linear and differential bias change

src/tea3/tea3linearbias.py

@@ -5,9 +5,15 @@ from random import Random
 
 from .tea3 import Tea3
 
+
 def rand_key(rng: Random) -> list[int]:
     return [rng.getrandbits(8) for _ in range(10)]
 
+
+def rand_frame_number(rng: Random) -> int:
+    return rng.getrandbits(32)
+
+
 @dataclass
 class BiasResult:
     samples: int
@@ -16,9 +22,10 @@ class BiasResult:
     bias: float
     estimated_needed_samples: float
 
+
 def estimate_black_box_output_bias(
     *,
-    frame_number: int,
+    key: list[int],
     output_byte_index: int = 0,
     output_bit: int = 0,
     samples: int = 10000,
@@ -28,12 +35,12 @@ def estimate_black_box_output_bias(
     matches = 0
 
     for _ in range(samples):
-        key = rand_key(rng)
+        frame_number = rand_frame_number(rng)
         tea = Tea3(frame_number, key)
 
-        out_byte = 0
         for _ in range(output_byte_index + 1):
             tea.next_byte()
+
         out_byte = tea.iv_view() >> 56
 
         bit = (out_byte >> output_bit) & 1
@@ -52,16 +59,22 @@ def estimate_black_box_output_bias(
         estimated_needed_samples=needed,
     )
 
+
 def main():
-    frame = 0x12345678
+    rng = Random(123)
+    key = rand_key(rng)
 
     res = estimate_black_box_output_bias(
-        frame_number=frame,
+        key=key,
         output_byte_index=0,
         output_bit=0,
         samples=20000,
         seed=123,
     )
     print("black-box output bias")
-    print("expected non-biased p_match: 1/2") # 2 possibilities for 1 bit
+    print("expected non-biased p_match: 1/2")
     print(res)
+
+
+if __name__ == "__main__":
+    main()