> For the complete documentation index, see [llms.txt](https://yeasy.gitbook.io/ai_security_guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://yeasy.gitbook.io/ai_security_guide/di-yi-bu-fen-ji-chu-pian/03_frameworks.md).

# 第三章 安全框架与标准

随着 LLM 安全问题日益受到重视，业界已经形成了一系列安全框架和标准，为评估和防护 LLM 安全提供了系统化的指导。本章将介绍最具影响力的安全框架，帮助读者建立结构化的安全思维。

本章聚焦于 LLM 安全的框架与标准，主要内容包括：

* **3.1 OWASP 大语言模型十大风险解析**：深入解读业界广泛采用的 LLM 安全风险清单
* **3.2 NIST AI 风险管理框架**：了解美国国家标准技术研究院的 AI 风险管理方法
* **3.3 行业安全标准与最佳实践**：汇总各行业的 LLM 安全要求
* **3.4 MITRE ATLAS：AI 系统对抗战术与技术矩阵**：以攻击者视角组织 AI 攻击 TTP，与 OWASP、NIST 形成“风险—治理—对抗”三视角

通过本章的学习，读者将掌握评估 LLM 安全的系统方法，能够将这些框架应用于实际的安全实践中。

```mermaid
graph LR
    subgraph "LLM 安全框架体系"
    A["OWASP LLM Top 10"] --> D["安全评估"]
    B["NIST AI RMF"] --> D
    C["行业标准"] --> D
    G["MITRE ATLAS"] --> D
    D --> E["安全成熟度"]
    E --> F["持续改进"]
    end
```


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