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所在平台: Udemy |
课程主页: https://www.udemy.com/course/owasp-top-10-for-llm-applications-2025-edition/
课程评论：没有评论
课程名称：OWASP Top 10 for LLM Applications - 2025 Edition 概述：您是否致力于大规模语言模型（LLMs）或生成性人工智能系统，并希望确保它们的安全性、弹性和可信赖性？本课程专为开发人员、安全工程师、MLOps专业人员和人工智能产品经理设计，旨在提供识别、缓解和防止与LLM-powered系统相关的最关键安全风险的知识和工具。课程与最新的OWASP推荐保持一致，探讨的真实世界威胁远超传统应用安全，重点包括提示注入、不安全输出处理、模型服务拒绝、过度代理、过度依赖、模型盗用等问题。 在整个课程中，您将学习如何将安全设计原则应用于LLM应用，包括隔离用户输入、过滤和验证输出、保护第三方插件集成和保护专有模型知识产权的实用方法。我们将引导您创建全面的风险登记册和缓解计划，使用可下载模板，确保您的LLM解决方案符合行业最佳人工智能安全实践。您还将探索如何设计人机协作（HITL）工作流程、实施有效的监控和异常检测策略，并进行红队演练，模拟针对您的LLM系统的现实对手。 无论您是在开发客户支持聊天机器人、人工智能编码助手、医疗保健机器人，还是法律顾问系统，本课程将帮助您构建更安全、更负责任的人工智能产品。通过基于GenAssist AI这一虚构企业LLM平台的案例研究，您将看到如何在现实场景中端到端地应用OWASP原则。课程结束时，您将能够自信地记录和辩护您的LLM安全架构。 加入我们，掌握LLMs的OWASP Top 10，巩固您的生成性人工智能项目的安全基础！
Are you working with large language models (LLMs) or generative AI systems and want to ensure they are secure, resilient, and trustworthy? This OWASP Top 10 for LLM Applications - 2025 Edition course is designed to equip developers, security engineers, MLOps professionals, and AI product managers with the knowledge and tools to identify, mitigate, and prevent the most critical security risks associated with LLM-powered systems. Aligned with the latest OWASP recommendations, this course covers real-world threats that go far beyond conventional application security-focusing on issues like prompt injection, insecure output handling, model denial of service, excessive agency, overreliance, model theft, and more.Throughout this course, you'll learn how to apply secure design principles to LLM applications, including practical methods for isolating user input, filtering and validating outputs, securing third-party plugin integrations, and protecting proprietary model IP. We'll guide you through creating a comprehensive risk register and mitigation plan using downloadable templates, ensuring that your LLM solution aligns with industry best practices for AI security. You'll also explore how to design human-in-the-loop (HITL) workflows, implement effective monitoring and anomaly detection strategies, and conduct red teaming exercises that simulate real-world adversaries targeting your LLM systems.Whether you're developing customer support chatbots, AI coding assistants, healthcare bots, or legal advisory systems, this course will help you build safer, more accountable AI products. With a case study based on GenAssist AI-a fictional enterprise LLM platform-you'll see how to apply OWASP principles end-to-end in realistic scenarios. By the end of the course, you will be able to document and defend your LLM security architecture with confidence.Join us to master the OWASP Top 10 for LLMs and future-proof your generative AI projects!
