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Text encoding type classifier

Project description

whatenc

PyPI License

Text encoding type classifier.

whatenc is a command-line tool that uses a gradient-boosted tree classifier to detect the encoding of a given string or file.

The model is trained on text samples from the English, Greek, Russian, Hebrew, and Arabic Wikipedia corpora, chosen to represent a diverse set of writing systems (Latin, Greek, Cyrillic, Hebrew, and Arabic scripts). Each line is encoded using multiple encoding schemes to generate labeled examples.

How It Works

whatenc applies a feature-based approach to characterize text, then feeds these features into a gradient-boosted decision tree model to classify the encoding.

Feature Extraction

Each input string is converted into a feature vector describing its statistical properties.

Features include:

Feature Description
Length (n) Number of characters in the input
n % 4 Useful for identifying base-N encodings
Printable Ratio Fraction of characters in string.printable
Alphabetic / Digit Ratios Ratio of letters and digits to total length
Padding Ratio (=) Common in Base64/32 encodings
Compressibility Ratio of compressed to raw byte length
Shannon Entropy Measure of randomness in character distribution
English Letter Correlation Correlation between letter frequencies and English letter frequency distribution
Stopword Ratio Fraction of English stopwords

Supported Encodings

whatenc currently recognizes the following formats and transformations:

Category Encodings
Base encodings base32, base64, base85, hex, url
Text ciphers morse
Compression gzip64
Hash digests md5, sha1, sha224, sha256, sha384, sha512

Installation

You can install whatenc using pipx:

pipx install whatenc

Usage

whatenc hello
whatenc samples.txt

Examples

[+] input: ZW5jb2RlIHRvIGJhc2U2NCBmb3JtYXQ=
   [~] top guess   = base64
      [=] base64   = 0.875
      [=] base32   = 0.101
      [=] gzip64   = 0.019

[+] input: hi
   [~] top guess   = plain
      [=] plain    = 0.772
      [=] base64   = 0.081
      [=] base32   = 0.075

[+] input: bfa99df33b137bc8fb5f5407d7e58da8
   [~] top guess   = md5
      [=] md5      = 1.000
      [=] sha1     = 0.000
      [=] url      = 0.000

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