dataset_info:
features:
- name: messages
list:
- name: role
dtype: string
- name: content
dtype: string
configs:
- config_name: default
data_files:- split: train
path: data/train.jsonl - split: validation
path: data/validation.jsonl
- split: train
Prompt Injection Analysis Dataset
Training data for fine-tuning an LLM to analyze prompt injection techniques,
jailbreak patterns, and LLM application defenses.
Source Distribution
- mosscap: 20,000 (41.6%)
- open_prompt_injection: 10,000 (20.8%)
- safeguard: 8,000 (16.6%)
- jailbreakhub: 5,000 (10.4%)
- jailbreak_classification: 3,063 (6.4%)
- deepset: 1,632 (3.4%)
- chatgpt_jailbreaks: 395 (0.8%)
Format
Each example is a 3-message chat conversation:
- system: LLM security researcher / red team operator persona
- user: Prompt injection analysis request, jailbreak technique question, or defense query
- assistant: Detailed analysis with technique identification, risk assessment, and defenses
Stats
- Train: 45,685 examples
- Validation: 2,405 examples