Agent skill

Implementing Dragos Platform For Ot Monitoring

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE…

Apache-2.0Auto-check passedSecurity

Install Implementing Dragos Platform For Ot Monitoring

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-dragos-platform-for-ot-monitoring -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-dragos-platform-for-ot-monitoring --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-dragos-platform-for-ot-monitoring .claude/skills/implementing-dragos-platform-for-ot-monitoring && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implementing-dragos-platform-for-ot-monitoring
GitHub stars
34k
Token cost
~3.5k tokens
SKILL.md length
436 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE…

  • Works in 2 steps: Deploy Dragos Sensors and Configure… → Configure Detection Analytics and…
  • Standing up OT-specific network detection and response
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 2 more sections
  • Runs Python scripts from its folder

What it does

Implementing Dragos Platform For Ot Monitoring is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE, CHERNOVITE, and KAMACITE. Use when standing up OT-specific network detection and response or an OT SOC, or integrating OT monitoring into an enterprise SIEM; not for IT-only or Claroty/Nozomi environments.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Security operations. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Standing up OT-specific network detection and response
  • Integrating OT monitoring into an enterprise SIEM
  • Not for IT-only
  • Claroty/Nozomi environments

Example prompts

  • “Use the implementing-dragos-platform-for-ot-monitoring skill to deploy and configures Dragos Platform sensors and detection analytics for OT/ICS…”
  • “/implementing-dragos-platform-for-ot-monitoring”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Deploy Dragos Sensors and Configure Monitoring
  2. Configure Detection Analytics and Knowledge Packs

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implementing Dragos Platform For Ot Monitoring loads about 3.5k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 436 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 436 words, ~3,470 tokens.

Download SKILL.mdSave it as .claude/skills/implementing-dragos-platform-for-ot-monitoring/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
implementing-dragos-platform-for-ot-monitoring
description
Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE, CHERNOVITE, and KAMACITE. Use when standing up OT-specific network detection and response or an OT SOC, or integrating OT monitoring into an enterprise SIEM; not for IT-only or Claroty/Nozomi environments.
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
mitre_attack
T1078, T1190, T1059, T0816, T0836

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
python
#!/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
yaml
# 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
Show full SKILL.md (168 more words)Show less

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]

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/implementing-dragos-platform-for-ot-monitoring of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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Categories

Questions about Implementing Dragos Platform For Ot Monitoring

What does Implementing Dragos Platform For Ot Monitoring do?

Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE…. Implementing Dragos Platform For Ot Monitoring is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE, CHERNOVITE, and KAMACITE.

When should I use Implementing Dragos Platform For Ot Monitoring?

Implementing Dragos Platform For Ot Monitoring fits situations like: standing up OT-specific network detection and response; integrating OT monitoring into an enterprise SIEM; not for IT-only; claroty/Nozomi environments.

How do I install Implementing Dragos Platform For Ot Monitoring in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-dragos-platform-for-ot-monitoring -a claude-code`. Or copy the skill folder (skills/implementing-dragos-platform-for-ot-monitoring in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-dragos-platform-for-ot-monitoring in your project. Claude Code loads it when a task matches its description.

How do I install Implementing Dragos Platform For Ot Monitoring in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-dragos-platform-for-ot-monitoring -a codex`. Or copy the skill folder (skills/implementing-dragos-platform-for-ot-monitoring in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-dragos-platform-for-ot-monitoring in your project. Codex loads it when a task matches its description.

Can I use Implementing Dragos Platform For Ot Monitoring in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-dragos-platform-for-ot-monitoring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-dragos-platform-for-ot-monitoring, .gemini/skills/implementing-dragos-platform-for-ot-monitoring, .github/skills/implementing-dragos-platform-for-ot-monitoring and .opencode/skills/implementing-dragos-platform-for-ot-monitoring in your project.

What does Implementing Dragos Platform For Ot Monitoring need to run?

Going by SKILL.md and its folder, Implementing Dragos Platform For Ot Monitoring needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Implementing Dragos Platform For Ot Monitoring access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Implementing Dragos Platform For Ot Monitoring safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Implementing Dragos Platform For Ot Monitoring use?

Implementing Dragos Platform For Ot Monitoring is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implementing Dragos Platform For Ot Monitoring use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 397 tokens, read only when the agent opens those files.

What are the alternatives to Implementing Dragos Platform For Ot Monitoring?

Skills that share tags, products or a category with Implementing Dragos Platform For Ot Monitoring: Security Alert Triage (elastic/agent-skills, 592 stars), Kubernetes Network Security Audit (kubeshark/kubeshark, 12k stars), Security Detection Rule Management (elastic/agent-skills, 592 stars) and Chaitin CLI (chaitin/chaitin-cli, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implementing Dragos Platform For Ot Monitoring?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.