https://github.com/dogancanbakir/metamaska

μετάμάσκα - malevolent payload classifier
https://github.com/dogancanbakir/metamaska

command-injection cybersecurity hacktoberfest ml path-traversal python sql-injection vulnerability xss

Last synced: 3 months ago
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μετάμάσκα - malevolent payload classifier

• Host: GitHub
• URL: https://github.com/dogancanbakir/metamaska
• Owner: dogancanbakir
• License: mit
• Created: 2022-09-19T08:07:16.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-06-29T13:33:44.000Z (over 1 year ago)
• Last Synced: 2024-10-14T12:48:33.316Z (3 months ago)
• Topics: command-injection, cybersecurity, hacktoberfest, ml, path-traversal, python, sql-injection, vulnerability, xss
• Language: Jupyter Notebook
• Homepage:
• Size: 30.2 MB
• Stars: 22
• Watchers: 1
• Forks: 2
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        
#  μετάμάσκα - malevolent payload classifier

meta.mask can detect different types of malicious payloads like SQL injection, XSS, path-traversal, and command injection payloads.

[![pypi](https://img.shields.io/pypi/v/metamaska.svg)](https://pypi.org/project/metamaska/)

[![python](https://img.shields.io/pypi/pyversions/metamaska.svg)](https://pypi.org/project/metamaska/)

[![Build Status](https://github.com/dogancanbakir/metamaska/actions/workflows/dev.yml/badge.svg)](https://github.com/dogancanbakir/metamaska/actions/workflows/dev.yml)

[![codecov](https://codecov.io/gh/dogancanbakir/metamaska/branch/main/graphs/badge.svg)](https://codecov.io/github/dogancanbakir/metamaska)

* Documentation: 

* GitHub: 

* PyPI: 

* Free software: MIT

## TODO

* support more types

* support interoperable model formats, more at [here](https://scikit-learn.org/stable/model_persistence.html#interoperable-formats)

## Credits

- [Cookiecutter](https://github.com/audreyr/cookiecutter)

- [waynerv/cookiecutter-pypackage](https://github.com/waynerv/cookiecutter-pypackage)

- [ML-based-WAF](https://github.com/vladan-stojnic/ML-based-WAF)

- [WAF-A-MoLE](https://github.com/AvalZ/WAF-A-MoLE)