cyber-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,

Jump to install

Repository: nexuslinkproductions/yuri-os
Last source activity: August 2, 2026 at 20:10
Detected SKILL.md language: English
Stars: 2
Forks: 0

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/nexuslinkproductions/yuri-os --skill cyber-detecting-anomalies-in-industrial-control-systems

The command stays on one line. Scroll horizontally to inspect it before copying.

Prefer a local copy? Download the files currently available to SkillsMP.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

File Explorer

2 files

SKILL.md

Source instructions · Read-only preview

Back to search Back to installation

cyber-abusing-dpapi-for-credential-access

[LAB-GATED; discovery is not runtime authorization; offensive/dual-use — authorized-lab gate] Extract DPAPI-protected secrets such as credentials and browser data offline and online.

2026-08-02

cyber-abusing-shadow-credentials-for-privesc

[LAB-GATED; discovery is not runtime authorization; offensive/dual-use — authorized-lab gate] Take over Active Directory user and computer accounts by writing alternate certificate keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, and Certipy, then authenticate via PKINIT.

2026-08-02

cyber-achieving-cmmc-level-2-compliance

>- Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD

2026-08-02

View all from this repository

name	cyber-detecting-anomalies-in-industrial-control-systems
description	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,
hide	true

YURI skill adapter

Authoritative source: .claude/skills/cyber-detecting-anomalies-in-industrial-control-systems/SKILL.md

Authoritative source SHA-256: 4b2fe2829469db85d00cf03059eaa24d31d4fc270fae5c8098c1ca26cc4a437c

Source class: cyber-armed

Before acting, read the authoritative source file above completely from beginning to end. If the governed source is absent, run node _SYSTEM/Scripts/skill-recall.mjs --show cyber-detecting-anomalies-in-industrial-control-systems and read its complete verified output. Follow that source as the skill body; this adapter is a non-authoritative metadata-and-pointer projection.

cyber-detecting-anomalies-in-industrial-control-systems

Source facts

Install options

Review the source files

More from this repository

More from this repository

YURI skill adapter

YURI skill adapter