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GuardrailsAI/detect-jailbreak

published by @GuardrailsAI

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
4.9K
Last 30 days
327
Likes
7
Size
66.2 MB
Created on HF
2025-02-11
Age
1 years ago

Description

Content Warning:

This dataset contains unsafe model responses and user queries. Viewers may find the content disturbing.

Overview

Our evaluation dataset combines three existing datasets with custom augmentations to create a robust framework for assessing LLM vulnerabilities and defense effectiveness. The core components are the Verazuo dataset, the ZHX123 benchmark, and the Weapons of Mass Destruction Proxy (WMDP) dataset.

Credits and Citations

Our… See the full description on the dataset page: https://huggingface.co/datasets/GuardrailsAI/detect-jailbreak.

Tags

task_categories:text-classificationlanguage:enlicense:mitsize_categories:10K<n<100Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsarxiv:2402.13457arxiv:2403.03218arxiv:2307.15043region:usjailbreakingnot-for-all-audiences

README current version from Hugging Face


license: mit
task_categories:

  • text-classification
    language:
  • en
    tags:
  • jailbreaking
  • not-for-all-audiences
    size_categories:
  • 1K<n<10K

Content Warning:

This dataset contains unsafe model responses and user queries. Viewers may find the content disturbing.

Overview

Our evaluation dataset combines three existing datasets with custom augmentations to create a robust framework for assessing LLM vulnerabilities and defense effectiveness. The core components are the Verazuo dataset, the ZHX123 benchmark, and the Weapons of Mass Destruction Proxy (WMDP) dataset.

Credits and Citations

Our greatest thanks go out to the authors of the following publications, without whom this evaluation dataset would not be possible.

@inproceedings{SCBSZ24,
      author = {Xinyue Shen and Zeyuan Chen and Michael Backes and Yun Shen and Yang Zhang},
      title = {{``Do Anything Now'': Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models}},
      booktitle = {{ACM SIGSAC Conference on Computer and Communications Security (CCS)}},
      publisher = {ACM},
      year = {2024}
}

@citation{
  author = {Zihao Xu and Yi Liu and Gelei Deng and Yuekang Li and Stjepan Picek},
  title = {{A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models}},
  year = {2024},
  eprint = {2402.13457},
  archivePrefix = {arXiv},
}

@misc{li2024wmdp,
  title={The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning},
  author={Nathaniel Li and Alexander Pan and Anjali Gopal and Summer Yue and Daniel Berrios and Alice Gatti and Justin D. Li and Ann-Kathrin Dombrowski and Shashwat Goel and Long Phan and Gabriel Mukobi and Nathan Helm-Burger and Rassin Lababidi and Lennart Justen and Andrew B. Liu and Michael Chen and Isabelle Barrass and Oliver Zhang and Xiaoyuan Zhu and Rishub Tamirisa and Bhrugu Bharathi and Adam Khoja and Zhenqi Zhao and Ariel Herbert-Voss and Cort B. Breuer and Samuel Marks and Oam Patel and Andy Zou and Mantas Mazeika and Zifan Wang and Palash Oswal and Weiran Liu and Adam A. Hunt and Justin Tienken-Harder and Kevin Y. Shih and Kemper Talley and John Guan and Russell Kaplan and Ian Steneker and David Campbell and Brad Jokubaitis and Alex Levinson and Jean Wang and William Qian and Kallol Krishna Karmakar and Steven Basart and Stephen Fitz and Mindy Levine and Ponnurangam Kumaraguru and Uday Tupakula and Vijay Varadharajan and Yan Shoshitaishvili and Jimmy Ba and Kevin M. Esvelt and Alexandr Wang and Dan Hendrycks},
  year={2024},
  eprint={2403.03218},
  archivePrefix={arXiv},
  primaryClass={cs.LG}
}

@misc{zou2023universal,
    title={Universal and Transferable Adversarial Attacks on Aligned Language Models},
    author={Andy Zou and Zifan Wang and Nicholas Carlini and Milad Nasr and J. Zico Kolter and Matt Fredrikson},
    year={2023},
    eprint={2307.15043},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

README history 6 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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Used by abliterated models none yet

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Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

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Metadata

License
mit

Repository

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("GuardrailsAI/detect-jailbreak")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="GuardrailsAI/detect-jailbreak", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/GuardrailsAI/detect-jailbreak
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