agentdojo
A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents.
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.7%) to scientific vocabulary
Keywords
Repository
A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents.
Basic Info
- Host: GitHub
- Owner: ethz-spylab
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://agentdojo.spylab.ai/
- Size: 47.7 MB
Statistics
- Stars: 254
- Watchers: 5
- Forks: 65
- Open Issues: 9
- Releases: 36
Topics
Metadata Files
README.md
Quickstart
bash
pip install agentdojo
[!IMPORTANT] Note that the API of the package is still under development and might change in the future.
If you want to use the prompt injection detector, you need to install the transformers extra:
bash
pip install "agentdojo[transformers]"
Running the benchmark
The benchmark can be run with the benchmark script. Documentation on how to use the script can be obtained with the --help flag.
For example, to run the workspace suite on the tasks 0 and 1, with gpt-4o-2024-05-13 as the LLM, the tool filter as a defense, and the attack with tool knowlege, run the following command:
bash
python -m agentdojo.scripts.benchmark -s workspace -ut user_task_0 \
-ut user_task_1 --model gpt-4o-2024-05-13 \
--defense tool_filter --attack tool_knowledge
To run the above, but on all suites and tasks, run the following:
bash
python -m agentdojo.scripts.benchmark --model gpt-4o-2024-05-13 \
--defense tool_filter --attack tool_knowledge
Inspect the results
To inspect the results, go to the dedicated results page of the documentation. AgentDojo results are also listed in the Invariant Benchmark Registry.Agent
Documentation of the Dojo
Take a look at our documentation.
Development set-up
Take a look at the development set-up docs.
Citing
If you use AgentDojo in your research, please consider citing our paper:
bibtex
@inproceedings{
debenedetti2024agentdojo,
title={AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for {LLM} Agents},
author={Edoardo Debenedetti and Jie Zhang and Mislav Balunovic and Luca Beurer-Kellner and Marc Fischer and Florian Tram{\`e}r},
booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2024},
url={https://openreview.net/forum?id=m1YYAQjO3w}
}
Owner
- Name: SPY Lab
- Login: ethz-spylab
- Kind: organization
- Location: Switzerland
- Website: https://spylab.ai
- Repositories: 1
- Profile: https://github.com/ethz-spylab
Secure and Private AI research at ETH Zürich
GitHub Events
Total
- Create event: 47
- Release event: 21
- Issues event: 33
- Watch event: 163
- Delete event: 5
- Member event: 1
- Issue comment event: 81
- Push event: 215
- Pull request review comment event: 40
- Pull request event: 113
- Pull request review event: 62
- Fork event: 44
Last Year
- Create event: 47
- Release event: 21
- Issues event: 33
- Watch event: 163
- Delete event: 5
- Member event: 1
- Issue comment event: 81
- Push event: 215
- Pull request review comment event: 40
- Pull request event: 113
- Pull request review event: 62
- Fork event: 44
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 18
- Total pull requests: 75
- Average time to close issues: 18 days
- Average time to close pull requests: 5 days
- Total issue authors: 13
- Total pull request authors: 13
- Average comments per issue: 1.78
- Average comments per pull request: 0.35
- Merged pull requests: 38
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 17
- Pull requests: 63
- Average time to close issues: 20 days
- Average time to close pull requests: 4 days
- Issue authors: 12
- Pull request authors: 12
- Average comments per issue: 1.82
- Average comments per pull request: 0.4
- Merged pull requests: 28
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- alexandrasouly-aisi (3)
- dedeswim (3)
- zggg1p (2)
- ianhhlee (1)
- stneng (1)
- MasihaVafa (1)
- juppytt (1)
- tongwu2020 (1)
- iliaishacked (1)
- javirandor (1)
- Mcilie (1)
- ZeynabSamei (1)
- EricWinsorDSIT (1)
Pull Request Authors
- dedeswim (39)
- maxwbuckley (9)
- cw00h (7)
- Danylo2006 (4)
- thavens (3)
- alexandrasouly-aisi (3)
- lbeurerkellner (3)
- cg563 (2)
- javirandor (1)
- MasihaVafa (1)
- pxuanbach (1)
- Mcilie (1)
- davhofer (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
-
Total downloads:
- pypi 2,486 last-month
-
Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 0
(may contain duplicates) - Total versions: 70
- Total maintainers: 1
proxy.golang.org: github.com/ethz-spylab/agentdojo
- Documentation: https://pkg.go.dev/github.com/ethz-spylab/agentdojo#section-documentation
- License: mit
-
Latest release: v0.1.34
published 9 months ago
Rankings
pypi.org: agentdojo
A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents
- Documentation: https://agentdojo.readthedocs.io/
- License: MIT License
-
Latest release: 0.1.34
published 9 months ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v4 composite
- eifinger/setup-rye v3 composite
- actions/checkout v4 composite
- eifinger/setup-rye v3 composite
- pypa/gh-action-pypi-publish 81e9d935c883d0b210363ab89cf05f3894778450 composite
- anthropic >=0.28.0
- click >=8.1.7
- cohere >=5.3.4
- deepdiff >=7.0.1
- docstring-parser >=0.15
- jsonref >=1.1.0
- langchain >=0.1.17
- openai >=1.0.0
- openapi-pydantic >=0.4.0
- pydantic [email]>=2.7.1
- pyyaml >=6.0.1
- rich >=13.7.1
- tenacity >=8.2.3
- typing-extensions >=4.11.0
- vertexai >=1.49.0
- 227 dependencies