Magika is an AI-powered file-type detector that uses a compact deep-learning model to classify binary and textual files with high accuracy and very low latency. The model is engineered to be only a few megabytes and to run quickly even on CPU-only systems, making it practical for desktop apps, servers, and security pipelines. Magika ships as a command-line tool and a library, providing drop-in detection that improves on traditional “magic number” and heuristic approaches, especially for ambiguous or short files. The project documentation highlights how the model is trained and optimized, and how its inference path enables millisecond-level classification. It also emphasizes reproducibility and developer ergonomics with clear install and usage instructions for common platforms. A public site complements the repo with background, examples, and guidance for integrating Magika into existing workflows.

Features

  • Tiny deep-learning model that runs in milliseconds on CPU
  • CLI and library APIs for easy integration
  • High accuracy on tricky or ambiguous file samples
  • Works across binary and textual content types
  • Reproducible installs with clear usage examples
  • Practical replacement for heuristic magic-based detectors

Project Samples

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License

Apache License V2.0

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Magika Web Site

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Artificial Intelligence Software

Registered

2025-10-09