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Ics Anomaly Detection
Design and analyze industrial control system anomaly detection logic for safe, protocol-aware OT security monitoring.
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See it in action
You say
I have passive monitoring data from a Modbus/TCP network covering 48 hours. There are 3 devices showing unexpected polling frequency changes and 1 device communicating on a previously unobserved port. Produce an anomaly detection report and findings register.
Your agent does
The skill produces a structured anomaly detection report covering the observed deviations, a baseline profile comparison, and a findings register with severity classifications. Each anomaly entry includes protocol context, observed versus baseline behaviour, potential significance, and recommended passive investigation steps. A passive monitoring and active testing boundary note is included, confirming no active probing is advised. The output is formatted for inclusion in an OT security governance or assurance review.
What you get
About this skill
Professional ICS and OT Anomaly Analysis
In industrial environments, distinguishing between a routine process change and a sophisticated cyber threat is a high-stakes challenge. The ICS Anomaly Detection skill provides a specialized framework for assessing, designing, and validating anomaly detection across SCADA, PLC, and IIoT environments. It bridges the gap between raw network data and operational safety.
What it does
This skill enables cyber defenders to analyze passive monitoring evidence, establish behavioral baselines, and investigate protocol-specific deviations without risking plant stability. It guides users through creating structured anomaly reports and detection designs that map network behavior to operational risk.
- Protocol Intelligence: Analyze Modbus, DNP3, OPC UA, S7, and BACnet for function code outliers or timing anomalies.
- Baseline Validation: Differentiate between legitimate maintenance windows and malicious lateral movement.
- Vendor Agnostic: Compatible with any OT monitoring platform, PCAP export, or Historian data.
- Safe Methodology: Enforces strict authorization and passive-first analysis to protect live production environments.
Why use this skill?
Prompting an AI yourself often leads to generic IT security advice that ignores the physical safety constraints of a factory or utility. This skill applies specialized OT logic to ensure recommendations are non-disruptive, evidence-based, and aligned with industrial engineering standards. It produces professional-grade documentation—such as findings registers and detection plans—ready for SOC and engineering stakeholders.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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