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Bananagotchi

This is the main source for the BananaPi fork:

  • BPi M4 Zero

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bananagotchi is an A2C-based "AI" leveraging bettercap that learns from its surrounding Wi-Fi 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), bananagotchi tunes its parameters over time to get better at pwning Wi-Fi things to in the environments you expose it to.

More specifically, bananagotchi 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 bananagotchi learns. (You can read more about how bananagotchi learns in the Usage doc.)

Keep in mind: Unlike the usual RL simulations, bananagotchi learns over time. Time for a bananagotchi 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 bananagotchi 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 bananagotchi when it tells you it's boring!** Bring it into novel Wi-Fi 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.bananagotchi.ai

Links

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

License

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