https://github.com/google/magika
Fast and accurate AI powered file content types detection
https://github.com/google/magika
ai deep-learning filetype keras-classification-models keras-models mime-types onnx
Last synced: 2 days ago
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Fast and accurate AI powered file content types detection
- Host: GitHub
- URL: https://github.com/google/magika
- Owner: google
- License: apache-2.0
- Created: 2023-08-22T09:36:55.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2026-02-11T22:30:07.000Z (16 days ago)
- Last Synced: 2026-02-11T23:55:35.883Z (16 days ago)
- Topics: ai, deep-learning, filetype, keras-classification-models, keras-models, mime-types, onnx
- Language: Python
- Homepage: https://securityresearch.google/magika/
- Size: 81.7 MB
- Stars: 10,104
- Watchers: 41
- Forks: 490
- Open Issues: 123
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
- Codeowners: .github/CODEOWNERS
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README
# Magika
[](https://pypi.python.org/pypi/magika)
[](https://npmjs.com/package/magika)
[](https://pypi.python.org/pypi/magika)
[](https://pypi.python.org/pypi/magika)
[](https://pkg.go.dev/github.com/google/magika/go)
[](https://www.bestpractices.dev/en/projects/8706)
[](https://github.com/google/magika/actions)
[](https://pepy.tech/projects/magika)
[](https://pepy.tech/projects/magika)
Magika is a novel AI-powered file type detection tool that relies on the recent advance of deep learning to provide accurate detection. Under the hood, Magika employs a custom, highly optimized model that only weighs about a few MBs, and enables precise file identification within milliseconds, even when running on a single CPU. Magika has been trained and evaluated on a dataset of ~100M samples across 200+ content types (covering both binary and textual file formats), and it achieves an average ~99% accuracy on our test set.
Here is an example of what Magika command line output looks like:
Magika is used at scale to help improve Google users' safety by routing Gmail, Drive, and Safe Browsing files to the proper security and content policy scanners, processing hundreds billions samples on a weekly basis. Magika has also been integrated with [VirusTotal](https://www.virustotal.com/) ([example](./assets/magika-vt.png)) and [abuse.ch](https://bazaar.abuse.ch/) ([example](./assets/magika-abusech.png)).
For more context you can read our initial [announcement post on Google's OSS blog](https://opensource.googleblog.com/2024/02/magika-ai-powered-fast-and-efficient-file-type-identification.html), you can consult [Magika's website](https://securityresearch.google/magika/), and you can read more in our [research paper](https://securityresearch.google/magika/additional-resources/research-papers-and-citation/), published at the IEEE/ACM International Conference on Software Engineering (ICSE) 2025.
You can try Magika without installing anything by using our [web demo](https://securityresearch.google/magika/demo/magika-demo/), which runs locally in your browser!
# Highlights
- Available as a command line tool written in Rust, a Python API, and additional bindings for Rust, JavaScript/TypeScript (with an experimental npm package, which powers our [web demo](https://securityresearch.google/magika/demo/magika-demo/)), and GoLang (WIP).
- Trained and evaluated on a dataset of ~100M files across [200+ content types](./assets/models/standard_v3_3/README.md).
- On our test set, Magika achieves ~99% average precision and recall, outperforming existing approaches -- especially on textual content types.
- After the model is loaded (which is a one-off overhead), the inference time is about 5ms per file, even when run on a single CPU.
- You can invoke Magika with even thousands of files at the same time. You can also use `-r` for recursively scanning a directory.
- Near-constant inference time, independently from the file size; Magika only uses a limited subset of the file's content.
- Magika uses a per-content-type threshold system that determines whether to "trust" the prediction for the model, or whether to return a generic label, such as "Generic text document" or "Unknown binary data".
- The tolerance to errors can be controlled via different prediction modes, such as `high-confidence`, `medium-confidence`, and `best-guess`.
- The client and the bindings are already open source, and more is coming soon!
# Table of Contents
1. [Getting Started](#getting-started)
1. [Installation](#installation)
1. [Quick Start](#quick-start)
1. [Documentation](#documentation)
1. [Security Vulnerabilities](#security-vulnerabilities)
1. [License](#license)
1. [Disclaimer](#disclaimer)
# Getting Started
## Installation
### Command Line Tool
Magika ships a CLI written in Rust, and can be installed in several ways.
Via `magika` python package:
```shell
pipx install magika
```
Via brew (macOS / Linux)
```shell
brew install magika
```
Via installer script:
```shell
curl -LsSf https://securityresearch.google/magika/install.sh | sh
```
or
```shell
powershell -ExecutionPolicy Bypass -c "irm https://securityresearch.google/magika/install.ps1 | iex"
```
### Python package
```shell
pip install magika
```
### JavaScript package
```shell
npm install magika
```
## Quick Start
Here you can find a number of quick examples just to get you started.
To learn about Magika's inner workings, see the [Core Concepts](https://securityresearch.google/magika/core-concepts/) section of Magika's website.
### Command Line Tool Examples
```shell
% cd tests_data/basic && magika -r * | head
asm/code.asm: Assembly (code)
batch/simple.bat: DOS batch file (code)
c/code.c: C source (code)
css/code.css: CSS source (code)
csv/magika_test.csv: CSV document (code)
dockerfile/Dockerfile: Dockerfile (code)
docx/doc.docx: Microsoft Word 2007+ document (document)
docx/magika_test.docx: Microsoft Word 2007+ document (document)
eml/sample.eml: RFC 822 mail (text)
empty/empty_file: Empty file (inode)
```
```shell
% magika ./tests_data/basic/python/code.py --json
[
{
"path": "./tests_data/basic/python/code.py",
"result": {
"status": "ok",
"value": {
"dl": {
"description": "Python source",
"extensions": [
"py",
"pyi"
],
"group": "code",
"is_text": true,
"label": "python",
"mime_type": "text/x-python"
},
"output": {
"description": "Python source",
"extensions": [
"py",
"pyi"
],
"group": "code",
"is_text": true,
"label": "python",
"mime_type": "text/x-python"
},
"score": 0.996999979019165
}
}
}
]
```
```shell
% cat tests_data/basic/ini/doc.ini | magika -
-: INI configuration file (text)
```
```shell
% magika --help
Determines file content types using AI
Usage: magika [OPTIONS] [PATH]...
Arguments:
[PATH]...
List of paths to the files to analyze.
Use a dash (-) to read from standard input (can only be used once).
Options:
-r, --recursive
Identifies files within directories instead of identifying the directory itself
--no-dereference
Identifies symbolic links as is instead of identifying their content by following them
--colors
Prints with colors regardless of terminal support
--no-colors
Prints without colors regardless of terminal support
-s, --output-score
Prints the prediction score in addition to the content type
-i, --mime-type
Prints the MIME type instead of the content type description
-l, --label
Prints a simple label instead of the content type description
--json
Prints in JSON format
--jsonl
Prints in JSONL format
--format
Prints using a custom format (use --help for details).
The following placeholders are supported:
%p The file path
%l The unique label identifying the content type
%d The description of the content type
%g The group of the content type
%m The MIME type of the content type
%e Possible file extensions for the content type
%s The score of the content type for the file
%S The score of the content type for the file in percent
%b The model output if overruled (empty otherwise)
%% A literal %
-h, --help
Print help (see a summary with '-h')
-V, --version
Print version
```
For more examples and documentation about the CLI, see https://crates.io/crates/magika-cli.
### Python Examples
```python
>>> from magika import Magika
>>> m = Magika()
>>> res = m.identify_bytes(b'function log(msg) {console.log(msg);}')
>>> print(res.output.label)
javascript
```
```python
>>> from magika import Magika
>>> m = Magika()
>>> res = m.identify_path('./tests_data/basic/ini/doc.ini')
>>> print(res.output.label)
ini
```
```python
>>> from magika import Magika
>>> m = Magika()
>>> with open('./tests_data/basic/ini/doc.ini', 'rb') as f:
>>> res = m.identify_stream(f)
>>> print(res.output.label)
ini
```
For more examples and documentation about the Python module, see the [Python `Magika` module](https://securityresearch.google/magika/cli-and-bindings/python/) section.
# Documentation
Please consult [Magika's website](https://securityresearch.google/magika) for detailed documentation about:
- Core Concepts
- How Magika works
- Models & content types
- Prediction modes
- Understanding the output
- CLI & Bindings (Python module, JavaScript module, ...)
- Contributing
- FAQ
- ...
# Security Vulnerabilities
Please contact us directly at magika-dev@google.com.
# License
Apache 2.0; see [`LICENSE`](LICENSE) for details.
# Disclaimer
This project is not an official Google project. It is not supported by
Google and Google specifically disclaims all warranties as to its quality,
merchantability, or fitness for a particular purpose.