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detecting-attacks-on-historian-servers

detecting-attacks-on-historian-servers

github.com/mukul975Security35.2k63 installsUpdated 8w ago
Repository

About detecting-attacks-on-historian-servers

A security skill for teams monitoring operational technology historians, including OSIsoft PI and Ignition. It outlines checks for unauthorized access, data manipulation, lateral movement, and historian-specific exploitation.

Key features

  1. 01Monitor historian attack indicators
  2. 02Check unauthorized clients and queries
  3. 03Investigate data manipulation
  4. 04Assess lateral movement
  5. 05Validate historian data integrity

Use cases

  1. 01Investigate suspicious historian connections
  2. 02Check integrity after an OT incident
  3. 03Review possible historian vulnerability exploitation

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill detecting-attacks-on-historian-servers

After installing, type/detecting-attacks-on-historian-serversin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

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

Details

From the project README

Detecting Attacks on Historian Servers

When to Use

  • When monitoring historian servers that bridge IT and OT networks for compromise indicators
  • When detecting unauthorized queries or data manipulation in process historian databases
  • When investigating lateral movement through historian servers between IT and OT zones
  • When responding to alerts about exploitation of historian-specific vulnerabilities (CVE-2025-0921)
  • When validating historian data integrity after a suspected OT security incident

Do not use for general database security monitoring (see database security skills), for historian deployment and configuration, or for IT-only data warehouse security.

Prerequisites

  • Historian server inventory (OSIsoft PI, Ignition, GE Proficy, Wonderware InSQL)
  • Network monitoring on historian network segments (both IT-facing and OT-facing interfaces)
  • Historian API access for data integrity validation
  • Baseline of normal historian query patterns (which applications query which tags)
  • Understanding of historian architecture (data sources, interfaces, client connections)

Workflow

Step 1: Monitor Historian for Attack Indicators
#!/usr/bin/env python3
"""OT Historian Attack Detector.

Monitors historian servers for unauthorized access, data manipulation,
lateral movement indicators, and exploitation of historian-specific
vulnerabilities. Supports OSIsoft PI and Ignition platforms.
"""

import json
import sys
from collections import defaultdict
from datetime import datetime, timedelta
from typing import Dict, List, Optional

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


class HistorianAttackDetector:
    """Detects attacks targeting OT historian servers."""

    def __init__(self, historian_type: str, historian_url: str,
                 api_credentials: dict, verify_ssl: bool = False):
        self.historian_type = historian_type
        self.historian_url = historian_url.rstrip("/")
        self.credentials = api_credentials
        self.verify_ssl = verify_ssl
        self.alerts = []
        self.authorized_clients = set()
        self.authorized_queries = {}

    def set_baseline(self, authorized_clients: List[str],
                     authorized_query_patterns: Dict[str, List[str]]):
        """Set baseline of authorized historian clients and query patterns."""
        self.authorized_clients = set(authorized_clients)
        self.authorized_queries = authorized_query_patterns

    def check_active_connections(self) -> List[dict]:
        """Check for unauthorized connections to historian."""
        connections = []

        if self.historian_type == "osisoft_pi":
            try:
                resp = requests.get(
                    f"{self.historian_url}/piwebapi/system/status",
                    auth=(self.credentials.get("username"), self.credentials.get("password")),
                    verify=self.verify_ssl,
                    timeout=10,
                )
                if resp.status_code == 200:
                    data = resp.json()
                    connections = data.get("ConnectedClients", [])
            except requests.RequestException as e:
                print(f"[!] PI Web API error: {e}")

        elif self.historian_type == "ignition":
            try:
                resp = requests.get(
                    f"{self.historian_url}/data/status/connections",
                    headers={"Authorization": f"Bearer {self.credentials.get('token')}"},
                    verify=self.verify_ssl,
                    timeout=10,
                )
                if resp.status_code == 200:
                    connections = resp.json().get("connections", [])
            except requests.RequestException as e:
                print(f"[!] Ignition API error: {e}")

        # Check for unauthorized clients
        for conn in connections:
            client_ip = conn.get("client_ip", conn.get("address", ""))
            if self.authorized_clients and client_ip not in self.authorized_clients:
                self.alerts.append({
                    "severity": "HIGH",
                    "type": "UNAUTHORIZED_HISTORIAN_CLIENT",
                    "timestamp": datetime.now().isoformat(),
                    "source_ip": client_ip,
                    "details": f"Unauthorized client {client_ip} connected to {self.historian_type} historian",
                    "mitre": "T0802 - Automated Collection",
                })

        return connections

    def check_data_integrity(self, tags: List[str], hours_back: int = 24):
        """Check historian data for manipulation indicators."""
        print(f"[*] Checking data integrity for {len(tags)} tags over last {hours_back}h")

        integrity_issues = []
        for tag in tags:
            try:
                if self.historian_type == "osisoft_pi":
                    resp = requests.get(
                        f"{self.historian_url}/piwebapi/streams/{tag}/recorded",
                        params={"startTime": f"*-{hours_back}h", "endTime": "*"},
                        auth=(self.credentials.get("username"), self.credentials.get("password")),
                        verify=self.verify_ssl,
                        timeout=15,
                    )
                    if resp.status_code == 200:
                        items = resp.json().get("Items", [])
                        # Check for suspicious patterns
                        if len(items) == 0:
                            integrity_issues.append({
                                "tag": tag, "issue": "NO_DATA",
                                "detail": "No data points in expected timeframe - possible deletion",
                            })
                        else:
                            values = [i.get("Value", 0) for i in items if isinstance(i.get("Value"), (int, float))]
                            if values and len(set(values)) == 1 and len(values) > 100:
                                integrity_issues.append({
                                    "tag": tag, "issue": "FLATLINE",
                                    "detail": f"Constant value {values[0]} for {len(values)} points - possible replay/spoofing",
                                })
            except requests.RequestException:
                pass

        for issue in integrity_issues:
            self.alerts.append({
                "severity": "HIGH",
                "type": f"DATA_INTEGRITY_{issue['issue']}",
                "timestamp": datetime.now().isoformat(),
                "tag": issue["tag"],
                "details": issue["detail"],
                "mitre": "T0809 - Data Destruction" if issue["issue"] == "NO_DATA" else "T0832 - Manipulation of View",
            })

        return integrity_issues

    def check_lateral_movement_indicators(self):
        """Check for indicators of historian being used as pivot point."""
        indicators = []

        # Check 1: Historian making outbound connections to Level 1 devices
        # (Historian should receive data, not initiate connections to PLCs)
        indicators.append({
            "check": "Outbound connections to PLC subnets",
            "description": "Historian initiating connections to Level 1 devices may indicate compromise",
            "detection": "Monitor firewall logs for historian IP connecting to PLC ports (502, 102, 44818)",
        })

        # Check 2: New processes or services on historian
        indicators.append({
            "check": "Unauthorized processes on historian server",
            "description": "Attackers may install tools on historian for lateral movement",
            "detection": "Monitor process creation events (Sysmon EventID 1) on historian",
        })

        # Check 3: Unusual authentication to historian
        indicators.append({
            "check": "Authentication from unexpected sources",
            "description": "Compromised IT systems authenticating to historian for pivoting",
            "detection": "Monitor Windows Security Event 4624 for logons from non-baseline sources",
        })

        return indicators

    def generate_report(self):
        """Generate historian attack detection report."""
        print(f"\n{'='*70}")
        print("HISTORIAN ATTACK DETECTION REPORT")
        print(f"{'='*70}")
        print(f"Historian Type: {self.historian_type}")
        print(f"Historian URL: {self.historian_url}")
        print(f"Report Time: {datetime.now().isoformat()}")
        print(f"Total Alerts: {len(self.alerts)}")

        if self.alerts:
            print(f"\n--- ALERTS ---")
            for alert in self.alerts:
                print(f"\n  [{alert['severity']}] {alert['type']}")
                print(f"    Time: {alert['timestamp']}")
                print(f"    Detail: {alert['details']}")
                print(f"    MITRE ICS: {alert.get('mitre', 'N/A')}")

        print(f"\n--- LATERAL MOVEMENT CHECKS ---")
        for indicator in self.check_lateral_movement_indicators():
            print(f"\n  Check: {indicator['check']}")
            print(f"    Risk: {indicator['description']}")
            print(f"    Detection: {indicator['detection']}")


if __name__ == "__main__":
    detector = HistorianAttackDetector(
        historian_type="osisoft_pi",
        historian_url="https://pi-server.plant.local",
        api_credentials={"username": "pi_reader", "password": "api_key_here"},
    )

    detector.set_baseline(
        authorized_clients=["10.10.2.10", "10.10.2.20", "10.10.3.50", "10.10.150.10"],
        authorized_query_patterns={},
    )

    detector.check_active_connections()
    detector.check_data_integrity(tags=["REACTOR_01.TEMP", "PUMP_03.FLOW"], hours_back=24)
    detector.generate_report()

Key Concepts

TermDefinition
OT HistorianDatabase server (OSIsoft PI, Ignition, Wonderware) storing time-series process data from SCADA/DCS systems
Pivot PointHistorian's position between IT and OT networks makes it a prime target for attackers to move between zones
Data Replay AttackFeeding historical data to an HMI to mask real-time process manipulation (Stuxnet technique)
OSIsoft PIMost widely deployed OT historian, used by 65% of Global 500 process companies
IgnitionInductive Automation SCADA platform with historian module, increasingly targeted due to Python scripting capabilities
CVE-2025-0921Ignition SCADA privileged file system vulnerability allowing escalation through malicious project files

Output Format

HISTORIAN ATTACK DETECTION REPORT
====================================
Historian: [type and hostname]
Date: YYYY-MM-DD

CONNECTION ANALYSIS:
  Authorized Clients: [count]
  Unauthorized Clients Detected: [count with IPs]

DATA INTEGRITY:
  Tags Checked: [count]
  Integrity Issues: [count]
  Flatline Detections: [count]
  Data Gaps: [count]

LATERAL MOVEMENT INDICATORS:
  Outbound PLC Connections: [found/not found]
  Unauthorized Processes: [found/not found]
  Anomalous Authentication: [found/not found]

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