Overview

Magika is a groundbreaking AI-powered tool engineered for rapid and highly accurate file content type detection. Leveraging advanced deep learning, Magika identifies file formats with exceptional precision in milliseconds, even on single-core CPUs. Its compact, optimized model, trained on a massive dataset of ~100 million files spanning over 200 content types, achieves an impressive ~99% accuracy. This robust performance makes Magika a critical component for security infrastructure, processing trillions of files weekly for Google's safety initiatives and integrated into platforms like VirusTotal.

Key Features

• AI-Powered Accuracy: Utilizes a sophisticated, custom deep learning model trained on extensive datasets for superior file type identification.
• Blazing Fast Performance: Delivers inference times of approximately 5ms per file after initial model load, with near-constant speed regardless of file size, as it only processes a select portion of file content.
• Broad Content Type Support: Capable of identifying over 200 distinct file types, encompassing both binary and textual formats.
• Lightweight & Efficient: Features a compact model (just a few MBs) that runs efficiently on standard hardware, including single CPUs.
• Flexible Bindings: Available as a command-line tool (Rust), a Python API, and experimental bindings for JavaScript/TypeScript (npm) and GoLang.
• Configurable Confidence: Offers adjustable prediction modes (high-confidence, medium-confidence, best-guess) and a per-content-type threshold system to manage prediction reliability.
• Scalable Operation: Designed to handle large volumes of files, with support for batch processing and recursive directory scanning.

Typical Use Cases

• Enhanced Security Scanning: Integral to systems that route files for security and content policy analysis, such as in email, cloud storage, and web browsing protection.
• Malware Analysis & Threat Detection: Powers platforms like VirusTotal for initial file triage and identification of potentially malicious content.
• Data Organization & Management: Automates the classification of diverse file types within large datasets for improved indexing and retrieval.
• Content Policy Enforcement: Assists in identifying and categorizing content to ensure compliance with various regulations and policies.
• Development & Integration: Provides developers with a fast and accurate method to programmatically identify file types within applications via its Python, JavaScript, or GoLang APIs.