implementing-dragos-platform-for-ot-monitoring

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

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-dragos-platform-for-ot-monitoring
0 commentsdiscussion
summary

Deploy and configure the Dragos Platform for OT network monitoring, leveraging its 600+ industrial protocol parsers, intelligence-driven threat detection analytics, and asset visibility capabilities to protect ICS environments against threat groups like VOLTZITE, GRAPHITE, and BAUXITE.

skill.md
name
implementing-dragos-platform-for-ot-monitoring
description
'Deploy and configure the Dragos Platform for OT network monitoring, leveraging its 600+ industrial protocol parsers, intelligence-driven threat detection analytics, and asset visibility capabilities to protect ICS environments against threat groups like VOLTZITE, GRAPHITE, and BAUXITE. '
domain
cybersecurity
subdomain
ot-ics-security
tags
- ot-security - ics - dragos - threat-detection - ot-monitoring - scada - threat-intelligence - ndr
version
'1.0'
author
mahipal
license
Apache-2.0
nist_ai_rmf
- MEASURE-2.7 - MAP-5.1 - MANAGE-2.4
atlas_techniques
- AML.T0070 - AML.T0066 - AML.T0082
nist_csf
- PR.IR-01 - DE.CM-01 - ID.AM-05 - GV.OC-02

Implementing Dragos Platform for OT Monitoring

When to Use

  • When deploying an OT-specific network detection and response (NDR) solution for industrial environments
  • When needing threat intelligence-driven detection against known ICS threat groups (VOLTZITE, CHERNOVITE, KAMACITE)
  • When building an OT SOC capability with purpose-built industrial security tooling
  • When requiring asset discovery and vulnerability management alongside threat detection in a single platform
  • When integrating OT security monitoring with an enterprise SIEM (Splunk, Sentinel, QRadar)

Do not use for IT-only network monitoring without ICS components, for endpoint detection and response (EDR) on OT workstations, or for environments standardized on Claroty or Nozomi (see respective skills).

Prerequisites

  • Dragos Platform license and deployment package
  • Network TAP or SPAN port at OT network boundaries (one sensor per monitored segment)
  • Dragos sensor hardware (physical appliance) or virtual appliance meeting minimum specifications
  • Firewall rules allowing sensor-to-Dragos-SiteStore communication (encrypted, outbound only from OT)
  • Dragos Knowledge Pack subscription for threat intelligence updates

Workflow

Step 1: Deploy Dragos Sensors and Configure Monitoring

#!/usr/bin/env python3
"""Dragos Platform Deployment Validator and Integration Tool.

Validates Dragos sensor deployment, checks connectivity, and
configures integration with enterprise SIEM for OT alert forwarding.
"""

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

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


class DragosPlatformManager:
    """Interface with Dragos Platform API for OT monitoring management."""

    def __init__(self, base_url: str, api_key: str, api_secret: str, verify_ssl: bool = True):
        self.base_url = base_url.rstrip("/")
        self.session = requests.Session()
        self.session.headers.update({
            "API-Key": api_key,
            "API-Secret": api_secret,
            "Content-Type": "application/json",
        })
        self.session.verify = verify_ssl

    def get_sensors(self) -> List[Dict]:
        """Retrieve all deployed Dragos sensors and their status."""
        resp = self.session.get(f"{self.base_url}/api/v1/sensors")
        resp.raise_for_status()
        return resp.json().get("sensors", [])

    def get_assets(self, asset_type: Optional[str] = None) -> List[Dict]:
        """Retrieve OT assets discovered by Dragos."""
        params = {}
        if asset_type:
            params["type"] = asset_type
        resp = self.session.get(f"{self.base_url}/api/v1/assets", params=params)
        resp.raise_for_status()
        return resp.json().get("assets", [])

    def get_notifications(self, severity: str = "high", limit: int = 50) -> List[Dict]:
        """Retrieve threat detection notifications."""
        params = {"min_severity": severity, "limit": limit}
        resp = self.session.get(f"{self.base_url}/api/v1/notifications", params=params)
        resp.raise_for_status()
        return resp.json().get("notifications", [])

    def get_vulnerabilities(self, severity: str = "critical") -> List[Dict]:
        """Retrieve OT vulnerabilities with Dragos-specific context."""
        params = {"min_severity": severity}
        resp = self.session.get(f"{self.base_url}/api/v1/vulnerabilities", params=params)
        resp.raise_for_status()
        return resp.json().get("vulnerabilities", [])

    def get_threat_groups(self) -> List[Dict]:
        """Retrieve tracked ICS threat group activity relevant to the environment."""
        resp = self.session.get(f"{self.base_url}/api/v1/threat-groups")
        resp.raise_for_status()
        return resp.json().get("threat_groups", [])

    def validate_deployment(self):
        """Validate sensor deployment health and coverage."""
        sensors = self.get_sensors()
        assets = self.get_assets()

        print(f"\n{'='*65}")
        print("DRAGOS PLATFORM DEPLOYMENT VALIDATION")
        print(f"{'='*65}")
        print(f"Validation Time: {datetime.now().isoformat()}")

        print(f"\n--- SENSOR STATUS ---")
        healthy_sensors = 0
        for sensor in sensors:
            status = sensor.get("status", "unknown")
            icon = "[OK]" if status == "connected" else "[!!]"
            print(f"  {icon} {sensor.get('name', 'Unknown')} | Status: {status}")
            print(f"      IP: {sensor.get('ip_address')} | Segment: {sensor.get('monitored_segment')}")
            print(f"      Last Seen: {sensor.get('last_seen')} | Packets/sec: {sensor.get('pps', 0)}")
            print(f"      Knowledge Pack: {sensor.get('knowledge_pack_version', 'N/A')}")
            if status == "connected":
                healthy_sensors += 1

        print(f"\n  Sensor Health: {healthy_sensors}/{len(sensors)} operational")

        print(f"\n--- ASSET VISIBILITY ---")
        print(f"  Total Assets Discovered: {len(assets)}")
        asset_types = {}
        for asset in assets:
            atype = asset.get("type", "Unknown")
            asset_types[atype] = asset_types.get(atype, 0) + 1
        for atype, count in sorted(asset_types.items(), key=lambda x: -x[1]):
            print(f"    {atype}: {count}")

        protocols = set()
        for asset in assets:
            protocols.update(asset.get("protocols", []))
        print(f"  Protocols Observed: {', '.join(sorted(protocols))}")

        print(f"\n--- THREAT INTELLIGENCE ---")
        groups = self.get_threat_groups()
        print(f"  Relevant Threat Groups: {len(groups)}")
        for group in groups:
            print(f"    - {group.get('name')}: {group.get('description', '')[:80]}")
            print(f"      Targets: {', '.join(group.get('target_sectors', []))}")
            print(f"      Activity Level: {group.get('activity_level', 'Unknown')}")

    def generate_siem_integration_config(self, siem_type: str = "splunk"):
        """Generate SIEM integration configuration for Dragos alerts."""
        configs = {
            "splunk": {
                "syslog_format": "CEF",
                "syslog_port": 514,
                "severity_mapping": {
                    "critical": 10,
                    "high": 7,
                    "medium": 5,
                    "low": 3,
                    "info": 1,
                },
                "index": "ot_security",
                "sourcetype": "dragos:notification",
                "fields": [
                    "notification_id", "severity", "category", "source_ip",
                    "destination_ip", "asset_name", "protocol", "description",
                    "mitre_ics_technique", "threat_group",
                ],
            },
            "sentinel": {
                "connector_type": "Syslog-CEF",
                "workspace_id": "<workspace-id>",
                "log_analytics_table": "DragosOTAlerts_CL",
                "severity_mapping": {
                    "critical": "High",
                    "high": "High",
                    "medium": "Medium",
                    "low": "Low",
                    "info": "Informational",
                },
            },
        }

        config = configs.get(siem_type, configs["splunk"])
        print(f"\n--- {siem_type.upper()} INTEGRATION CONFIG ---")
        print(json.dumps(config, indent=2))
        return config


if __name__ == "__main__":
    manager = DragosPlatformManager(
        base_url="https://dragos-sitestore.plant.local",
        api_key="your-api-key",
        api_secret="your-api-secret",
        verify_ssl=True,
    )

    manager.validate_deployment()
    manager.generate_siem_integration_config("splunk")

    print(f"\n--- RECENT HIGH-SEVERITY NOTIFICATIONS ---")
    notifications = manager.get_notifications(severity="high", limit=10)
    for n in notifications:
        print(f"  [{n.get('severity', '').upper()}] {n.get('title', 'No title')}")
        print(f"    Category: {n.get('category')} | Time: {n.get('timestamp')}")
        print(f"    Assets: {', '.join(n.get('affected_assets', []))}")
        print(f"    MITRE ICS: {n.get('mitre_technique', 'N/A')}")

Step 2: Configure Detection Analytics and Knowledge Packs

# Dragos Platform Detection Configuration
# Tuned for manufacturing/energy environment

detection_configuration:
  knowledge_pack:
    auto_update: true
    update_schedule: "weekly"
    include_threat_groups:
      - "VOLTZITE"    # Targets energy sector, exfiltrates OT diagrams
      - "GRAPHITE"    # New 2025 threat group targeting ICS
      - "BAUXITE"     # New 2025 threat group targeting ICS
      - "CHERNOVITE"  # Developed PIPEDREAM/INCONTROLLER framework
      - "ELECTRUM"    # Linked to Industroyer/CrashOverride
      - "KAMACITE"    # Targets energy sector initial access

  detection_categories:
    network_baseline:
      enabled: true
      learning_period_days: 30
      alert_on:
        - "new_communication_pair"
        - "new_protocol_detected"
        - "new_device_on_network"
        - "protocol_anomaly"

    threat_detection:
      enabled: true
      alert_on:
        - "known_malware_ioc"
        - "threat_group_ttp"
        - "lateral_movement"
        - "command_and_control"
        - "data_exfiltration"

    vulnerability_correlation:
      enabled: true
      alert_on:
        - "active_exploitation_attempt"
        - "vulnerability_with_public_exploit"

  protocol_monitoring:
    modbus:
      monitor_writes: true
      baseline_function_codes: true
      baseline_register_ranges: true
    dnp3:
      monitor_control_commands: true
      detect_firmware_updates: true
    s7comm:
      detect_cpu_stop: true
      detect_program_download: true
    opc_ua:
      monitor_method_calls: true
      detect_browsing: true
    ethernet_ip:
      monitor_cip_services: true
      detect_firmware_flash: true

  alert_routing:
    critical:
      notify: ["ot_soc_team", "plant_manager"]
      siem_forward: true
      auto_ticket: true
    high:
      notify: ["ot_soc_team"]
      siem_forward: true
      auto_ticket: true
    medium:
      siem_forward: true
    low:
      siem_forward: true

Key Concepts

TermDefinition
Dragos PlatformPurpose-built OT cybersecurity platform with asset visibility, threat detection, and vulnerability management for ICS environments
Knowledge PackDragos threat intelligence update containing detection analytics for new threats, malware, and vulnerability exploits specific to ICS
SiteStoreDragos central management server aggregating data from all deployed sensors across a site
VOLTZITEDragos-tracked threat group targeting energy sector OT environments, exfiltrating GIS data and ICS network diagrams
PIPEDREAM/INCONTROLLERModular ICS attack framework developed by CHERNOVITE, targeting Schneider/OMRON PLCs and OPC UA servers
Neighborhood KeeperDragos community defense program sharing anonymized threat data across participating OT environments

Common Scenarios

Scenario: Detecting VOLTZITE Reconnaissance in Energy Utility

Context: A Dragos sensor deployed at an electric utility detects unusual OPC UA browsing activity and exfiltration of device configuration data from an engineering workstation.

Approach:

  1. Review the Dragos notification for MITRE ATT&CK ICS technique mapping
  2. Identify the source host performing OPC UA browsing (check if it is an authorized engineering workstation)
  3. Check Dragos threat intelligence correlation for VOLTZITE TTPs
  4. Examine the scope of data accessed (GIS data, network diagrams, ICS configuration files)
  5. Isolate the compromised workstation from the OT network
  6. Check for lateral movement indicators to other OT systems
  7. Engage Dragos Professional Services if threat group attribution is confirmed
  8. Report to CISA as a critical infrastructure cyber incident

Pitfalls: Do not ignore OPC UA browsing alerts as false positives -- VOLTZITE specifically uses this technique for pre-positioning. Ensure Dragos Knowledge Packs are current to detect the latest VOLTZITE indicators. Do not reimage the compromised workstation before collecting forensic evidence.

Output Format

DRAGOS OT MONITORING DEPLOYMENT REPORT
==========================================
Site: [Site Name]
Date: YYYY-MM-DD

SENSOR DEPLOYMENT:
  Total Sensors: [count]
  Operational: [count]
  Coverage: [percentage of OT segments monitored]

ASSET VISIBILITY:
  Total OT Assets: [count]
  PLCs: [count] | HMIs: [count] | Network Devices: [count]
  Protocols: [list]

THREAT DETECTION:
  Active Threat Groups Relevant: [count]
  Detection Analytics Loaded: [count]
  Alerts (Last 30 Days): [count by severity]

SIEM INTEGRATION:
  Status: [Connected/Disconnected]
  Events Forwarded (Last 24h): [count]
how to use implementing-dragos-platform-for-ot-monitoring

How to use implementing-dragos-platform-for-ot-monitoring on Cursor

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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 implementing-dragos-platform-for-ot-monitoring
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/implementing-dragos-platform-for-ot-monitoring

The skills CLI fetches implementing-dragos-platform-for-ot-monitoring from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

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Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-dragos-platform-for-ot-monitoring

Reload or restart Cursor to activate implementing-dragos-platform-for-ot-monitoring. Access the skill through slash commands (e.g., /implementing-dragos-platform-for-ot-monitoring) or your agent's skill management interface.

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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

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  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

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  • Don't skip validation of outputs
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💡 Pro Tips

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  • Combine AI efficiency with human expertise

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✓ 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

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Ratings

4.851 reviews
  • Aisha Taylor· Dec 16, 2024

    implementing-dragos-platform-for-ot-monitoring fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Aisha Brown· Dec 16, 2024

    implementing-dragos-platform-for-ot-monitoring is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • James Bansal· Dec 4, 2024

    implementing-dragos-platform-for-ot-monitoring reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Valentina Haddad· Nov 23, 2024

    We added implementing-dragos-platform-for-ot-monitoring from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • William Martinez· Nov 7, 2024

    Registry listing for implementing-dragos-platform-for-ot-monitoring matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Hassan Patel· Nov 7, 2024

    Useful defaults in implementing-dragos-platform-for-ot-monitoring — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Soo Bansal· Oct 26, 2024

    implementing-dragos-platform-for-ot-monitoring reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ava Thomas· Oct 26, 2024

    I recommend implementing-dragos-platform-for-ot-monitoring for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • William Choi· Oct 14, 2024

    implementing-dragos-platform-for-ot-monitoring fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ava Anderson· Sep 17, 2024

    Solid pick for teams standardizing on skills: implementing-dragos-platform-for-ot-monitoring is focused, and the summary matches what you get after install.

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