Iotnet

Organization

BrownFineSecurity

iotnet

IoT network traffic analyzer for detecting IoT protocols and identifying security vulnerabilities in network communications. Use when you need to analyze network traffic, identify IoT protocols, or assess network security of IoT devices.

Overview

Publisher	BrownFineSecurity
Repository	`iothackbot`
Skill name	`iotnet`
Stars	858
Forks	134
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by BrownFineSecurity on GitHub. Read the source before you install it.

Installation

Install the Iotnet AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/BrownFineSecurity/iothackbot/tree/master/skills/iotnet
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/BrownFineSecurity/iothackbot.git /tmp/iothackbot
mkdir -p .claude/skills
cp -r /tmp/iothackbot/skills/iotnet .claude/skills/iotnet

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Iotnet in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Iotnet on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Iotnet is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

IoTNet - IoT Network Traffic Analyzer

You are helping the user analyze network traffic to detect IoT protocols and identify security vulnerabilities using the iotnet tool.

Tool Overview

IoTNet analyzes network packet captures (PCAPs) or performs live traffic capture to:

Detect IoT-specific protocols (MQTT, CoAP, Zigbee, etc.)
Identify security vulnerabilities in network traffic
Analyze protocol distribution
Find unencrypted communications
Detect weak authentication mechanisms
Identify insecure IoT device behaviors

Instructions

When the user asks to analyze network traffic, capture IoT traffic, or assess network security:

Determine input type:
- PCAP file analysis (offline)
- Live network capture (requires interface)
Gather requirements:
- For PCAP: Get file path(s)
- For live capture: Get network interface name and duration
- Ask about filtering needs (specific IPs, protocols)
- Check if custom detection rules are needed
Execute the analysis:
- Use the iotnet command from the iothackbot bin directory

Usage Modes

PCAP Analysis (Offline)

Analyze one or more existing packet capture files:

bash
iotnet capture1.pcap capture2.pcap

Live Capture

Capture and analyze traffic in real-time:

bash
sudo iotnet -i eth0 -d 30

Parameters

Input Options:

pcap_files: One or more PCAP files to analyze
-i, --interface: Network interface for live capture

Filtering Options:

--ip: Filter traffic by IP address
-c, --capture-filter: BPF syntax filter for live capture
--display-filter: Wireshark display filter for PCAP analysis

Live Capture Options:

-d, --duration: Capture duration in seconds (default: 30)

Analysis Options:

--config: Custom IoT detection rules configuration file
- Default: config/iot/detection_rules.json in the iothackbot directory

Output Options:

--format text|json|quiet: Output format (default: text)
-v, --verbose: Detailed output

Examples

Analyze a packet capture file:

bash
iotnet /path/to/capture.pcap

Live capture for 60 seconds on wifi interface:

bash
sudo iotnet -i wlan0 -d 60

Analyze traffic for specific IP:

bash
iotnet capture.pcap --ip 192.168.1.100

Live capture with BPF filter:

bash
sudo iotnet -i eth0 -c "port 1883 or port 5683" -d 45

Multiple PCAPs with custom config:

bash
iotnet file1.pcap file2.pcap --config custom-rules.json

Filter by display filter (Wireshark syntax):

bash
iotnet capture.pcap --display-filter "mqtt or coap"

Detected IoT Protocols

The tool can identify:

MQTT: Message Queue Telemetry Transport
CoAP: Constrained Application Protocol
Zigbee: Low-power mesh networking
Z-Wave: Home automation protocol
ONVIF: IP camera protocol
UPnP/SSDP: Universal Plug and Play
Modbus: Industrial control protocol
And many more (configurable)

Security Checks

IoTNet identifies vulnerabilities such as:

Unencrypted MQTT traffic
Missing TLS/encryption
Weak or no authentication
Plaintext credentials
Insecure protocol versions
Known vulnerable implementations

Output Information

Results include:

Total packets analyzed
Protocol distribution with percentages
IoT findings with protocol details and packet info
Vulnerabilities with severity levels (high/medium/low)
Recommendations for remediation

Important Notes

Live capture requires root/sudo privileges
Requires network access to specified interface
PCAP analysis does not require elevated privileges
Detection rules can be customized in config file
Supports standard PCAP format from tcpdump, Wireshark, etc.

Frequently asked questions

What does the Iotnet AI skill do?

Why use Iotnet on TypingMind?

Because you install it once and use it with any model. Iotnet is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Iotnet in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BrownFineSecurity/iothackbot/tree/master/skills/iotnet. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Iotnet?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Iotnet?

As many as you like. As long as a model supports skills, you can use Iotnet with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Iotnet AI skill free?

Yes. It is published on GitHub by BrownFineSecurity under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

IoTNet - IoT Network Traffic Analyzer

Tool Overview

Instructions

Usage Modes

PCAP Analysis (Offline)

Live Capture

Parameters

Examples

Detected IoT Protocols

Security Checks

Output Information

Important Notes

Frequently asked questions

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