Google’s Magika: Revolutionizing File-Type Identification for Enhanced Cybersecurity

In a continuous effort to fortify cybersecurity measures, Google has introduced Magika, an AI-powered file-type identification system designed to swiftly detect both binary and textual file formats. This innovative tool, equipped with a unique deep-learning model, marks a significant leap forward in file identification capabilities, contributing to the overall safety of Google users. 

Magika’s implementation is integral to Google’s internal processes, particularly in routing files through Gmail, Drive, and Safe Browsing to the appropriate security and content policy scanners. The tool’s ability to operate seamlessly on a CPU, with file identification occurring in a matter of milliseconds, sets it apart in terms of efficiency and responsiveness. 

Under the hood, Magika leverages a custom, highly optimized deep-learning model developed and trained using Keras, weighing in at a mere 1MB. During inference, Magika utilizes the Open Neural Network Exchange (ONNX) as an inference engine, ensuring rapid file identification, almost as fast as non-AI tools, even on the CPU.

Magika’s prowess was tested in a benchmark involving one million files encompassing over a hundred file types. 

The AI model, coupled with a robust training dataset, outperformed rival solutions by approximately 20% in performance. This heightened performance translated into enhanced detection quality, especially for textual files such as code and configuration fi

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