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Python IoT Edge Module Development

python-azure-iot-edge-modules

github/awesome-copilot

This skill guides the end-to-end development, implementation, and validation of production-ready Python modules for Azure IoT Edge. It covers critical aspects including telemetry processing, protocol adaptation (Modbus, OPC-UA), local inference, and ensuring robust, secure edge-to-cloud messaging under variable network conditions.

BLE Attack Methodology

offensive-bluetooth-ble

SnailSploit/Claude-Red

Covers Bluetooth Low Energy attack workflows, including GATT enumeration, unauthenticated characteristic access, pairing downgrade checks, MITM during pairing, sniffing, and companion app reverse engineering for IoT and consumer BLE devices.

IoT Security Testing

SnailSploit/Claude-Red

A hands-on methodology for testing IoT and embedded devices, covering hardware reconnaissance, firmware extraction and analysis, bootloader access, runtime exploitation, wireless protocol attacks, companion app review, and cloud API abuse.

LoRaWAN Sub-GHz Attacks

offensive-lorawan-sub-ghz

SnailSploit/Claude-Red

Methodology for capturing, analyzing, and replaying LoRaWAN and sub-GHz wireless traffic. Useful for testing IoT deployments, fixed-code remotes, garage doors, TPMS, and other devices in 433/868/915 MHz bands.

Z-Wave Smart Home Security Attack Guide

offensive-z-wave

SnailSploit/Claude-Red

A comprehensive guide detailing attack methodologies for Z-Wave smart home networks. Techniques covered include sniffing during inclusion (S0/S2), exploiting key derivation flaws, performing replay attacks on unauthenticated nodes, and crucial hub compromise (pivoting) to gain full control over the entire mesh network. Essential reading for IoT penetration testing.

Homelab Network Infrastructure Setup

homelab-network-setup

affaan-m/everything-claude-code

A comprehensive guide to designing and structuring a scalable home or small-lab network. This skill covers best practices for IP addressing, network segmentation (VLANs), selecting reliable gateways (like pfSense/OPNsense), and planning for future growth, ensuring stability and avoiding common pitfalls like Double NAT. Ideal for advanced users building robust IoT, server, and guest networks.

Advanced VLAN Segmentation For Home Networks

homelab-vlan-segmentation

affaan-m/everything-claude-code

A comprehensive guide on segmenting a home network using VLANs to dramatically enhance security. Learn how to isolate different device types—such as IoT gadgets, guests, and servers—from main PCs, preventing cross-segment malware spread and unauthorized communication. Covers setup steps for UniFi, pfSense, and OPNsense.

Homelab Network Infrastructure Setup

homelab-network-setup

A comprehensive guide to designing and structuring a scalable home or small-lab network. This skill covers best practices for IP addressing, network segmentation (VLANs), selecting reliable gateways (like pfSense/OPNsense), and planning for future growth, ensuring stability and avoiding common pitfalls like Double NAT. Ideal for advanced users building robust IoT, server, and guest networks.

Advanced VLAN Segmentation For Home Networks

homelab-vlan-segmentation

A comprehensive guide on segmenting a home network using VLANs to dramatically enhance security. Learn how to isolate different device types—such as IoT gadgets, guests, and servers—from main PCs, preventing cross-segment malware spread and unauthorized communication. Covers setup steps for UniFi, pfSense, and OPNsense.

Detect IoT Telemetry Anomalies

This utility detects and classifies various anomalies (such as spikes, flatlines, drift, or pattern breaks) within telemetry data streamed from IoT devices. It utilizes Z-score anomaly detection to provide actionable insights. This is crucial for investigating unusual device metrics, ensuring system health before deploying major firmware updates (canary advancement), or triaging fleet-wide operational alerts.

Manage IoT Firmware Rollouts

This tool orchestrates the entire firmware rollout lifecycle across large device fleets. It supports controlled, gradual deployment strategies, including canary testing and anomaly-gated advancement. Users can deploy new versions, check real-time status, execute rollbacks, or list all ongoing rollout campaigns, ensuring stable and reliable updates.

Manage IoT Device Fleets with Cognitum

This tool provides comprehensive management capabilities for Cognitum Seed device fleets. Users can perform various actions such as creating new fleets, listing existing ones, adding or removing individual devices, and deleting entire fleets. It helps maintain firmware policies and manage the lifecycle of connected IoT devices.

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