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TECHNICAL GUIDE OPEN SOURCE

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Randomness testing: ENT, rngtest, Dieharder, and entropy audits

Big Bang Entropy describes a testing model where raw samples and output bytes are evaluated with statistical test suites and monitored over time.

1. Why test randomness

Statistical tests help detect bias, repetitions, correlations, and source failures. They do not prove absolute randomness, but they are an important alarm system.

For a physical entropy generator, testing matters because radio conditions and hardware behavior can change over time.

2. ENT, rngtest, and Dieharder

Tools such as ENT, rngtest, and Dieharder examine bit balance, runs, correlations, byte distribution, and behavior across larger samples.

Audit_Score = Tests(ENT || rngtest || Dieharder || FIPS_140_2)

3. Continuous audits

One good result is not enough. Big Bang Entropy relies on recurring reports, audit history, and drift detection for node behavior.

Open current randomness reports ->

4. Reading results

Quality reports should be treated as diagnostic signals. Production integrations should combine them with local monitoring and their own security policy.

curl -s "https://entropy.sparksome.pl/raw?bytes=1048576" --output sample.bin
ent sample.bin