True random number generator (TRNG) from physical measurements

1. PRNG versus TRNG

A PRNG produces a deterministic sequence from a seed. A TRNG relies on measuring a physical process that cannot be practically recreated in the same state.

Big Bang Entropy treats SDR receivers as input sources for a TRNG pipeline, not as a standalone cryptographic guarantee without further processing.

2. Why radio noise is useful

Radio noise combines environmental, electronic, and natural background contributions. With proper sampling and quality control, it can feed a true random number generator.

3. Tests and limits

Randomness is evaluated statistically, but tests are not absolute proof. The system therefore combines physical measurements, audits, and cryptographic mixing.

4. CSPRNG integration

The safest model is to use the TRNG as an additional entropy source for a local CSPRNG, not as the only critical component.

python3 - <<'PY'
import os, requests
seed = requests.get("https://entropy.sparksome.pl/raw?bytes=64", timeout=5).content
print((int.from_bytes(seed, "big") % 1000000))
PY