ACSE-Eval

该数据集名为ACSE-Eval，包含了100个生产级别的AWS部署场景，每个场景都详细展示了架构规范、基础设施即代码实现、记录的安全漏洞以及相关的威胁建模参数。数据集涵盖了从简单到复杂不等的安全配置架构，跨越了12个不同的基础设施类别，并涉及146项独特的AWS服务。威胁模型中包含了来自多个框架的115种独特威胁。这100个部署场景涵盖了各种AWS服务与威胁模型，其目的是评估机器学习模型在云安全威胁建模方面的能力。

This dataset is named ACSE-Eval, which includes 100 production-grade AWS deployment scenarios. Each scenario elaborately displays architectural specifications, infrastructure-as-code (IaC) implementations, documented security vulnerabilities, and relevant threat modeling parameters. The dataset covers security configuration architectures ranging from simple to complex, spans 12 distinct infrastructure categories, and involves 146 unique AWS services. The threat models contain 115 unique threats sourced from multiple frameworks. These 100 deployment scenarios cover a diverse set of AWS services and threat models, and their purpose is to evaluate the capabilities of machine learning models in cloud security threat modeling.