An awesome tool to search EAR and secure your website!
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EAR Scanner Tools is a set of security tools designed to detect Excessive Access Rights (EAR) vulnerabilities in web applications. It comprises a Chrome extension for real-time scanning of active web pages and a separate fuzz scanning tool that searches for and scans subdomains.
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Chrome Extension:
- Allows users to scan the currently active website in their browser for EAR vulnerabilities.
- If the current tab's URL is vulnerable to EAR, the extension will display the vulnerability details.
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Fuzz Scanner:
- Discovers subdomains for a given domain and scans each one for EAR vulnerabilities.
- Results will be displayed in the console and saved to a log file.
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Database Integration:
- Saves scan results to a database to prevent redundant scanning and speed up the process by using cached results within a 10-day window.
Here are major frameworks/libraries we used to build our project.
- Git clone and repo and navigate to the folder
git clone https://github.com/Kennnnn774/EAR-Detection-Tool.git
cd EAR-Detection-Tool
- OPTIONAL: To run locally, install the required Python packages. ONLY DO THIS if you are running this locally rather than with the hosted service- typically would just be for testing.
pip install -r requirements.txt
Additionally, create a .env file with a 'DB_API_KEY' and 'DB_URL_API_BASE' as keys, with an api key and base url from MongoDB Atlas. ONLY DO THIS if you are running this locally rather than with the hosted service- typically would just be for testing.
Finally, change the url in 'scripts/content.js' on line 4 to the localhost url. ONLY DO THIS if you are running it locally rather than with the hosted service- typically would just be for testing. To switch it back to the hosted service, remove the localhost URL and replace it with 'https://ear-extension-backend.onrender.com/scan'
- Load the Chrome extension into your browser
- Navigate to chrome://extensions/
- Enable Developer mode
- Click on Load unpacked and select the entire folder from the cloned repository.
- After cloning the repository, install the required Python packages
pip install -r requirements.txt
- navigate to the
fuzz_scan_tool
folder after following the previous two steps
cd fuzz_scan_tool
- Run the fuzz scanner tool:
python fuzz_scan.py
Contributions are what make the development community such 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 this repo and create a pull request.
Don't forget to give the project a star! ⭐ Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b
) - Commit your Changes (
git commit -m 'RandomMessage'
) - Push to the Branch (
git push origin
) - Open a Pull Request
- Emily Berger - @heyitsM - eberge11@jh.edu
- Aya Habbas - @ahabbs20 - ahabbas1@jh.edu
- Yujian (Ken) He - @Kennnnn774 - yhe99@jhu.edu
We are thankful for these resources which have helped us on our development journey: