halencarjunior/cis_aws_foundation_benchmark_5_0

该数据集包含高质量的指令跟随数据，源自《互联网安全中心（CIS）亚马逊网络服务基础基准v5.0.0》（2025年3月31日发布）。它旨在微调大型语言模型（LLMs），使其能够充当云安全审计师和顾问。数据集涵盖了为AWS建立安全基线配置的规范性指导，重点关注身份和访问管理（IAM）、存储、日志记录、监控和网络。训练在该数据集上的模型将能够提供：安全控制的**基本原理**、验证合规性的**审计程序**（CLI和控制台）、修复安全配置错误的**补救步骤**，以及关于应用特定控制的操作风险的**影响评估**。

This dataset contains high-quality instruction-following data derived from the **Center for Internet Security (CIS) Amazon Web Services Foundations Benchmark v5.0.0** (released March 31, 2025). It is designed to fine-tune Large Language Models (LLMs) to act as Cloud Security Auditors and Consultants. The dataset covers prescriptive guidance for establishing a secure baseline configuration for AWS, focusing on Identity and Access Management (IAM), Storage, Logging, Monitoring, and Networking. The model trained on this dataset will be able to provide: * **Rationales** for security controls. * **Audit Procedures** (CLI and Console) to verify compliance. * **Remediation Steps** to fix security misconfigurations. * **Impact Assessments** regarding the operational risks of applying specific controls.