yaojialzc/JailFlowEval

--- pretty_name: JailFlowEval language: - en license: cc-by-4.0 size_categories: - n<1K task_categories: - text-generation tags: - datasets - benchmark - safety - red-teaming - jailbreak - agent-security - workflow-safety - enterprise-workflows configs: - config_name: default data_files: - split: train path: data/train.parquet --- # JailFlowEval This repository contains the dataset subset for our paper **"JailFlowEval: A Workflow-Safety Benchmark for LLM-Driven Enterprise Service Workflows"**. ## Dataset Summary - Rows: `744` - Unique source prompts: `373` - Split: `train` Task distribution: - `plan=336` - `exec=202` - `review=103` - `improve=103` ## Fields Each row contains: - `example_id`: unique row identifier in this packaged dataset - `source_id`: prompt ID from the source table - `quality_tier`: always `high_quality` - `task`: one of `plan`, `exec`, `review`, or `improve` - `source`: source dataset name - `cluster_label`: semantic cluster label - `forbidden_prompt`: original harmful or disallowed prompt - `jailbroken_prompt`: rewritten situational jailbreak prompt - `response`: target model response - `score`: PAIR-based harmfulness score ## Safety Notice This dataset contains harmful prompts and harmful or policy-violating model outputs. It is intended for safety evaluation, red teaming research, and defense analysis. It should not be used to facilitate real-world harm. ## Citation If you use this dataset, please cite this dataset release. The formal manuscript citation can be added after publication. ```bibtex @misc{liu2026jailfloweval_dataset, title = {JailFlowEval: A Workflow-Safety Benchmark for LLM-Driven Enterprise Service Workflows}, author = {Zhichao Liu and Haining Yu and Wenbo Pan and Wenting Zhang and Bingxuan Wang and Xiang Li}, year = {2026}, howpublished = {\url{https://huggingface.co/datasets/yaojialzc/JailFlowEval}}, note = {Dataset release} } ```