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
"""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}")
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", [])
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 = []
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)",
})
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",
})
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
| Term | Definition |
|---|
| OT Historian | Database server (OSIsoft PI, Ignition, Wonderware) storing time-series process data from SCADA/DCS systems |
| Pivot Point | Historian's position between IT and OT networks makes it a prime target for attackers to move between zones |
| Data Replay Attack | Feeding historical data to an HMI to mask real-time process manipulation (Stuxnet technique) |
| OSIsoft PI | Most widely deployed OT historian, used by 65% of Global 500 process companies |
| Ignition | Inductive Automation SCADA platform with historian module, increasingly targeted due to Python scripting capabilities |
| CVE-2025-0921 | Ignition 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]
