datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.semantic-overlays-injection
Semantic Overlays — injection training corpus
The training corpus for the "do-not-execute" overlay of Semantic
Overlays: Mitigating Prompt Injection with Annotations Beyond Tokens
and Steering Vectors (arXiv:2608.23873),
released for both base models used in the paper.
paper
arXiv:2608.23873
code
semantic-overlays
trained adapters
semantic-overlays-adapters
interactive demo
semantic-overlays.vercel.app
The companion code tokenizes these files into… See the full description on the dataset page: https://huggingface.co/datasets/joshuapenman/semantic-overlays-injection.turkish-llm-injection
🇹🇷 AltaySec Turkish LLM Prompt Injection Dataset (v0.2)
Türkiye'nin ilk Türkçe-öncelikli, kategorize edilmiş LLM prompt injection veri seti — genişletilmiş sürüm.
📌 TL;DR
300 elle/üretim-destekli hazırlanmış Türkçe prompt injection payload'u, 12 saldırı kategorisi × 25, OWASP LLM Top 10 (2025) ile eşlenmiş. v0.1'in 120 çekirdek payload'una, AltayDuel arenasındaki bulgular ışığında üretilip düşmanca kalite/dedup denetiminden geçirilmiş 180 yeni payload eklendi.… See the full description on the dataset page: https://huggingface.co/datasets/AltaySec/turkish-llm-injection.moltbook-ai-injection-dataset
Moltbook AI-to-AI Injection Dataset
Researcher: David Keane (IR240474)
Institution: NCI — National College of Ireland
Programme: MSc Cybersecurity
Collected: February 2026
📖 Read the Full Journey
From RangerBot to CyberRanger V42 Gold — The Full Story
The complete story: dentist chatbot → Moltbook discovery → 4,209 real injections → V42-gold (100% block rate). Psychology, engineering, and 42 versions of persistence.
🔗 Links
Resource
URL
📦 This… See the full description on the dataset page: https://huggingface.co/datasets/DavidTKeane/moltbook-ai-injection-dataset.moltbook-extended-injection-dataset
Moltbook Extended Injection Dataset
Researcher: David Keane (IR240474)
Institution: NCI — National College of Ireland
Programme: MSc Cybersecurity
Collected: March 2026
Paper Reference: Greshake et al. (2023) — arXiv:2302.12173
📖 Read the Full Journey
From RangerBot to CyberRanger V42 Gold — The Full Story
The complete story: dentist chatbot → Moltbook discovery → 4,209 real injections → V42-gold (100% block rate). Psychology, engineering, and 42 versions of… See the full description on the dataset page: https://huggingface.co/datasets/DavidTKeane/moltbook-extended-injection-dataset.moltbook-ai-injection-dataset
Moltbook AI-to-AI Injection Dataset
Researcher: David Keane (IR240474)
Institution: NCI — National College of Ireland
Programme: MSc Cybersecurity
Collected: February 2026
📖 Read the Full Journey
From RangerBot to CyberRanger V42 Gold — The Full Story
The complete story: dentist chatbot → Moltbook discovery → 4,209 real injections → V42-gold (100% block rate). Psychology, engineering, and 42 versions of persistence.
🔗 Links
Resource
URL
📦 This… See the full description on the dataset page: https://huggingface.co/datasets/cyberec/moltbook-ai-injection-dataset.prompt-injection-defense-dpo-3k
Prompt Injection Defense DPO (3K)
DPO preference pairs training LLMs to detect and resist prompt injection attacks.
Motivation
As LLMs are deployed in agentic and production contexts, prompt injection — where malicious instructions are embedded in user input or retrieved documents — is a critical security threat. This dataset trains models to recognize and decline injection attempts while remaining helpful for legitimate queries.
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/prompt-injection-defense-dpo-3k.proximal-bug-injection-sft
Proximal Bug-Injection SFT
Supervised fine-tuning data for teaching a model to inject realistic, hard-to-find bugs into otherwise-correct code. The goal is to build coding RL environments where the introduced bugs resemble real human mistakes rather than trivial off-by-one or sign-flip errors.
The data is mined from real GitHub bug fixes: for each fix we take the after (correct) file as input and train the model to produce the before (buggy) version — i.e. the inverse of a… See the full description on the dataset page: https://huggingface.co/datasets/nreHieW/proximal-bug-injection-sft.dataset_with_prompt_injection
📦 Dataset Card
Dataset Summary
This dataset contains examples for training and evaluating language models.
The data is stored in JSONL format, where each line represents one training example.
Typical use cases include:
Instruction fine-tuning
Response generation
Conversational modelling
Question answering
Prompt injection research
🎯 Intended Uses
This dataset is intended for research and learning purposes:
Training LLMs
Experimenting with fine-tuning and… See the full description on the dataset page: https://huggingface.co/datasets/shehrozrafaqat/dataset_with_prompt_injection.akeel-thought-injection-20k
Akeel Thought Injection Dataset (20K)
Single-turn reasoning traces for training thought injection models
A QRK Labs Research Dataset
Overview
This dataset contains 20,000 single-turn examples of thought injection reasoning traces. Each example demonstrates a model:
Receiving a question
Reasoning about what it knows (in <think> tags)
Requesting external knowledge when needed (<knowledge> tags)
Integrating retrieved context… See the full description on the dataset page: https://huggingface.co/datasets/qrk-labs/akeel-thought-injection-20k.akeel-thought-injection-50k-augmented
Akeel Thought Injection Dataset (50K Augmented)
Multi-turn augmented reasoning traces for robust thought injection training
A QRK Labs Research Dataset
Overview
This dataset contains 50,000 augmented examples designed to prevent overfitting when training thought injection models. It expands the base 20K dataset through:
Shuffled originals (17,500) — Base samples randomly reordered
System prompt variations (17,500) — Same Q&A with different… See the full description on the dataset page: https://huggingface.co/datasets/qrk-labs/akeel-thought-injection-50k-augmented.