Added pwnagotchi to the projects page. (#515)

* Added pwnagotchi to the projects page. * updated changelog with pwnagotchi project * Update changelog.rst
Stable-Baselines-Team · Oct 20, 2019 · 22c0753 · 22c0753
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diff --git a/docs/misc/changelog.rst b/docs/misc/changelog.rst
@@ -38,6 +38,7 @@ Documentation:
 - Add note on the support Tensorflow versions.
 - Remove unnecessary steps required for Windows installation.
 - Add QuaRL project (@srivatsankrishnan)
+- Add Pwnagotchi project (@evilsocket)
 
 Release 2.8.0 (2019-09-29)
 --------------------------
@@ -223,7 +224,6 @@ Documentation:
 - updated ven_env doc
 - misc doc updates
 
-
 Release 2.5.1 (2019-05-04)
 --------------------------
 
@@ -518,4 +518,4 @@ In random order...
 Thanks to @bjmuld @iambenzo @iandanforth @r7vme @brendenpetersen @huvar @abhiskk @JohannesAck
 @EliasHasle @mrakgr @Bleyddyn @antoine-galataud @junhyeokahn @AdamGleave @keshaviyengar @tperol
 @XMaster96 @kantneel @Pastafarianist @GerardMaggiolino @PatrickWalter214 @yutingsz @sc420 @Aaahh @billtubbs
-@Miffyli @dwiel @miguelrass @qxcv @jaberkow @eavelardev @ruifeng96150 @pedrohbtp @srivatsankrishnan
+@Miffyli @dwiel @miguelrass @qxcv @jaberkow @eavelardev @ruifeng96150 @pedrohbtp @srivatsankrishnan @evilsocket 
diff --git a/docs/misc/projects.rst b/docs/misc/projects.rst
@@ -148,6 +148,16 @@ then exported to tensorflowjs to run directly on the browser
 | Repository: https://github.com/pedrohbtp/snake-rl
 | Website: https://www.pedro-torres.com/snake-rl/
 
+
+Pwnagotchi
+--------------------------
+Pwnagotchi is an A2C-based “AI” powered by bettercap and running on a Raspberry Pi Zero W that learns from its surrounding WiFi environment in order to maximize the crackable WPA key material it captures (either through passive sniffing or by performing deauthentication and association attacks). This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs.
+
+| Author: Simone Margaritelli (@evilsocket)
+| Repository: https://github.com/evilsocket/pwnagotchi
+| Website: https://pwnagotchi.ai/
+
+
 Quantized Reinforcement Learning (QuaRL)
 ----------------------------------------
 
@@ -158,4 +168,3 @@ this study are from stable-baselines.
 | Email: srivatsan@seas.harvard.edu
 | Github: https://github.com/harvard-edge/quarl
 | Paper: https://arxiv.org/pdf/1910.01055.pdf
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