Join us

ContentUpdates and recent posts about Magika..
 Activity
@mjh started using tool PostgreSQL , 1 day, 15 hours ago.
 Activity
@mjh started using tool Go , 1 day, 15 hours ago.
 Activity
@mjh started using tool GNU/Linux , 1 day, 15 hours ago.
 Activity
@mjh started using tool Docker , 1 day, 15 hours ago.
 Activity
@mjh started using tool Amazon Web Services , 1 day, 15 hours ago.
 Activity
@mjh started using tool Amazon S3 , 1 day, 15 hours ago.
 Activity
@mjh started using tool Amazon Elastic Block Store (EBS) , 1 day, 15 hours ago.
 Activity
@mjh started using tool Amazon EC2 , 1 day, 15 hours ago.
 Activity
@mjh started using tool Amazon ALB , 1 day, 15 hours ago.
Story FAUN.dev() Team
@eon01 shared a post, 1 day, 15 hours ago
Founder, FAUN.dev

Announcing FAUN.sensei() — Self-paced guides to grow fast — even when tech moves faster.

Docker GitLab CI/CD Helm Kubernetes GitHub Copilot

After months of hard work, FAUN.sensei() is finally alive!

FAUN.sensei()
Magika is an open-source file type identification engine developed by Google that uses machine learning instead of traditional signature-based heuristics. Unlike classic tools such as file, which rely on magic bytes and handcrafted rules, Magika analyzes file content holistically using a trained model to infer the true file type.

It is designed to be both highly accurate and extremely fast, capable of classifying files in milliseconds. Magika excels at detecting edge cases where file extensions are incorrect, intentionally spoofed, or absent altogether. This makes it particularly valuable for security scanning, malware analysis, digital forensics, and large-scale content ingestion pipelines.

Magika supports hundreds of file formats, including programming languages, configuration files, documents, archives, executables, media formats, and data files. It is available as a Python library, a CLI, and integrates cleanly into automated workflows. The project is maintained by Google and released under an open-source license, making it suitable for both enterprise and research use.

Magika is commonly used in scenarios such as:

- Secure file uploads and content validation
- Malware detection and sandboxing pipelines
- Code repository scanning
- Data lake ingestion and classification
- Digital forensics and incident response