Files
tea3-py/src/tea3/tea3linearbias.py
T
2026-05-19 10:15:35 +02:00

81 lines
1.6 KiB
Python

from __future__ import annotations
from dataclasses import dataclass
from random import Random
from tea3.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
matches: int
p_match: float
bias: float
estimated_needed_samples: float
def estimate_black_box_output_bias(
*,
key: list[int],
output_byte_index: int = 0,
output_bit: int = 0,
samples: int = 10000,
seed: int = 1,
) -> BiasResult:
rng = Random(seed)
matches = 0
for _ in range(samples):
frame_number = rand_frame_number(rng)
tea = Tea3(frame_number, key)
for _ in range(output_byte_index + 1):
tea.next_byte()
out_byte = tea.iv_view() >> 56
bit = (out_byte >> output_bit) & 1
if bit == 0:
matches += 1
p_match = matches / samples
bias = abs(p_match - 0.5)
needed = float("inf") if bias == 0 else 1.0 / (bias * bias)
return BiasResult(
samples=samples,
matches=matches,
p_match=p_match,
bias=bias,
estimated_needed_samples=needed,
)
def main():
rng = Random(123)
key = rand_key(rng)
res = estimate_black_box_output_bias(
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")
print(res)
if __name__ == "__main__":
main()