Entropy Breakdown
The entropy module provides a detailed min-entropy assessment inspired by NIST SP 800-90B. It runs multiple estimators and reports conservative values.
Implemented in openentropy_core::conditioning.
Estimators
Section titled “Estimators”| Estimator | Method | Notes |
|---|---|---|
| Shannon | Information entropy | Classical H = -sum p log2 p, max 8 bits/byte |
| MCV | Most common value | Conservative min-entropy estimate |
| Collision | Collision spacing | Repetition-distance based estimate |
| Markov | Transition model | Captures sequential dependence |
| Compression | Universal compression | Pattern recurrence estimate |
| t-Tuple | Tuple frequency | Repeated tuple dominance estimate |
min_entropy uses the conservative estimate used by the core report; a
diagnostic floor is also available for additional caution.
Entropy Grade
Section titled “Entropy Grade”| Grade | Min-Entropy | Interpretation |
|---|---|---|
| A | >= 6.0 | Excellent density for cryptographic seeding |
| B | >= 4.0 | Good entropy density |
| C | >= 2.0 | Moderate redundancy present |
| D | >= 1.0 | High predictability risk |
| F | < 1.0 | Insufficient entropy |
When To Use
Section titled “When To Use”--profile securityfor security-focused validation--profile deepfor broad research characterization--entropyto enable entropy breakdown in custom runs