added support for 5Ghz

sdcard/rootfs/root/pwnagotchi/scripts/core/__init__.py

@@ -40,6 +40,17 @@ def iface_address(ifname):
             return line.split(' ')[1].strip()
     return None
 
+
+def iface_channels(ifname):
+    channels = []
+    output = subprocess.getoutput("/sbin/iwlist %s freq" % ifname)
+    for line in output.split("\n"):
+        line = line.strip()
+        if line.startswith("Channel "):
+            channels.append(int(line.split()[1]))
+    return channels
+
+
 def led(on=True):
     with open('/sys/class/leds/led0/brightness', 'w+t') as fp:
         fp.write("%d" % (0 if on is True else 1))

sdcard/rootfs/root/pwnagotchi/scripts/pwnagotchi/agent.py

@@ -28,6 +28,7 @@ class Agent(Client, AsyncAdvertiser, AsyncTrainer):
         self._started_at = time.time()
         self._filter = None if config['main']['filter'] is None else re.compile(config['main']['filter'])
         self._current_channel = 0
+        self._supported_channels = core.iface_channels(config['main']['iface'])
         self._view = view
         self._access_points = []
         self._last_pwnd = None
@@ -43,6 +44,9 @@ class Agent(Client, AsyncAdvertiser, AsyncTrainer):
             pass
         return False
 
+    def supported_channels(self):
+        return self._supported_channels
+
     def on_ai_ready(self):
         self._view.on_ai_ready()
 
@@ -107,6 +111,7 @@ class Agent(Client, AsyncAdvertiser, AsyncTrainer):
                     core.log("waiting for monitor interface %s ..." % mon_iface)
                     time.sleep(1)
 
+        core.log("supported channels: %s" % self._supported_channels)
         core.log("handshakes will be collected inside %s" % self._config['bettercap']['handshakes'])
 
         self._reset_wifi_settings()

sdcard/rootfs/root/pwnagotchi/scripts/pwnagotchi/ai/gym.py

@@ -11,28 +11,21 @@ from pwnagotchi.ai.parameter import Parameter
 class Environment(gym.Env):
     metadata = {'render.modes': ['human']}
     params = [
-                 # Parameter('advertise', trainable=False),
-                 # Parameter('deauth', trainable=False),
-                 # Parameter('associate', trainable=False),
+        Parameter('min_rssi', min_value=-200, max_value=-50),
+        Parameter('ap_ttl', min_value=30, max_value=600),
+        Parameter('sta_ttl', min_value=60, max_value=300),
 
-                 Parameter('min_rssi', min_value=-200, max_value=-50),
-                 Parameter('ap_ttl', min_value=30, max_value=600),
-                 Parameter('sta_ttl', min_value=60, max_value=300),
-
-                 Parameter('recon_time', min_value=5, max_value=60),
-                 Parameter('max_inactive_scale', min_value=3, max_value=10),
-                 Parameter('recon_inactive_multiplier', min_value=1, max_value=3),
-                 Parameter('hop_recon_time', min_value=5, max_value=60),
-                 Parameter('min_recon_time', min_value=1, max_value=30),
-                 Parameter('max_interactions', min_value=1, max_value=25),
-                 Parameter('max_misses_for_recon', min_value=3, max_value=10),
-                 Parameter('excited_num_epochs', min_value=5, max_value=30),
-                 Parameter('bored_num_epochs', min_value=5, max_value=30),
-                 Parameter('sad_num_epochs', min_value=5, max_value=30),
-             ] + [
-                 Parameter('_channel_%d' % ch, min_value=0, max_value=1, meta=ch + 1) for ch in
-                 range(featurizer.histogram_size)
-             ]
+        Parameter('recon_time', min_value=5, max_value=60),
+        Parameter('max_inactive_scale', min_value=3, max_value=10),
+        Parameter('recon_inactive_multiplier', min_value=1, max_value=3),
+        Parameter('hop_recon_time', min_value=5, max_value=60),
+        Parameter('min_recon_time', min_value=1, max_value=30),
+        Parameter('max_interactions', min_value=1, max_value=25),
+        Parameter('max_misses_for_recon', min_value=3, max_value=10),
+        Parameter('excited_num_epochs', min_value=5, max_value=30),
+        Parameter('bored_num_epochs', min_value=5, max_value=30),
+        Parameter('sad_num_epochs', min_value=5, max_value=30),
+    ]
 
     def __init__(self, agent, epoch):
         super(Environment, self).__init__()
@@ -41,6 +34,12 @@ class Environment(gym.Env):
         self._epoch_num = 0
         self._last_render = None
 
+        channels = agent.supported_channels()
+        Environment.params += [
+            Parameter('_channel_%d' % ch, min_value=0, max_value=1, meta=ch + 1) for ch in
+            range(featurizer.histogram_size) if ch + 1 in channels
+        ]
+
         self.last = {
             'reward': 0.0,
             'observation': None,

sdcard/rootfs/root/pwnagotchi/scripts/pwnagotchi/mesh/wifi.py

@@ -1,7 +1,7 @@
 SignatureAddress = 'de:ad:be:ef:de:ad'
 BroadcastAddress = 'ff:ff:ff:ff:ff:ff'
 Dot11ElemID_Identity = 222
-NumChannels = 14
+NumChannels = 140
 
 def freq_to_channel(freq):
     if freq <= 2472: