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  3. Tensor Trust
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Tensor Trust

A prompt injection game to collect data for robust ML research.

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Introduction

Tensor Trust

Tensor Trust is a web-based tool designed to explore prompt injection attacks while collecting valuable data to enhance the robustness of machine learning models. It involves a game format that allows researchers and developers to engage in interactive scenarios, providing insights into adversarial machine learning challenges.

Key Features:
  • Interactive Gameplay: Engage with a unique prompt injection game that simulates real-world scenarios.
  • Data Collection: Compile data crucial for understanding and improving the resilience of ML models against adversarial attacks.
  • Django Framework: Built using Django, which ensures a robust and scalable development environment.
  • Deployment: Easily deployable on Google Cloud Platform, leveraging various GCP services for better performance.
Benefits:
  • Robustness Research: A valuable resource for researchers focusing on the security and robustness of machine learning applications.
  • Collaborative Environment: Opens avenues for collaboration within the AI research community.
  • Hands-on Learning: Provides a space for users to learn about prompt injection in an engaging manner.
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Information

  • Publisher
    AISecKit
  • Websitegithub.com
  • Published date2025/04/27

Categories

  • Input Validation & Filtering
  • AI Research Papers
  • Adversarial Example Detection

Tags

  • Prompt Injection
  • Model Robustness

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