Initial commit

.gitignore

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+seed.txt
+random.txt
+*.wav

LICENSE

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+MIT License
+
+Copyright (c) 2023 Blockdrops LLC
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# AmbianceRNG
+
+This is a very simple proof of concept for generating true random numbers by
+feeding the python pseudo-random number generator with ambiental noise.
+
+While is not enforced, the ambiental noise is expected to be generated by
+having an input device that is able to capture sound from the environment
+
+A cheap and simple way to generate ambiental noise is to use a simple radio
+with antenna and headphone out and to connect the headphone to your computer.
+
+Be sure to tune your radio into an empty frequency so that the ambiental
+recording is purely background noise.
+
+## Benchmark
+
+At the moment, no one. Is more a fun thing than a production ready tool. Anyway, anyone is free and encouraged to run benchmarks and spot errors in this codebase.

main.py

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+# INFO
+# @author: TheCookingSenpai
+# @github: https://github.com/TheCookingSenpai
+# @homepage: https://github.com/TheCookingSenpai/AmbianceRNG
+#
+# @description:
+# This is a very simple proof of concept for generating true random numbers by
+# feeding the python pseudo-random number generator with ambiental noise.
+# While is not enforced, the ambiental noise is expected to be generated by
+# having an input device that is able to capture sound from the environment.
+# A cheap and simple way to generate ambiental noise is to use a simple radio
+# with antenna and headphone out and to connect the headphone to your computer.
+# Be sure to tune your radio into an empty frequency so that the ambiental
+# recording is purely background noise.
+#
+
+import pyaudio
+import wave
+from bitstring import BitArray
+import hashlib
+import random
+
+class AmbianceRNG:
+    
+	def __init__(self):
+		self.CHUNK = 1024
+		self.FORMAT = pyaudio.paInt16
+		self.CHANNELS = 1
+		self.RATE = 44100
+		self.RECORD_SECONDS = 2
+		self.WAVE_OUTPUT_FILENAME = "seed.wav"
+		self.frames = []
+		self.stream = None
+		self.device = None
+		self.bin_bytes = ''
+
+
+	def record_seed(self):
+        # Opening our device and setting up the stream for recording
+		self.device = pyaudio.PyAudio()
+		self.stream = self.device.open(format=self.FORMAT,
+					channels=self.CHANNELS,
+					rate=self.RATE,
+					input=True,
+					frames_per_buffer=self.CHUNK)
+		print("* detecting ambiental noise...")  
+        # Recording ambiental noise
+		for _ in range(int(self.RATE / self.CHUNK * self.RECORD_SECONDS)):
+			data = self.stream.read(self.CHUNK)
+			self.frames.append(data)
+		print("* done recording ambiental noise")
+		self.stream.stop_stream()
+		self.stream.close()
+		self.device.terminate()
+		return self.frames
+
+	def save_seed(self):
+		wf = wave.open(self.WAVE_OUTPUT_FILENAME, 'wb')
+		wf.setnchannels(self.CHANNELS)
+		wf.setsampwidth(self.device.get_sample_size(self.FORMAT))
+		wf.setframerate(self.RATE)
+		wf.writeframes(b''.join(self.frames))
+		wf.close()
+  
+	def serialize_seed(self):
+		print("* serializing ambiental noise... [ ]", end="\b\b", flush=True)
+		counter = 1 # Initialized to 1 to avoid unnecessary assignment later
+		bin_bytes = ''
+		with open(self.WAVE_OUTPUT_FILENAME, 'rb') as f:
+			all_bytes = f.read()
+			raw_bytes = all_bytes[44:] # Removing the first 44 bytes
+			self.bin_bytes = BitArray(raw_bytes)
+		print("\b\b\n* done serializing ambiental noise")
+		# Logging to file  
+		with open("seed.txt", "w") as f:
+			f.write(str(self.bin_bytes))
+	
+	def get_random_number(self, min, max):
+        # Using an hash representation is way faster than using the whole string			
+		hash_object = hashlib.sha256(str(self.bin_bytes).encode())
+		hex_dig = hash_object.hexdigest()
+		print(f"* using seed {hex_dig}")
+		with open("hash.txt", "a") as f:
+			f.write(f"{hex_dig}\n")
+        # Seeding the prng
+		random.seed(hex_dig, version=2)
+        # Getting a random number
+		arn = random.randint(min, max)
+		with open("random.txt", "a+") as f:
+			f.write(f"{arn} ")
+		with open("seeds_history.txt", "a+") as f:
+			f.write(f"{hex_dig}\n")
+		return arn
+  
+		
+	
+if __name__ == "__main__":	
+	counter = 0
+	while True:
+		arng = AmbianceRNG()
+		arng.record_seed()
+		arng.save_seed()
+		arng.serialize_seed()
+		rn = arng.get_random_number(1, 100)
+		counter += 1
+		print(f"Produced {counter} random numbers")
+		print(rn)

requirements.txt

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+pyaudio
+bitstring