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Securing Generative AI

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  • 文件大小:846MB
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文件列表

  1. Lesson 3 Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities/006. 3.5 Securing Amazon BedRock, SageMaker, Microsoft Azure AI Services, and Other Environments.mp4 68MB
  2. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/002. 2.1 Defining Prompt Injection Attacks.mp4 66MB
  3. Lesson 6 Protecting Retrieval Augmented Generation (RAG) Implementations/002. 6.1 Understanding the RAG, LangChain, Llama Index, and AI Orchestration.mp4 59MB
  4. Lesson 3 Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities/005. 3.4 Best Practices when Using Open-Source Models from Hugging Face and Other Sources.mp4 52MB
  5. Lesson 5 Overreliance, Model Theft, and Red Teaming AI Models/004. 5.3 Understanding Red Teaming of AI Models.mp4 49MB
  6. Lesson 1 Introduction to AI Threats and LLM Security/002. 1.1 Understanding the Significance of LLMs in the AI Landscape.mp4 49MB
  7. Lesson 6 Protecting Retrieval Augmented Generation (RAG) Implementations/004. 6.3 Securing Vector Databases.mp4 42MB
  8. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/004. 2.3 Using ChatML for OpenAI API Calls to Indicate to the LLM the Source of Prompt Input.mp4 38MB
  9. Lesson 3 Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities/004. 3.3 Understanding the Risks of the AI and ML Supply Chain.mp4 36MB
  10. Lesson 1 Introduction to AI Threats and LLM Security/004. 1.3 Introducing Retrieval Augmented Generation (RAG).mp4 34MB
  11. Lesson 6 Protecting Retrieval Augmented Generation (RAG) Implementations/003. 6.2 Securing Embedding Models.mp4 29MB
  12. Lesson 1 Introduction to AI Threats and LLM Security/006. 1.5 Exploring the MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) Framework.mp4 26MB
  13. Lesson 6 Protecting Retrieval Augmented Generation (RAG) Implementations/005. 6.4 Monitoring and Incident Response.mp4 23MB
  14. Lesson 3 Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities/002. 3.1 Understanding Training Data Poisoning Attacks.mp4 22MB
  15. Lesson 5 Overreliance, Model Theft, and Red Teaming AI Models/002. 5.1 Understanding Overreliance.mp4 21MB
  16. Lesson 1 Introduction to AI Threats and LLM Security/005. 1.4 Understanding the OWASP Top-10 Risks for LLMs.mp4 21MB
  17. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/008. 2.7 Using the OWASP ASVS to Protect Against Insecure Output Handling.mp4 20MB
  18. Introduction/001. Securing Generative AI Introduction.mp4 19MB
  19. Lesson 4 Sensitive Information Disclosure, Insecure Plugin Design, and Excessive Agency/002. 4.1 Understanding Sensitive Information Disclosure.mp4 18MB
  20. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/003. 2.2 Exploring Real-life Prompt Injection Attacks.mp4 17MB
  21. Lesson 5 Overreliance, Model Theft, and Red Teaming AI Models/003. 5.2 Exploring Model Theft Attacks.mp4 16MB
  22. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/005. 2.4 Enforcing Privilege Control on LLM Access to Backend Systems.mp4 16MB
  23. Lesson 4 Sensitive Information Disclosure, Insecure Plugin Design, and Excessive Agency/004. 4.3 Avoiding Excessive Agency.mp4 15MB
  24. Lesson 4 Sensitive Information Disclosure, Insecure Plugin Design, and Excessive Agency/003. 4.2 Exploiting Insecure Plugin Design.mp4 12MB
  25. Lesson 1 Introduction to AI Threats and LLM Security/003. 1.2 Exploring the Resources for this Course - GitHub Repositories and Others.mp4 11MB
  26. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/006. 2.5 Best Practices Around API Tokens for Plugins, Data Access, and Function-level Permissions.mp4 10MB
  27. Lesson 3 Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities/003. 3.2 Exploring Model Denial of Service Attacks.mp4 10MB
  28. Lesson 1 Introduction to AI Threats and LLM Security/001. Learning objectives.mp4 8MB
  29. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/007. 2.6 Understanding Insecure Output Handling Attacks.mp4 8MB
  30. Lesson 6 Protecting Retrieval Augmented Generation (RAG) Implementations/001. Learning objectives.mp4 7MB
  31. Lesson 2 Understanding Prompt Injection & Insecure Output Handling/001. Learning objectives.mp4 7MB
  32. Lesson 4 Sensitive Information Disclosure, Insecure Plugin Design, and Excessive Agency/001. Learning objectives.mp4 7MB
  33. Lesson 3 Training Data Poisoning, Model Denial of Service & Supply Chain Vulnerabilities/001. Learning objectives.mp4 5MB
  34. Lesson 5 Overreliance, Model Theft, and Red Teaming AI Models/001. Learning objectives.mp4 4MB