Analyze letter, character, word, bigram, and trigram frequencies in any text. Compare distributions against language profiles and use frequency analysis for classical cipher cryptanalysis.
The quick brown fox jumps over the lazy dog
This pangram contains every letter of the English alphabet at least once.
KHOOR ZRUOG
HELLO WORLD encoded with Caesar cipher (shift 3). K, H, U, O, Z, G dominate — shifted from H, E, L, W, O, D.
To be or not to be that is the question
A famous English sentence for testing natural language letter distribution.
ATTACK AT DAWN ATTACK AT DUSK
A short phrase with repeated words and letter patterns. Useful for testing word frequency, bigrams, trigrams, and repeated-symbol analysis.
Frequency analysis measures how often letters, symbols, words, or character groups appear in a text. Natural languages follow predictable statistical patterns, which means some letters occur far more frequently than others. In English, for example, E, T, A, O, I, N, S, H, and R are among the most common letters.
This tool calculates frequencies for letters, words, bigrams, and trigrams, allowing you to compare an unknown text against expected language distributions. Large deviations from normal language patterns often reveal encryption, encoding, or unusual text structures.
The results can be sorted and compared against language profiles to help identify the probable language of a text and detect statistical anomalies.
Frequency analysis is one of the oldest techniques in cryptanalysis. Simple substitution ciphers preserve the statistical structure of a language, meaning the most common ciphertext symbols usually correspond to the most common plaintext letters.
To analyze a ciphertext, compare the observed frequencies with the expected frequencies of the suspected language. High-frequency symbols, common bigrams, and common trigrams can provide valuable clues when reconstructing the original message.
For Caesar cipher, frequency peaks often reveal the shift directly. For Vigenère and other polyalphabetic ciphers, frequency analysis is commonly combined with the Index of Coincidence and the Kasiski examination to estimate key length before attempting decryption.
Every language has a unique statistical fingerprint. In English, just six letters account for nearly half of all written text — and this distribution stays remarkably stable across topics, authors, and time periods.
Cryptanalysts compare observed ciphertext frequencies against profiles like these to identify the probable language and map high-frequency symbols to likely plaintext letters. The classic mnemonic ETAOIN SHRDLU captures the twelve most common English letters in order — a shorthand every classical cryptanalyst knows by heart.