zer0-1s / Web-Attack-Detection

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WEB ATTACK DETECTION USING DEEP LEARNING

Overview

This project is capable of detecting web attacks based on HTTP packet patterns using NLP model

Features

  • The model uses multiple HTTP packet samples collected from the web server through the HTTP Debugger
  • The model analyzes each word in the packet and gives a suspicious rate based on a set threshold.
  • The model can make instant predictions so it can be integrated as WAF

Some examples of model recognition:

XSS
Cross-site scripting


XML External Entities Injection

About

License:MIT License


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Language:Jupyter Notebook 87.1%Language:Python 12.9%