sensitive-data-detector 1.0.2

A package to detect sensitive information in code and files

Sensitive Data Detector 🔍

A Python package that helps detect sensitive information in files and code. Protect your codebase from accidental exposure of API keys, passwords, tokens, and other sensitive data.

🚀 Features

• 🔑 Detects API keys and tokens
• 📧 Identifies email addresses
• 🔐 Finds sensitive patterns in code
• ⚙️ Configurable detection patterns
• 📁 Works with any text-based file
• 🛡️ Pre-commit hook support

📦 Installation

pip install sensitive_data_detector

🎯 Quick Start

from sensitive_data_detector import has_sensitive_info

# Check a single file
result = has_sensitive_info("path/to/your/file.txt")
if result:
    True (sensitive info found in the file)
else:
    False (no sensitive info found)

🔍 What It Detects

The package detects various types of sensitive information, including:

• API Keys and Tokens
• Email Addresses
• Private Keys
• Access Tokens
• And more configurable patterns

🛠️ Development Setup

# Clone the repository
git clone https://github.com/akashdv25/sensitive_info_detector.git
cd sensitive_info_detector

# Create and activate virtual environment (optional)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run pre-commit hooks
pre-commit run --all-files

🔧 Configuration

The package uses a config.json file that defines patterns for sensitive information detection. You can customize these patterns for your specific needs.

Default patterns include:

{
    "patterns": {
        "api_key": "api[_-]?key['\"]?\\s*[:=]\\s*['\"]([\\w-]+)['\"]",
        "email": "[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}"
    }
}

🐍 Python Version Support

• Python 3.9
• Python 3.10
• Python 3.11

🛠️ Built With

• Python - Programming Language
• Black - Code Formatting
• isort - Import Sorting
• Flake8 - Code Linting
• pytest - Testing Framework
• pre-commit - Git Hooks Framework

🤝 Contributing

Contributions are welcome! Here's how you can help:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Run tests (pytest)
5. Commit your changes (git commit -m 'Add amazing feature')
6. Push to the branch (git push origin feature/amazing-feature)
7. Open a Pull Request

📝 License

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

📫 Contact

Akash Anandani

• Email

• Project Repo Link

• Official PyPI Page

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Made with ❤️ by Akash Anandani