This fork of Pwnagotchi is only for 64-bit Raspberry Pi's. Such as the 02W, 3(b+) and 4(b) and the new Raspberry Pi 5!!.
It seems the Pi 5 is unable to run in monitor mode, will keep you updated on this.
If you are using an older 32-bit version Raspberry Pi, ZeroWH, use this fork and make sure you download the armhf version.
Download the latest image file here, and let it auto-update from here on out.
Use RPi imager to flash, please don't flash a new user as this will mess with logs created.
- Select
Use Custom Image - Browse for the downloaded image file
- Select No under
Use OS Customization
SSH credentials are pi/raspberry.
I would like to thank
for donating!
Pwnagotchi 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.
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 Wi-Fi 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 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.
| Official Links | |
|---|---|
| Website | pwnagotchi.ai |
| Forum | community.pwnagotchi.ai |
| Slack | pwnagotchi.slack.com |
| Subreddit | r/pwnagotchi |
| @pwnagotchi |
pwnagotchi is made with ♥ by @evilsocket and the amazing dev team. It is released under the GPL3 license.