Dataset · Hugging Face

JailbreakV-28K/JailBreakV-28k

Name: JailBreakV-28k
Creator: JailbreakV-28K
License: mit
Keywords: task_categories:text-generation, task_categories:question-answering, license:mit, size_categories:10K<n<100K, format:csv, modality:image, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2404.03027, region:us

⛓‍💥 JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks 🌐 GitHub | 🛎 Project Page ｜ 👉 Download full datasets If you like our project, please give us a star ⭐ on Hugging Face for the latest update. 📰 News Date Event 2024/07/09 🎉 Our paper is accepted by COLM 2024. 2024/06/22 🛠️ We have updated our version to V0.2, which supports users to customize their attack… See the full description on the dataset page: https://huggingface.co/datasets/JailbreakV-28K/JailBreakV-28k.

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Author / organization	JailbreakV-28K
License (as declared)	mit
Downloads	3.4K (as reported by Hugging Face)
Likes	80
Created	30 March 2024
Last updated at source	10 July 2024

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Connected in the knowledge graph

codeintegrity-ai/promptguardModel · used to train
katanemo/Arch-GuardModel · used to train
Horizon-Labs/prompt-injection-guard-smallModel · used to train
Horizon-Labs/prompt-injection-guard-baseModel · used to train
Horizon-Labs/prompt-injection-guard-largeModel · used to train

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16 Oct 2026 Description: ⛓‍💥 JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks 🌐 GitHub | 🛎 Project Page ｜ 👉 Download full datasets If you like our project, please give us a star ⭐ on Hugging → ⛓‍💥 JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks 🌐 GitHub | 🛎 Project Page ｜ 👉 Download full datasets If you like our project, please give us a star ⭐ on Hugging

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Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.