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Wifi Wireless

CommunityPopular
zhaoxuya520
wifi-wireless

Use for authorized wireless security assessment including Wi-Fi capture, WPA handshake analysis, rogue AP detection research, and lab-only deauth testing.

Overview

Publisherzhaoxuya520
Repositoryreverse-skill
Skill namewifi-wireless
Stars
41K
Forks
5.8K
Bundled files
1
LicenseMIT
Links
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zhaoxuya520 on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zhaoxuya520/reverse-skill/tree/main/skills/wifi-wireless
  4. 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.
2

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/zhaoxuya520/reverse-skill.git /tmp/reverse-skill
mkdir -p .claude/skills
cp -r /tmp/reverse-skill/skills/wifi-wireless .claude/skills/wifi-wireless
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wifi Wireless 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 Wifi Wireless 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 Wifi Wireless 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.

Wi-Fi / Wireless Security

ACTION REQUIRED(读完后立刻执行)

  1. NOW: 读取 precedent-pentest;无线攻击法律风险高,必须书面授权与物理范围
  2. NOW: scope 写明目标 SSID/BSSID/场地;禁止扫邻居网络
  3. NEXT: 确认适配器监听模式能力
  4. ACT: 侦察 → 采集 → 分析(实验室优先)

适用场景

  • 授权 Wi-Fi 安全评估
  • WPA/WPA2 握手采集与离线评估
  • 流氓 AP / 钓鱼热点检测研究
  • 企业无线隔离与门户安全

工作流

text
□ iwconfig / airmon-ng 进入 monitor(合法环境)
□ airodump-ng 锁定目标 BSSID 频道
□ 握手或 PMKID 采集(仅目标)
□ hashcat/aircrack 离线评估口令策略
□ 报告:加密类型、隔离、门户绕过、建议

工具链

工具用途
aircrack-ng suite采集/评估
hcxdumptool / hcxtoolsPMKID
hashcat口令评估
Wireshark管理帧分析

参考

  • references/wireless-lab-rules.md
  • ../pentest-tools/ ../attack-chain/(近源章节)

路由上下文

上游: MASTER R29
MUST NOT: 未授权 deauth、对非目标客户网络操作

任务完成自检

  • 是否严格锁定目标 BSSID?
  • 是否在报告中给出加固建议?
  • Checklist?

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Wifi Wireless AI skill do?

Use for authorized wireless security assessment including Wi-Fi capture, WPA handshake analysis, rogue AP detection research, and lab-only deauth testing.

Why use Wifi Wireless on TypingMind?

Because you install it once and use it with any model. Wifi Wireless 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 Wifi Wireless in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/skills/wifi-wireless. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Wifi Wireless?

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 Wifi Wireless?

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

Is the Wifi Wireless AI skill free?

Yes. It is published on GitHub by zhaoxuya520 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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