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Counterfit

A CLI that provides a generic automation layer for assessing the security of ML models.

Introduction

Counterfit

Counterfit is a command-line interface (CLI) tool designed to provide a generic automation layer for assessing the security of machine learning (ML) models. It integrates various existing adversarial frameworks into a single tool, allowing users to create their own assessments and tests.

Key Features:
  • Multi-Platform Support: Compatible with Microsoft Azure, Linux, and Windows (via WSL).
  • Adversarial Framework Integration: Combines multiple adversarial frameworks for comprehensive security assessments.
  • Custom Attack Creation: Users can create and run their own attacks on ML models.
  • Easy Installation: Simple setup process using Python virtual environments or Conda.
  • Extensive Documentation: Detailed guides for installation, usage, and contribution.
Benefits:
  • Enhanced Security: Helps identify vulnerabilities in ML models, improving their robustness against attacks.
  • Flexibility: Users can tailor the tool to their specific needs by creating custom attacks.
  • Community Support: Open-source project with contributions welcomed, fostering a collaborative environment for improvement.
Highlights:
  • Supports various data types including text, tabular, and image data.
  • Provides a range of pre-defined attacks for different target types.
  • Actively maintained with regular updates and community engagement.

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