Individual skill
detecting-anomalies-in-industrial-control-systems
This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.
internal/tools/skills/data/ot-ics-security/detecting-anomalies-in-industrial-control-systems/SKILL.md
Source commit d42f381ad34843e71a42658e5c57290c713e85af
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Instructions only
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,329
- Repository last updated
- Nov 9, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- cybersecurity Repository topic
- security Repository topic
- bug-bounty Repository topic
- automation Repository topic
- autonomous-pentesting Repository topic
- ai-agent Repository topic
- ai-security Repository topic
- ethical-hacking Repository topic
- golang Repository topic
- penetration-testing Repository topic
- ot-security Declared skill tag
- ics Declared skill tag
- scada Declared skill tag
- industrial-control Declared skill tag
- iec62443 Declared skill tag
- anomaly-detection Declared skill tag
- machine-learning Declared skill tag
- operations Derived category
- data Derived category
- security Derived category
- education Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
# Detecting Anomalies in Industrial Control Systems
## When to Use
- When deploying continuous monitoring for OT environments that lack intrusion detection
- When building behavior-based detection to complement signature-based IDS in OT networks
- When establishing baselines for deterministic SCADA communications to detect deviations
- When integrating machine learning anomaly detection with OT security monitoring platforms
- When investigating alerts from Nozomi Guardian or Dragos Platform that require deeper analysis
**Do not use** for signature-based detection of known exploits (see detecting-attacks-on-scada-systems), for IT network anomaly detection without OT protocols, or as a replacement for process safety systems (SIS).
## Detection Gaps & Validation
