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On the recordRead 8 Oct 202622 facts
AgentDojo
On the record
- Affiliations
- The listed authors are affiliated with ETH Zurich and Invariant Labs.agentdojo.spylab.ai · read 8 Oct 2026
- API status
- The package API is still under development and may change.agentdojo.spylab.ai · read 8 Oct 2026
- Benchmark
- The benchmark script runs selected models, defenses, attacks, task suites, and tasks.agentdojo.spylab.ai · read 8 Oct 2026
- Contribute results
- Users can submit benchmark results by opening a repository pull request that includes a brief description and an implementation.agentdojo.spylab.ai · read 8 Oct 2026
- Custom attacks
- Users can create and plug in custom attacks that target a pipeline, task suite, user task, and injection task.agentdojo.spylab.ai · read 8 Oct 2026
- Custom benchmarks
- Users can define task suites and tasks to extend the provided benchmarks or create a new benchmark from scratch.agentdojo.spylab.ai · read 8 Oct 2026
- Custom pipelines
- Pipeline components can be combined into custom agent pipelines, including defense components.agentdojo.spylab.ai · read 8 Oct 2026
- Defense research
- The results page reports model, defense, and attack combinations and says it is not a leaderboard because not all combinations were tested.agentdojo.spylab.ai · read 8 Oct 2026
- Function runtime
- Its functions runtime defines and runs Python functions for use with function-calling LLMs, including functions that operate on stateful environments.agentdojo.spylab.ai · read 8 Oct 2026
- Install
- The quickstart installs AgentDojo with `pip install agentdojo`.agentdojo.spylab.ai · read 8 Oct 2026
- License
- The project's GitHub page identifies its license as MIT.github.com · read 8 Oct 2026
- Makers
- The project page lists authors affiliated with ETH Zurich and Invariant Labs.agentdojo.spylab.ai · read 8 Oct 2026
- Model integrations
- Documented tool calling LLM implementations include OpenAI GPT, Anthropic Claude, Google Gemini, Cohere Command, and a prompting interface for other models.agentdojo.spylab.ai · read 8 Oct 2026
- Model providers
- Documented tool-calling LLM implementations support OpenAI, Anthropic, Google, and Cohere; the docs also describe using Llama 3 70B through TogetherAI’s API.agentdojo.spylab.ai · read 8 Oct 2026
- Pipeline components
- Agent pipelines combine elements such as system messages, LLMs, tool execution, and defense components.agentdojo.spylab.ai · read 8 Oct 2026
- Prompt injection detector
- The prompt injection detector requires installing the `transformers` extra.agentdojo.spylab.ai · read 8 Oct 2026
- Purpose
- AgentDojo is a dynamic environment for evaluating prompt injection attacks and defenses for LLM agents.agentdojo.spylab.ai · read 8 Oct 2026
- Research use
- The project asks research users to consider citing its 2024 paper.agentdojo.spylab.ai · read 8 Oct 2026
