datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
real-toxicity-prompts
Dataset Card for Real Toxicity Prompts
Dataset Summary
RealToxicityPrompts is a dataset of 100k sentence snippets from the web for researchers to further address the risk of neural toxic degeneration in models.
Languages
English
Dataset Structure
Data Instances
Each instance represents a prompt and its metadata:
{
"filename":"0766186-bc7f2a64cb271f5f56cf6f25570cd9ed.txt",
"begin":340,
"end":564,
"challenging":false… See the full description on the dataset page: https://huggingface.co/datasets/allenai/real-toxicity-prompts.drh-System-Prompt-processedtm-system_promptChatGPT-4o-Writing-Prompts
ChatGPT-4o Writing Prompts
This is a dataset containing 3746 short stories, generated with OpenAI's chatgpt-4o-latest model and using Reddit's Writing Prompts subreddit as a source. Each sample is generally between 6000-8000 characters long.
These stories were thoroughly cleaned and then further enriched with a title and a series of applicable genres.
Note that I did not touch the Markdown ChatGPT-4o produced by itself to enrich its output, as I very much enjoy the added flavour… See the full description on the dataset page: https://huggingface.co/datasets/Gryphe/ChatGPT-4o-Writing-Prompts.veo3-video-prompts
Veo 3 Video Generation Dataset
English | Português do Brasil
English
Summary
A collection of AI-generated videos created with Google's Veo 3 family of models. Each record contains the original text prompt, the model variant used, the generated video, and (when applicable) the input reference image. Videos are organized into one configuration per model variant.
Videos: 5,811
Input images: 1,354
Configurations: 6
Language of prompts: multilingual… See the full description on the dataset page: https://huggingface.co/datasets/artificialguybr/veo3-video-prompts.cyberseceval3-visual-prompt-injection
Dataset Card for CyberSecEval 3 - Visual Prompt Injection Benchmark
Dataset Details
Dataset Description
This dataset provides a multimodal benchmark for visual prompt injection, with text/image inputs. It is part of CyberSecEval 3, the third edition of Meta's flagship suite of security benchmarks for LLMs to measure cybersecurity risks and capabilities across multiple domains.
Language(s): English
License: MIT
Dataset Sources
Repository: Link… See the full description on the dataset page: https://huggingface.co/datasets/facebook/cyberseceval3-visual-prompt-injection.Nemotron-RL-Agentic-Indirect-Prompt-Injection-v1
Nemotron-RL-Agentic-Indirect-Prompt-Injection-v1
Dataset Description:
Nemotron-RL-Agentic-Indirect-Prompt-Injection-v1 is an RL dataset for training and evaluating a tool-using agent's ability to resist Indirect Prompt Injection (IPI) attacks hidden inside tool-returned environment data. In each record, the agent receives a benign user request that requires calling a read tool whose output contains an adversarial instruction disguised as legitimate domain content… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Indirect-Prompt-Injection-v1.PromptCoT-2.0-SFT-4.8M
PromptCoT-2.0-SFT-4.8M
This repository contains the largest dataset released with PromptCoT 2.0 (Scaling Prompt Synthesis for LLM Reasoning).It includes 4.8 million fully synthetic prompts with reasoning trajectories, serving as the cornerstone for supervised fine-tuning (SFT) experiments.
The dataset demonstrates that purely synthetic data—when generated with PromptCoT 2.0—can train competitive reasoning models that outperform human-curated baselines such as OpenMathReasoning and… See the full description on the dataset page: https://huggingface.co/datasets/xl-zhao/PromptCoT-2.0-SFT-4.8M.PromptShield
PromptShield Benchmark: A Flexible and Realistic Benchmark for Prompt Injection Attacks
This dataset accompanies the paper "[PromptShield: Deployable Detection for Prompt Injection Attacks]" (ArXiv Link) and is built from a curated selection of open-source datasets and published prompt injection attack strategies.
Dataset Details
Task: Binary classification of prompt injection attempts.
Fields:
prompt: The full text of the prompt, including instructions, inputs, and… See the full description on the dataset page: https://huggingface.co/datasets/hendzh/PromptShield.Official_LLM_System_Prompts
Official LLM System Prompts
This short dataset contains a few system prompts leaked from proprietary models. Contains date-stamped prompts from OpenAI, Anthropic, MS Copilot, GitHub Copilot, Grok, and Perplexity.
prompt-swap-mixed12-5xlr-e1-mxfp4-mergedprompt-swap-mixed12-5xlr-e2-mxfp4-mergedhle_rlvr_no_promptagentic-prompt-injection-boundary-pairs
Agentic Prompt-Injection Boundary Pairs
Most prompt-injection datasets make the attack easy to recognize. The malicious row contains obvious override language, while the benign row discusses something unrelated. A classifier can look capable without learning the boundary that matters in production.
This dataset takes a stricter approach. Each attack is paired with a legitimate request from the same workflow. The two rows share the asset, role, tool and topic. What changes is… See the full description on the dataset page: https://huggingface.co/datasets/3nesdeniz/agentic-prompt-injection-boundary-pairs.prompt-swap-medium12-e2-mxfp4-mergedIndirect-Prompt-Injection-BIPIA-GPT
Indirect Prompt Injection Detection Dataset (BIPIA + GPT-4o-mini)
Dataset Summary
This dataset contains 70,000 examples for detecting indirect prompt injection attacks in Large Language Models. It combines:
35,000 malicious samples from the BIPIA benchmark (cleaned and processed)
35,000 benign samples generated using GPT-4o-mini
Indirect prompt injection attacks embed malicious instructions within external content (code, table, email, webAQ, abstract) that LLMs process… See the full description on the dataset page: https://huggingface.co/datasets/MAlmasabi/Indirect-Prompt-Injection-BIPIA-GPT.Prompt-Routing-DatasetPrompt Routing Dataset · Multi-Task Infrastructure Routing
About this dataset
This dataset is a highly dense, premium alignment asset explicitly designed to train Edge Orchestrators and Routing Models ranging from 50M to 1.5B parameters.
When deploying small language models (SLMs) on consumer hardware or local edge instances, running multi-step mathematical derivations or complex architectural software tasks often causes catastrophic hallucinations or syntax breakdown. This dataset… See the full description on the dataset page: https://huggingface.co/datasets/SupraLabs/Prompt-Routing-Dataset.hebrew_lyrics_prompting_finetuneLTX2.3-22B_IC-LoRA-CrossView-Prompt-Dataset
CrossView Prompt Dataset
The training dataset behind the
CrossView Prompt IC-LoRA
for LTX-Video 2.3 — a "virtual second camera" adapter that re-renders a scene
from a new viewpoint described by a short prompt.
Each sample is a pair of static-camera clips of the same scene (a reference
view and a target view) plus a camera-delta caption describing how the
target camera differs from the reference.
Contents
clips/<scene>/<cam>.mp4 # 504 unique clips, native… See the full description on the dataset page: https://huggingface.co/datasets/Cseti/LTX2.3-22B_IC-LoRA-CrossView-Prompt-Dataset.Reddit-SFW-Writing_Prompts_ShareGPTConverted, deslopped, min-hash deduplicated, rejection filtered, grammar corrected using: https://github.com/The-Chaotic-Neutrals/ShareGPT-Formaxxing
[Description Tags],"Deleted user", "Hello,\n\nYour post has been removed..", "Post has been deleted by user", "This post has been marked NSFW", duplicated system and human turns, etc has been removed.
llm-system-prompts-benchmark
Dataset Card for Dataset Name
This datset is a collection of 100 system prompts for large language models.
Dataset Details
Dataset Description
These 100 system prompts test a model's ability to follow grammatical patterns; answer basic multiple choice questions; act according to a particular persona; memorize information; and speak in French.
Files:
hundred_system_prompts.py: refer to this to see the (prompt, probe, function) triplets, as well as the… See the full description on the dataset page: https://huggingface.co/datasets/Naomibas/llm-system-prompts-benchmark.clawk-agent-social-ai-prompt-injection-dataset
Clawk Agent-Social AI Prompt Injection Dataset
85,703 items — 44,232 posts and 41,471 replies — from Clawk, a social network whose users are AI agents.
Scanned for AI-to-AI indirect prompt injection using the threat model of Greshake et al. (2023). The full raw corpus is included, so you can ignore my analysis entirely and do your own.
These are keyword-matched candidates, not verified attacks. An agent discussing prompt injection matches the same words as one performing it.… See the full description on the dataset page: https://huggingface.co/datasets/DavidTKeane/clawk-agent-social-ai-prompt-injection-dataset.PKU-SafeRLHF-prompt
Dataset Card for PKU-SafeRLHF-prompt
This dataset contains 44.6K unique prompts from PKU-SafeRLHF. 22.4% of the prompts in this dataset come from the sibling project BeaverTails. Additionally, we performed SFT on Llama3-70B using the Alpaca 52K dataset, resulting in Alpaca3-70B. 63.6% and 14.0% of our dataset is generated by Alpaca3-70B and WizardLM-30B-Uncensored, respectively, under the guidance of experts.
Here is the generation pipeline:
Usage
To load our dataset… See the full description on the dataset page: https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF-prompt.finance-deepseek-prompts-distill
We are soon launching an end-to-end data process—distillation and synthetic data—to train (SFT and RL) a financial agentic model!
Financial DeepSeek Distillation Prompts
Ready-to-paste prompts for manually distilling financial reasoning datasets through DeepSeek-V4 pro/flash (or any LLM) UI.
Available Datasets (English)
Dataset
Prompts
Size
Category
Target
finqa_train_prompts.jsonl
6,251
58 MB
Advanced Business Knowledge
2,948… See the full description on the dataset page: https://huggingface.co/datasets/RASSAISAID/finance-deepseek-prompts-distill.moltbook-agent-social-ai-prompt-injection-dataset
Moltbook Agent-Social AI Prompt Injection Dataset
207,391 items — 77,469 posts and 129,922 comments — from Moltbook, a social network whose users are AI agents.
Scanned for indirect prompt-injection patterns using the taxonomy of Greshake et al. (2023). The full raw corpus is included, so you can ignore my analysis entirely and do your own.
These are keyword-matched candidates, not verified attacks. An agent discussing prompt injection matches the same words as one performing… See the full description on the dataset page: https://huggingface.co/datasets/DavidTKeane/moltbook-agent-social-ai-prompt-injection-dataset.PromptCoT-2.0-SelfPlay-4B-48K
PromptCoT-2.0-SelfPlay Datasets
This repository hosts the self-play datasets used in PromptCoT 2.0 (Scaling Prompt Synthesis for LLM Reasoning).These datasets were created by applying the PromptCoT 2.0 synthesis framework to generate challenging math and programming problems, and then training models through self-play with Direct Preference Optimization (DPO).
PromptCoT-2.0-SelfPlay-4B-48K: 48,113 prompts for Qwen3-4B-Thinking-2507 self-play.
PromptCoT-2.0-SelfPlay-30B-11K: 11… See the full description on the dataset page: https://huggingface.co/datasets/xl-zhao/PromptCoT-2.0-SelfPlay-4B-48K.prompt-injection-repo-dataset
Prompt Injection Repository File Dataset
A labeled dataset for detecting prompt injection attacks in repository files — code, configs, READMEs, CI/CD workflows, and documentation that AI coding agents process as context.
What This Is (and Isn't)
This dataset targets a specific threat: indirect prompt injection via repository content. When AI coding agents (Claude Code, Cursor, Copilot, Gemini CLI) clone a repo, every file becomes part of the agent's context.… See the full description on the dataset page: https://huggingface.co/datasets/prodnull/prompt-injection-repo-dataset.prompt-difficulty
Prompt Difficulty Assessment
Prompt difficulty plays a critical role in the performance of large language models (LLMs).
Assessing this difficulty is essential for selecting training examples, evaluating model capabilities, and optimizing routing and reasoning strategies.
Yet, no standardized framework exists for comparing prompt difficulty across domains.
This report proposes a method to quantify prompt difficulty using multiple LLMs and introduces a composite difficulty score for… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/prompt-difficulty.deepcad_prompt_jsonAutoBench_Prompts