Google

Magika is an open-source file type detection library and command-line tool created by Google's security research team. It leverages a custom deep learning model trained on millions of files to accurately identify over 100 content types, including documents, executables, code files, and media formats. Unlike traditional file detection methods that rely on simple magic numbers or file extensions, Magika analyzes the actual content of files to determine their true nature.

The tool is designed for security researchers, developers, and system administrators who need reliable file type identification for malware analysis, content filtering, forensic investigations, and automated processing pipelines. Magika can be integrated into security tools, web applications, and data processing workflows to prevent file type spoofing attacks and ensure proper handling of uploaded or scanned files.

Magika achieves state-of-the-art accuracy while maintaining fast inference speeds, making it suitable for both batch processing of large datasets and real-time analysis scenarios. Its lightweight model and efficient implementation allow it to run on various platforms without requiring GPU acceleration.

• Deep learning-based detection: Magika uses a custom neural network model trained on millions of files to identify content types with over 99% accuracy, significantly outperforming traditional file detection methods.

• Support for 100+ content types: The tool can identify a wide range of file formats including executables, documents, images, audio, video, code files, archives, and many others used in modern computing environments.

• Fast inference speed: Magika processes files in milliseconds on CPU, enabling high-throughput analysis for security scanning and content processing workflows without hardware acceleration requirements.

• Command-line interface and Python API: Users can run Magika directly from the terminal or integrate it into Python applications through a simple, well-documented programming interface.

• Cross-platform compatibility: The tool runs on Linux, macOS, and Windows systems, with pre-built binaries available and easy installation through package managers like pip.

• Open source with Apache 2.0 license: Magika's source code, training data, and model weights are freely available, allowing community contributions, custom modifications, and commercial use.

• Resilient against file extension spoofing: By analyzing file content rather than relying on extensions or metadata, Magika accurately detects files that have been renamed to hide their true type.

• Install Magika: Run pip install magika in your terminal to install the Python package, or download pre-built binaries from the GitHub releases page for standalone use.

• Run from command line: Execute magika filename to analyze a single file, or use magika path/to/directory to recursively scan all files in a folder with automatic batch processing.

• Use the Python API: Import the Magika class with from magika import Magika, create an instance with magika = Magika(), and call magika.identify_path("filename") to get detailed file type information programmatically.

• Interpret results: Review the output showing the detected content type, confidence score, and MIME type to make decisions about file handling, security scanning, or content routing in your workflow.

• Integrate into pipelines: Incorporate Magika calls into shell scripts, CI/CD pipelines, or application code to automatically classify files during upload, download, or storage operations.

• Superior accuracy: Magika's deep learning approach achieves higher detection rates and fewer false positives than traditional libmagic-based tools, especially for ambiguous or malformed files.

• Content-based identification: The tool examines actual file bytes rather than trusting easily manipulated extensions or headers, providing robust protection against type spoofing attacks.

• Production-ready performance: With sub-millisecond inference times and minimal memory footprint, Magika scales efficiently to handle millions of files in enterprise security and data processing environments.

• Google's security expertise: Developed by Google's security research team and battle-tested on large-scale internal systems, Magika benefits from extensive real-world validation and continuous improvement.

• Transparent and auditable: Full open-source availability including model architecture and training methodology enables security audits, custom retraining, and trust verification impossible with proprietary solutions.

• GitHub repository: Access source code, report issues, and submit contributions at https://github.com/google/magika with community discussion and Google's team monitoring.

• Documentation: Comprehensive usage guides, API reference, and integration examples are available on the official website at https://google.github.io/magika/ with searchable content.

• Security research blog: Google's security research publications provide context on Magika's development, performance benchmarks, and deployment experiences at large scale.

• Community discussions: Engage with other users and developers through GitHub discussions for questions, best practices, and integration advice from the growing user community.

• Python package: Install with pip install magika requiring Python 3.8+ on Linux, macOS, or Windows systems.

• Pre-built binaries: Download standalone executables from GitHub releases for systems without Python or where isolated deployment is preferred.

• Source code: Clone or download from https://github.com/google/magika for custom builds, modifications, or integration into larger projects.