language:

• en
  license: cc-by-4.0
  pretty_name: JailbreakDB
  task_categories:
• text-classification
  tags:
• llm-safety
• jailbreak
• prompts
• security
  configs:
• config_name: prompt_corpus
  default: true
  data_files:
  • split: jailbreak
    path: text_jailbreak_unique.csv
  • split: regular
    path: text_regular_unique.csv

JailbreakDB

JailbreakDB is a large-scale prompt corpus for LLM safety and prompt-security
research. It contains two deduplicated, text-only CSV files:

• text_jailbreak_unique.csv (~6.6M rows): jailbreak and adversarial prompts.
• text_regular_unique.csv (~5.7M rows): benign prompts.

Each row stores the prompt text and lightweight source metadata. The associated
PromptSecurity evaluation measurements are maintained as a separate Hugging Face
dataset: https://huggingface.co/datasets/youbin2014/PromptSecurity-Eval.

Related resources:

• Code: https://github.com/datasec-lab/PromptSecurity
• Leaderboard: https://datasec-lab.github.io/PromptSecurityLeaderboard/

Data Files

CSV Field Reference

The prompt-corpus CSV files use the following fields:

Loading

from datasets import load_dataset

corpus = load_dataset("youbin2014/JailbreakDB", "prompt_corpus")
print(corpus)

The CSV files can also be loaded directly:

from datasets import load_dataset

files = {
    "jailbreak": "hf://datasets/youbin2014/JailbreakDB/text_jailbreak_unique.csv",
    "regular": "hf://datasets/youbin2014/JailbreakDB/text_regular_unique.csv",
}
corpus = load_dataset("csv", data_files=files)
print(corpus)

Paper

If you use JailbreakDB, please cite the PromptSecurity paper:

@misc{hong2025sokpromptsecurity,
  title = {SoK: Taxonomy and Evaluation of Prompt Security in Large Language Models},
  author = {Hong, Hanbin and Wu, Shuang and Feng, Shuya and Naderloui, Nima and Yan, Shenao and Zhang, Jingyu and Arastehfard, Ali and Huang, Heqing and Hong, Yuan},
  year = {2025},
  eprint = {2510.15476},
  archivePrefix = {arXiv},
  primaryClass = {cs.CR},
  doi = {10.48550/arXiv.2510.15476},
  url = {https://arxiv.org/abs/2510.15476}
}

Safety Notice

This dataset may contain harmful, offensive, or disturbing prompts. It is
intended strictly for research on model safety, jailbreak robustness, defense
evaluation, and prompt-security analysis. Please review your institutional and
legal requirements before use.