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api-security-tester

A machine learning based mobile app security testing framework

0.2.0
pipPyPI
Maintainers
1

API Security Tester

A machine learning-based framework for testing and assessing mobile application security vulnerabilities.

Features

  • Vulnerability detection using machine learning
  • Security risk assessment
  • Detailed security reports generation
  • Advanced metrics calculation (ROC-AUC, PR-AUC)
  • Support for multiple security features analysis

Installation

pip install api-security-tester

Quick Start

from api_security_tester import MobileAppSecurityFramework

# Initialize the framework
framework = MobileAppSecurityFramework()

# Example security features to analyze
app_features = {
    'storage_encryption_level': 0.8,
    'api_security_score': 0.7,
    'data_transmission_security': 0.9,
    'authentication_strength': 0.8,
    'input_validation_score': 0.7,
    'network_communication_security': 0.8,
    'third_party_library_risk': 0.2,
    'runtime_permissions_management': 0.7,
    'code_obfuscation_level': 0.6,
    'certificate_pinning_implementation': 0.8
}

# Detect vulnerabilities
results = framework.detect_vulnerabilities(app_features)

# Generate security report
report = framework.generate_security_report(results)
print(report)

Security Features

The framework analyzes the following security aspects:

  • Storage Encryption Level
  • API Security
  • Data Transmission Security
  • Authentication Strength
  • Input Validation
  • Network Communication Security
  • Third-party Library Risk
  • Runtime Permissions Management
  • Code Obfuscation
  • Certificate Pinning

Advanced Usage

Training Custom Models

# Generate and train with custom dataset
framework.generate_dataset(n_samples=1000)
framework.load_dataset('mobile_app_vulnerabilities.csv')
framework.build_ml_model()
framework.train_model()

# Save trained model
framework.save_model('custom_model.h5')

Calculating Advanced Metrics

# Get model performance metrics
metrics = framework.calculate_advanced_metrics()
print(f"ROC-AUC Score: {metrics['roc_auc']}")
print(f"PR-AUC Score: {metrics['pr_auc']}")

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Support

For support, please open an issue in the GitHub repository or contact contact@ashinno.com

FAQs

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