Tensor Trust

Tensor Trust offers an interactive game about testing AI security and model robustness.

github.com/HumanCompatibleAI/tensor-trust
Tensor Trust homepage screenshot

About Tensor Trust

Tensor Trust is the open source code for a prompt injection game that collects data for adversarial machine learning research. The repository contains the web game source code and a data cleaning pipeline, with references to use the data and play the game.

Running a local copy requires manual setup, including an OpenAI API key, Redis, Node.js, a Python 3.10 environment, and database migration. Academic publications that build on the code or data are asked to cite the associated 2023 paper using the included BibTeX entry.

Key features

  • Prompt injection attack game for collecting research data
  • Web game source code for local hosting
  • Data cleaning pipeline for collected game data
  • Django models with migration commands for database management
  • Admin login page for site administration
  • Tailwind workflow for updating stylesheet during development
Best for: Researchers and developers studying prompt injection and adversarial language model behavior.
Good for
  • Open source repository with game and data pipeline code
  • Provides data and game access for research use
  • Includes BibTeX citation for academic reuse
Watch out for
  • Local setup requires an OpenAI API key and additional software
  • Setup involves command-line steps and database migration

Tensor Trust at a glance

Type
Open-source project
Pricing
Not confirmed. Check the site
Platforms
Windows
Open source
Yes · Source code
Language
English
Last checked
Oct 6, 2026 · Online when checked
Listed
Oct 5, 2026

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Tensor Trust FAQ

What does this repository contain?
The source code for the Tensor Trust web game and data cleaning pipeline.
What is needed to run a local copy?
Set an OPENAI_API_KEY, install Redis and Node.js, set up a Python 3.10 environment, install dependencies, run database migration, and start the Django server.
How should academic publications credit the project?
Cite the 2023 Tensor Trust paper using the BibTeX entry included in the repository.
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