https://github.com/xalgord/xalgorix/blob/cec44d71b1d998208e1e2091982d0ee2f928041f/internal/tools/skills/data/ot-ics-security/performing-ot-vulnerability-assessment-with-claroty/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright 2026 xalgord Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: xalgord Original project: https://github.com/xalgord/xalgorix/blob/cec44d71b1d998208e1e2091982d0ee2f928041f/internal/tools/skills/data/ot-ics-security/performing-ot-vulnerability-assessment-with-claroty/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering, Operations Roles: IT Operations, Security Engineer Specialties: API Tools: Claroty Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 4761a42736dc38a8339d9fdae46e4573def4d99cfa3a309c53501de17a87aa55