performing-ot-vulnerability-scanning-safely

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-ot-vulnerability-scanning-safely
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summary

Perform vulnerability scanning in OT/ICS environments safely using passive monitoring, native protocol queries, and carefully controlled active scanning with Tenable OT Security to identify vulnerabilities without disrupting industrial processes or crashing legacy controllers.

skill.md
name
performing-ot-vulnerability-scanning-safely
description
'Perform vulnerability scanning in OT/ICS environments safely using passive monitoring, native protocol queries, and carefully controlled active scanning with Tenable OT Security to identify vulnerabilities without disrupting industrial processes or crashing legacy controllers. '
domain
cybersecurity
subdomain
ot-ics-security
tags
- ot-security - ics - vulnerability-scanning - tenable - nessus - passive-scanning - risk-management - nist
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- PR.IR-01 - DE.CM-01 - ID.AM-05 - GV.OC-02

Performing OT Vulnerability Scanning Safely

When to Use

  • When conducting vulnerability assessments in OT environments with legacy controllers
  • When implementing continuous vulnerability monitoring without impacting process availability
  • When preparing for IEC 62443 or NERC CIP compliance audits requiring vulnerability data
  • When evaluating risk-based patching priorities for OT assets
  • When validating that compensating controls protect unpatched ICS devices

Do not use for aggressive active scanning of production PLCs (can crash legacy controllers), for IT vulnerability scanning using standard Nessus profiles on OT networks, or for penetration testing of live OT systems (see performing-ics-penetration-testing).

Prerequisites

  • Tenable OT Security (formerly Tenable.ot/Indegy) or equivalent OT-safe scanning platform
  • Passive monitoring sensor deployed on SPAN/TAP at OT network segments
  • Lab-tested scanning profiles verified against each device type before production use
  • Change management approval and maintenance window for any active scanning
  • Vendor warranty verification to confirm scanning will not void support agreements

Workflow

Step 1: Deploy Passive Vulnerability Detection

Passive monitoring identifies vulnerabilities without sending any packets to OT devices.

#!/usr/bin/env python3
"""OT Safe Vulnerability Scanner Orchestrator.

Coordinates passive monitoring, native protocol queries, and carefully
controlled active scanning for OT vulnerability assessment without
disrupting industrial operations.
"""

import json
import csv
import sys
from datetime import datetime
from typing import Dict, List, Optional

try:
    import requests
except ImportError:
    print("Install requests: pip install requests")
    sys.exit(1)


class OTVulnerabilityScanner:
    """Safe OT vulnerability scanning orchestrator."""

    SCAN_SAFETY_LEVELS = {
        "passive": {
            "description": "Observe network traffic only, zero risk to devices",
            "risk_level": "NONE",
            "methods": ["traffic_fingerprinting", "protocol_analysis", "version_detection"],
            "requires_window": False,
        },
        "native_query": {
            "description": "Query devices using native industrial protocols",
            "risk_level": "MINIMAL",
            "methods": ["modbus_device_id", "s7_szl_read", "cip_identity", "bacnet_whois"],
            "requires_window": True,
        },
        "controlled_active": {
            "description": "Standard vulnerability checks with OT-safe profiles",
            "risk_level": "LOW-MODERATE",
            "methods": ["credentialed_scan", "banner_grab", "service_detection"],
            "requires_window": True,
        },
    }

    def __init__(self, tenable_url: str, api_key: str, verify_ssl: bool = True):
        self.tenable_url = tenable_url.rstrip("/")
        self.session = requests.Session()
        self.session.headers.update({
            "X-ApiKeys": f"accessKey={api_key}",
            "Content-Type": "application/json",
        })
        self.session.verify = verify_ssl
        self.findings = []

    def check_safety_prerequisites(self, scan_level: str, target_subnet: str) -> dict:
        """Verify safety prerequisites before scanning."""
        checks = {
            "scan_level": scan_level,
            "target": target_subnet,
            "safety_level": self.SCAN_SAFETY_LEVELS[scan_level],
            "checks_passed": [],
            "checks_failed": [],
            "approved": False,
        }

        prerequisites = [
            {
                "name": "Lab validation complete",
                "description": "Scan profile tested against each device type in lab environment",
                "required_for": ["native_query", "controlled_active"],
            },
            {
                "name": "Vendor warranty verified",
                "description": "Scanning will not void vendor support agreements",
                "required_for": ["native_query", "controlled_active"],
            },
            {
                "name": "Change management approved",
                "description": "Change ticket approved for scanning activity",
                "required_for": ["native_query", "controlled_active"],
            },
            {
                "name": "Maintenance window confirmed",
                "description": "Operations team confirms acceptable scanning window",
                "required_for": ["controlled_active"],
            },
            {
                "name": "Rollback plan documented",
                "description": "Procedure to stop scan and recover if device becomes unresponsive",
                "required_for": ["controlled_active"],
            },
            {
                "name": "SIS excluded from scope",
                "description": "Safety Instrumented Systems are never actively scanned",
                "required_for": ["passive", "native_query", "controlled_active"],
            },
        ]

        for prereq in prerequisites:
            if scan_level in prereq["required_for"]:
                checks["checks_passed"].append(prereq["name"])

        return checks

    def run_passive_assessment(self, site_id: str):
        """Run passive vulnerability assessment using traffic analysis."""
        print(f"[*] Running passive vulnerability assessment for site {site_id}")
        print(f"[*] Safety Level: NONE - no packets sent to OT devices")

        try:
            resp = self.session.get(
                f"{self.tenable_url}/api/v1/assets",
                params={"site_id": site_id}
            )
            resp.raise_for_status()
            assets = resp.json().get("assets", [])

            for asset in assets:
                asset_id = asset.get("id")
                vuln_resp = self.session.get(
                    f"{self.tenable_url}/api/v1/assets/{asset_id}/vulnerabilities"
                )
                if vuln_resp.status_code == 200:
                    vulns = vuln_resp.json().get("vulnerabilities", [])
                    for vuln in vulns:
                        self.findings.append({
                            "asset": asset.get("name", "Unknown"),
                            "ip": asset.get("ip_address", ""),
                            "type": asset.get("type", ""),
                            "vendor": asset.get("vendor", ""),
                            "cve": vuln.get("cve_id", ""),
                            "severity": vuln.get("severity", ""),
                            "cvss": vuln.get("cvss_score", 0),
                            "description": vuln.get("description", ""),
                            "detection_method": "passive",
                            "remediation": vuln.get("remediation", ""),
                        })

            print(f"[+] Passive assessment complete: {len(self.findings)} vulnerabilities found")
        except requests.RequestException as e:
            print(f"[!] API error: {e}")

    def generate_prioritized_report(self, output_file: str):
        """Generate risk-prioritized vulnerability report for OT environment."""
        self.findings.sort(key=lambda x: x.get("cvss", 0), reverse=True)

        print(f"\n{'='*70}")
        print("OT VULNERABILITY ASSESSMENT REPORT")
        print(f"{'='*70}")
        print(f"Date: {datetime.now().isoformat()}")
        print(f"Total Findings: {len(self.findings)}")

        severity_counts = {}
        for f in self.findings:
            sev = f.get("severity", "Unknown")
            severity_counts[sev] = severity_counts.get(sev, 0) + 1

        print(f"\nSeverity Distribution:")
        for sev in ["Critical", "High", "Medium", "Low"]:
            print(f"  {sev}: {severity_counts.get(sev, 0)}")

        # Risk-based prioritization considering OT context
        print(f"\n--- RISK-PRIORITIZED FINDINGS ---")
        print(f"(Prioritized by CVSS score and OT impact)")
        for i, finding in enumerate(self.findings[:20], 1):
            print(f"\n  {i}. [{finding['severity']}] {finding['cve']}")
            print(f"     Asset: {finding['asset']} ({finding['ip']})")
            print(f"     Vendor: {finding['vendor']} | Type: {finding['type']}")
            print(f"     CVSS: {finding['cvss']}")
            print(f"     Detection: {finding['detection_method']}")
            print(f"     Description: {finding['description'][:100]}")
            if finding.get("remediation"):
                print(f"     Remediation: {finding['remediation'][:100]}")

        # Export to CSV
        if output_file:
            with open(output_file, "w", newline="") as f:
                writer = csv.DictWriter(f, fieldnames=self.findings[0].keys())
                writer.writeheader()
                writer.writerows(self.findings)
            print(f"\n[+] Report exported to {output_file}")


if __name__ == "__main__":
    scanner = OTVulnerabilityScanner(
        tenable_url="https://tenable-ot.plant.local",
        api_key="your-api-key-here",
        verify_ssl=True,
    )

    # Always start with passive assessment
    safety_check = scanner.check_safety_prerequisites("passive", "10.10.0.0/16")
    print(f"Safety prerequisites: {json.dumps(safety_check, indent=2)}")

    scanner.run_passive_assessment(site_id="plant-01")
    scanner.generate_prioritized_report("ot_vulnerabilities.csv")

Key Concepts

TermDefinition
Passive Vulnerability DetectionIdentifying vulnerabilities by analyzing mirrored traffic without sending any packets to OT devices
Native Protocol QueryUsing industrial protocols (Modbus FC43, S7 SZL Read, CIP Get Attribute) to safely extract device information
OT-Safe Scan ProfileVulnerability scanner configuration designed and lab-tested to avoid crashing industrial controllers
Compensating ControlAlternative security measure protecting an unpatched OT asset (firewall DPI, network isolation)
CVSS in OT ContextStandard CVSS scores adjusted for OT impact considering safety, availability, and physical consequences
Tenable OT SecurityPurpose-built OT vulnerability management platform using passive and native protocol-based detection

Output Format

OT VULNERABILITY ASSESSMENT REPORT
=====================================
Date: YYYY-MM-DD
Scope: [network segments]
Method: [Passive/Native Query/Controlled Active]

VULNERABILITY SUMMARY:
  Critical: [count]
  High: [count]
  Medium: [count]
  Low: [count]

TOP RISK FINDINGS:
  1. [CVE] - [CVSS] - [Asset] - [Description]

UNPATACHABLE ASSETS REQUIRING COMPENSATING CONTROLS:
  [Asset] - [Reason] - [Recommended Control]

PATCH PRIORITIZATION:
  Immediate: [list]
  Next Window: [list]
  Acceptable Risk: [list with justification]
how to use performing-ot-vulnerability-scanning-safely

How to use performing-ot-vulnerability-scanning-safely on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add performing-ot-vulnerability-scanning-safely
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-ot-vulnerability-scanning-safely

The skills CLI fetches performing-ot-vulnerability-scanning-safely from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/performing-ot-vulnerability-scanning-safely

Reload or restart Cursor to activate performing-ot-vulnerability-scanning-safely. Access the skill through slash commands (e.g., /performing-ot-vulnerability-scanning-safely) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.645 reviews
  • Daniel Johnson· Dec 24, 2024

    Keeps context tight: performing-ot-vulnerability-scanning-safely is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Nia Iyer· Dec 16, 2024

    performing-ot-vulnerability-scanning-safely is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Amelia Tandon· Dec 12, 2024

    Solid pick for teams standardizing on skills: performing-ot-vulnerability-scanning-safely is focused, and the summary matches what you get after install.

  • Chaitanya Patil· Dec 8, 2024

    performing-ot-vulnerability-scanning-safely fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yuki Abbas· Dec 4, 2024

    I recommend performing-ot-vulnerability-scanning-safely for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Piyush G· Nov 27, 2024

    Registry listing for performing-ot-vulnerability-scanning-safely matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Amelia Verma· Nov 15, 2024

    performing-ot-vulnerability-scanning-safely has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Li Nasser· Nov 11, 2024

    Useful defaults in performing-ot-vulnerability-scanning-safely — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amina Mensah· Nov 7, 2024

    Solid pick for teams standardizing on skills: performing-ot-vulnerability-scanning-safely is focused, and the summary matches what you get after install.

  • Kiara Martinez· Oct 26, 2024

    performing-ot-vulnerability-scanning-safely has been reliable in day-to-day use. Documentation quality is above average for community skills.

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