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ARGUS: API Vulnerability Scanner

ARGUS is an API vulnerability scanner designed to identify security weaknesses in APIs by testing for the OWASP Top 10 vulnerabilities. It automates the process of finding common API flaws, ensuring robust security and providing detailed reports for remediation.

Features

  • OWASP Top 10 Coverage: Detect vulnerabilities like injection flaws, authentication issues, sensitive data exposure, and more.
  • Automated Testing: Perform scans with minimal setup.
  • Customizable Scanning: Specify target endpoints and customize scan configurations.
  • Detailed Reports: Generate comprehensive reports with findings and recommendations.
  • User-Friendly Interface: Simple to use for developers and security professionals.

Installation

To use ARGUS, follow these steps:

  1. Clone the repository:

    git clone https://github.com/Darry1968/argus.git
    cd argus
  2. Install dependencies:

    pip install -r requirements.txt
  3. Run the scanner:

    python argus.py

Usage

  1. Provide API Details: Input the API endpoint(s) you want to scan.
  2. Run Scans: Execute the scan to test for vulnerabilities.
  3. Review Reports: Analyze the generated report for detected issues and suggested fixes.

Requirements

  • Python 3.8+
  • Required Python libraries (installed via requirements.txt):
    • requests
    • flask
    • beautifulsoup4

Project Structure

argus/
├── argus.py            # Main scanner script
├── modules/            # Scanning modules
├── reports/            # Generated reports
├── requirements.txt    # Dependencies
├── README.md           # Project documentation

Contributing

Contributions are welcome! Follow these steps to contribute:

  1. Fork the repository.
  2. Create a new branch for your feature/bugfix.
    git checkout -b feature-name
  3. Commit your changes and push to your branch.
    git commit -m "Description of changes"
    git push origin feature-name
  4. Open a pull request.

Roadmap

  • Add support for more advanced scanning techniques.
  • Integrate machine learning for anomaly detection.
  • Develop a web-based dashboard for managing scans and reports.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For queries or suggestions, reach out to:


Contributions, feedback, and suggestions are always appreciated!

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