English (United States) Adversarial prompts for LLM red teaming USE_LLM002 false LLM training LLM Safety / Red-teaming 1000 prompts 2024; 2025 csv English 2024; 2025 Adversarial prompts authored/tested against LLMs (red-teaming) Harm category and prompt-target labelling; harmful/harmless response labelling Static Appen Global Prompts employing a variety of red-teaming attack techniques tested against 4 leading LLMs (Deepseek, Claude 3.7, LLAMA and GPT 4o) and labelled according to whether they received a harmful or harmless response. Prompts are annotated for harm category, and prompt target where applicable. This dataset corresponds to the research paper Adversarial Prompting: Benchmarking Safety in Large Language Models (https://www.appen.com/ebooks/adversarial-prompting).