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PCAP Analysis Tool

A streamlined Python application leveraging Streamlit for intuitive PCAP (Packet Capture) analysis. This tool is crucial for cybersecurity professionals and enthusiasts alike, enabling the analysis of network traffic to detect anomalies, investigate security incidents, and understand network behavior.\

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Table of Contents

Introduction

The PCAP Analysis Tool is designed to simplify the process of analyzing captured network traffic, making it accessible not only to seasoned cybersecurity experts but also to those new to the field. By harnessing the power of Python 3.10 and Streamlit, this tool provides a user-friendly interface for loading, viewing, and analyzing PCAP files. Whether you're investigating a security breach, conducting a network performance review, or learning about network protocols, our tool offers the insights you need through an intuitive graphical interface.

Features

  • Easy loading and parsing of PCAP files.
  • Interactive interface for filtering and inspecting packets.
  • Visualization of network traffic patterns and statistics.
  • Support for a wide range of network protocols.
  • Detailed packet analysis for in-depth investigation.

Getting Started

Follow these instructions to get a copy of the PCAP Analysis Tool running on your local machine for development, testing, or personal use.

Prerequisites

  • Python 3.10
  • PyCharm Professional (recommended for development)
  • Git (for cloning the repository)

Installation

  1. Clone the repository to your local machine:
git clone https://github.com/paresh2806/PCAP-Analyzer.git
  1. Navigate to the cloned repository directory:
cd PCAP-Analyzer
  1. Install the required Python packages:
pip install -r requirements.txt
  1. Run the app:
streamlit run .\app.py

Usage

To run the application, execute the following command in the terminal:

This command starts the Streamlit server and opens the application in your default web browser, where you can upload PCAP files and begin analysis.

Demo_App.2.mp4

Demo

Demo_App_view.mp4

Screenshots

HomePage

UploadFile

RawDataAndFiltering

GraphicalAnalysis

GeoPlots

Contributing

Your contributions are what make the open-source community an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Acknowledgments

  • Thanks to the Python and Streamlit communities for their invaluable resources and support.
  • Special thanks to the cybersecurity community for their insights and feedback on improving network analysis tools.