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项目介绍

evilsocket/pwnagotchi 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 Other 许可证,目前获得 9.2k 个 Star、1.1k 次 Fork。

仓库全名
evilsocket/pwnagotchi
开源许可证
Other
Star 数
9.2k
Fork 数
1.1k
未关闭 Issue
267

README 摘要

Pwnagotchi is an A2C-based "AI" leveraging bettercap that learns from its surrounding WiFi environment to maximize the crackable WPA key material it captures (either passively, or by performing authentication and association attacks). This material is collected as PCAP files containing any form of handshake supported by hashcat, including PMKIDs, full and half WPA handshakes. Instead of merely playing Super Mario or…

完整内容见 GitHub 原始 README 或本页 。

常见问题

pwnagotchi 用什么语言开发?

主要使用 Python 编写,采用 Other 许可证,目前有 9.2k 个 Star。

pwnagotchi 可以免费商用吗?

仓库标注的许可证为 Other,商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 pwnagotchi 的源码?

可以直接克隆仓库:git clone https://github.com/evilsocket/pwnagotchi.git,默认分支为 master;安装与运行步骤见仓库 README。

pwnagotchi 最近还在维护吗?

仓库最近一次更新为 8月19日,当前有 267 个未关闭 Issue;Star 数为 9.2k,可作为社区活跃度的参考。

简要分析

热度分
11662
价值分
5884
活跃状态
活跃

语言占比

HTML
Makefile
Python

Release

README

Release Software License Contributors follow on Twitter

This project is 100% made by humans.

Pwnagotchi is an A2C-based “AI” leveraging bettercap that learns from its surrounding WiFi environment to maximize the crackable WPA key material it captures (either passively, or by performing authentication and association attacks). This material is collected as PCAP files containing any form of handshake supported by hashcat, including PMKIDs, full and half WPA handshakes.

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Instead of merely playing Super Mario or Atari games like most reinforcement learning-based “AI” (yawn), Pwnagotchi tunes its parameters over time to get better at pwning WiFi things to in the environments you expose it to.

More specifically, Pwnagotchi is using an LSTM with MLP feature extractor as its policy network for the A2C agent. If you’re unfamiliar with A2C, here is a very good introductory explanation (in comic form!) of the basic principles behind how Pwnagotchi learns. (You can read more about how Pwnagotchi learns in the Usage doc.)

Keep in mind: Unlike the usual RL simulations, Pwnagotchi learns over time. Time for a Pwnagotchi is measured in epochs; a single epoch can last from a few seconds to minutes, depending on how many access points and client stations are visible. Do not expect your Pwnagotchi to perform amazingly well at the very beginning, as it will be exploring several combinations of key parameters to determine ideal adjustments for pwning the particular environment you are exposing it to during its beginning epochs … but ** listen to your Pwnagotchi when it tells you it’s boring!** Bring it into novel WiFi environments with you and have it observe new networks and capture new handshakes—and you’ll see. :)

Multiple units within close physical proximity can “talk” to each other, advertising their presence to each other by broadcasting custom information elements using a parasite protocol I’ve built on top of the existing dot11 standard. Over time, two or more units trained together will learn to cooperate upon detecting each other’s presence by dividing the available channels among them for optimal pwnage.

Documentation

https://www.pwnagotchi.ai

  Official Links
Website pwnagotchi.ai
Forum community.pwnagotchi.ai
Slack pwnagotchi.slack.com
Subreddit r/pwnagotchi
Twitter @pwnagotchi

License

pwnagotchi is made with ♥ by @evilsocket and the amazing dev team. It is released under the GPL3 license.

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