ethz-spylab/agentdojo
A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents.
AgentDojo helps developers and security engineers test how well their LLM agents can resist prompt injection attacks and how effective their defenses are. It takes in various attack scenarios and defense strategies, and outputs a benchmark of the agent's resilience. This is for anyone building or securing applications powered by large language models.
471 stars. Available on PyPI.
Use this if you are developing LLM agents and need to systematically evaluate their security against adversarial prompts or compare different defense mechanisms.
Not ideal if you are an end-user looking for a pre-built solution to protect your LLM application, rather than a development and evaluation tool.
Stars
471
Forks
118
Language
Python
License
MIT
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Dependencies
14
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