Entropy Calculator
التفاصيل التقنية
How the Entropy Calculator Works
What the Tool Does
The Entropy Calculator measures the Shannon entropy of a text string, reporting how many bits of information it contains per character and in total. Higher entropy means the string is more random and less predictable; lower entropy indicates repetitive or structured content. The tool also shows character frequency distribution to help visualise the source of entropy.
Common Developer Use Cases
Security engineers use entropy calculators to evaluate the randomness of passwords, API keys, tokens, and cryptographic seeds before using them in production. Developers use it to check whether a generated secret has sufficient entropy for its intended security level, to audit password policies, and to detect suspiciously low-entropy strings that may indicate weak or predictable credentials.
Data Formats, Types, or Variants
Shannon entropy H is calculated as -Σ p(x) log2 p(x) over all unique characters x, where p(x) is the probability of character x in the string. The result is expressed in bits per character (maximum log2(alphabet size)) and total bits (bits per character × string length). For a random 20-character password drawn from a 95-character printable ASCII set the theoretical maximum entropy is about 131 bits.
Common Pitfalls and Edge Cases
Shannon entropy measures statistical randomness of the sample but does not guarantee cryptographic security — a string can have high entropy while still being generated by a weak PRNG. Entropy of a short string is a poor estimator of true randomness because the character distribution has high variance. Entropy is calculated over the visible characters only; encoding (hex, Base64) inflates apparent length without increasing underlying randomness.
When to Use This Tool vs Code
Use this browser tool for quick entropy checks during security reviews or credential audits. For automated secret strength validation in CI pipelines or application code, implement Shannon entropy as a utility function or use a dedicated password-strength library that combines entropy with pattern detection for a more complete assessment.