[Pwnagotchi](https://twitter.com/pwnagotchi) is an "AI" that learns from the WiFi environment and instruments bettercap in order to maximize the WPA key material (any form of handshake that is crackable, including [PMKIDs](https://www.evilsocket.net/2019/02/13/Pwning-WiFi-networks-with-bettercap-and-the-PMKID-client-less-attack/), full and half WPA handshakes) captured.
Specifically, it's using an [LSTM with MLP feature extractor](https://stable-baselines.readthedocs.io/en/master/modules/policies.html#stable_baselines.common.policies.MlpLstmPolicy) as its policy network for the [A2C agent](https://stable-baselines.readthedocs.io/en/master/modules/a2c.html), here is [a very good intro](https://hackernoon.com/intuitive-rl-intro-to-advantage-actor-critic-a2c-4ff545978752) on the subject.
Instead of playing [Super Mario or Atari games](https://becominghuman.ai/getting-mario-back-into-the-gym-setting-up-super-mario-bros-in-openais-gym-8e39a96c1e41?gi=c4b66c3d5ced), pwnagotchi will tune over time [its own parameters](https://github.com/evilsocket/pwnagotchi/blob/master/sdcard/rootfs/root/pwnagotchi/config.yml#L54), effectively learning to get better at pwning WiFi things. **Keep in mind:** unlike the usual RL simulations, pwnagotchi learns over time (where 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 it to perform amazingly well at the beginning, as it'll be exploring several combinations of parameters ... but listen to it when it's bored, bring it with you and have it observe new networks and capture new handshakes and you'll see :)
Multiple units can talk to each other, advertising their own presence using a parasite protocol I've built on top of the existing dot11 standard, by broadcasting custom information elements. Over time, two or more units learn to cooperate if they detect each other's presence, by dividing the available channels among them.
Depending on the status of the unit, several states and states transitions are configurable and represented on the display as different moods, expressions and sentences.
If instead you just want to use your own parameters and save battery and CPU cycles, you can disable the AI in `config.yml` and enjoy an automated deauther, WPA handshake sniffer and portable bettercap + webui dedicated hardware.
**THIS IS STILL ALPHA STAGE SOFTWARE, IF YOU DECIDE TO TRY TO USE IT, YOU ARE ON YOUR OWN, NO SUPPORT WILL BE PROVIDED, NEITHER FOR INSTALLATION OR FOR BUGS**
However, there's [a Slack channel](https://join.slack.com/t/pwnagotchi/shared_invite/enQtNzc4NzY3MDE2OTAzLTg5NmNmNDJiMDM3ZWFkMWUwN2Y5NDk0Y2JlZWZjODlhMmRhNDZiOGMwYjJhM2UzNzA3YjA5NjJmZGY5NGI5NmI).
You need to configure the display type in `config.yml` where you can find `ui.display.type`. If your display does not work after changing this setting, you might need to complete remove power from the Raspberry and make a clean boot.
One thing to note, not all displays are created equaly, TFT displays for example work similar to an HDMI display, and they are not supported, currently all the displays supported are I2C displays.
### Color and Black & White displays
Some of the supported displays support Black & White and Coloured versions, one common question is regarding refresh speed of said displays.
Color displays have a much slower refresh rate, in some cases it can take up to 15 seconds, if slow refresh rates is something that you want to avoid we advise you to use Black & White displays
### FPS
You can configure the refresh interval of the display on config.yml, we advise to use a slow refresh to not shorten the lifetime of your display.
Another option is to change fps to 0, which will only refresh when changes are made to the screen.
- Raspbian + [nexmon patches](https://re4son-kernel.com/re4son-pi-kernel/) for monitor mode, or any Linux with a monitor mode enabled interface (if you tune config.yml).
**Do not try with Kali on the Raspberry Pi 0 W, it is compiled without hardware floating point support and TensorFlow is simply not available for it, use Raspbian.**
If you connect to the unit via `usb0` (thus using the data port), you might want to use the `scripts/linux_connection_share.sh` script to bring the interface up on your end and share internet connectivity from another interface, so you can update the unit and generally download things from the internet on it.
The UI is available either via display if installed, or via http://pwnagotchi.local:8080/ if you connect to the unit via `usb0` and set a static address on the network interface (change `pwnagotchi` with the hostname of your unit).
* **CH**: Current channel the unit is operating on or `*` when hopping on all channels.
* **APS**: Number of access points on the current channel and total visible access points.
* **UP**: Time since the unit has been activated.
* **PWND**: Number of handshakes captured in this session and number of unique networks we own at least one handshake of, from the beginning.
* **AUTO**: This indicates that the algorithm is running with AI disabled (or still loading), it disappears once the AI dependencies have been bootrapped and the neural network loaded.
as python files and then edit the `config.yml` file (`main.plugins` value) to point to their containing folder. Check the [plugins folder](https://github.com/evilsocket/pwnagotchi/tree/master/sdcard/rootfs/root/pwnagotchi/scripts/pwnagotchi/plugins/default/) for a list of default
plugins and all the callbacks that you can define for your own customizations.
the `PARTUUID`s for `rootfs` and `boot` partitions are the same in `/etc/fstab`. Use `sudo blkid` to find those values when you are using `create_sibling.sh`.
`pwnagotchi` is made with ♥ by [@evilsocket](https://twitter.com/evilsocket) and the [amazing dev team](https://github.com/evilsocket/pwnagotchi/graphs/contributors). It's released under the GPL3 license.
