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SafeStreet IP Analyzer

Welcome to the SafeStreet IP Analyzer - your go-to open-source tool for checking the safety and integrity of IP addresses. Our easy-to-use platform provides detailed insights into potentially malicious activities associated with IP addresses and helps in enhancing the cybersecurity posture of individuals and communities alike.

Screenshot 2024-04-22 at 00 32 57

Features

  • IP Information Retrieval: Get detailed information about an IP address, including its geolocation, ISP, and associated domain information.
  • Threat Intelligence: Determine if an IP address has been flagged for suspicious activities by integrating with threat intelligence databases.
  • Anomaly Detection: Utilize machine learning to score and identify unusual behavior or anomalies associated with an IP address.
  • User-Friendly Interface: Analyze IP addresses through a simple and intuitive web interface.
  • Real-Time Alerts: Receive instant notifications for any identified threats or unusual activities.
  • Community Contribution: As an open-source project, we welcome contributions to make the internet a safer place for everyone.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • flask: 1.1.2
  • requests: 2.25.1
  • scikit-learn: 0.24.1
  • waitress: 2.0.0
  • numpy: 1.20.1
  • pytest: 6.2.2
  • gunicorn: 20.0.4

Installing

  1. Clone the Repository

    git clone https://github.com/yourusername/SafeStreet-IP-Analyzer.git
    cd SafeStreet-IP-Analyzer
  2. Set Up a Virtual Environment (optional but recommended)

    python3 -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
  3. Install Required Packages

    pip3 install -r requirements.txt
  4. Environment Variables

    Set up the necessary environment variables. For security reasons, never hardcode sensitive information like API tokens within your application code.

    export IPINFO_API_TOKEN='your_ipinfo_api_token'
    export THREAT_INTELLIGENCE_API_TOKEN='your_threat_intelligence_api_token'
  5. Run the Application

    python3 app.py

Deployment

Netlify only serves static files and does not run the Flask server that powers this project. Deploying the repository directly to Netlify will therefore result in a 404 page. Use a platform that supports Python web services, such as Render or Heroku.

Deploying to Render

  1. Create an account at Render and click New > Web Service.

  2. Connect your GitHub repository and select the branch to deploy.

  3. For the build command enter:

    pip install -r requirements.txt
  4. Set the start command to:

    gunicorn app:app
  5. Add the environment variables IPINFO_API_TOKEN and THREAT_INTELLIGENCE_API_TOKEN in the service settings.

  6. Click Create Web Service to trigger the initial deployment. Render will build the container and provide a public URL where the Flask application runs.

How to Use

  1. Enter the IP Address: Simply type the IP address you wish to analyze into the input field.
  2. Analyze: Click the 'Analyze' button to retrieve information about the IP address.
  3. Review the Results: The analysis results will provide detailed information and a security assessment.

Contributing

We welcome contributions from the community. Whether it's improving the codebase, refining the user interface, or extending the feature set - your contributions are valuable to us.

  1. Fork the repository.
  2. Create your feature branch (git checkout -b feature/AmazingFeature).
  3. Commit your changes (git commit -am 'Add some AmazingFeature').
  4. Push to the branch (git push origin feature/AmazingFeature).
  5. Open a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgments

  • To all contributors and the community for their ideas and support.
  • Threat intelligence data provided by Threat Intelligence API.
  • Geolocation data by IPinfo.

Join us in our mission to make the digital streets safer!


Remember to replace placeholders like yourusername, your_ipinfo_api_token, your_threat_intelligence_api_token, and others with actual data. Also, make sure to include the actual links to the APIs or other services you're using. A LICENSE.md file should also be included if you're mentioning it in the README.

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