Category 9 — Cryptography / Security
Measure the information density of text or files using Shannon entropy — bits per character and total bits.
Input Text / File box — results update instantly as you type.Load File / drag & drop a file to measure the entropy of its raw bytes — ideal for keys, firmware, or compressed data.English phrase, Repeating pattern, Random-like hex, or All same char — to load a ready-made input.Shannon entropy (bits/char), for the average information per character.Total entropy (bits), Unique characters, and Byte-level entropy (bits/byte) for a fuller picture.Character Frequency Distribution to see each character's share, plus the What this means interpretation.Higher entropy means harder to guess. Compare candidate passphrases and see which has genuine variety rather than just more length.
API keys, session tokens, and hashes should look near-random. A low score on supposedly random output is a red flag worth investigating.
Well-encrypted or compressed data should approach maximum entropy. Repeating structure often reveals padding, headers, or weak encryption.
Feed in logs or generated strings to catch accidental repetition — like a counter that isn't actually mixing in randomness.
See Shannon's formula in action: English prose lands around 3.5–4.5 bits/char, while truly random bytes reach 8 bits/byte.
Everything runs in your browser. Your text is never uploaded, logged, or sent to a server — safe for sensitive payloads.
Shannon entropy is a measure of how much information — or surprise — a message contains, expressed in bits. A highly predictable message (like aaaaaaaa) has low entropy; a string of unrelated symbols has high entropy.
Shannon entropy (bits/char) is the average information carried by a single character. Total entropy (bits) is that value multiplied by the string length, giving the information content of the whole message.
It depends on context. Natural-language English runs about 3.5–4.5 bits/char, random printable ASCII about 6.5–6.7 bits/char, and truly random bytes up to 8 bits/byte. The vs. max (8 bits) stat shows how close you are to the theoretical ceiling.
Entropy measures unpredictability. When a few symbols dominate — like a repeated abcabc pattern — the outcome is easy to predict, so the calculated entropy drops even if the text is long.
Not on its own. Entropy is a strong signal of randomness, but it says nothing about whether data is encrypted or trustworthy. High entropy is necessary for good keys and ciphertext, but not sufficient for security.
Character entropy treats each distinct visible character as a symbol. Byte-level entropy (bits/byte) instead buckets the text by each character's numeric code value, which can differ when visually similar characters have distinct encodings.
Yes. Click Load File or drop a file onto the input panel. The tool reads the file's raw bytes and reports bits/byte entropy, total bits, and the byte-value distribution — perfect for checking keyfiles, encrypted blobs, or compressed archives.
Never. All computation happens locally in JavaScript. Your input is not sent to, stored on, or logged by any server.