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**AD-TEAM** · 11 hours ago

845.7 MB | 00:16:04 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
001 Securing Generative AI Introduction (18.76 MB)
001 Learning objectives (8.44 MB)
002 1 1 Understanding the Significance of LLMs in the AI Landscape (48.75 MB)
003 1 2 Exploring the Resources for this Course - GitHub Repositories and Others (10.69 MB)
004 1 3 Introducing Retrieval Augmented Generation (RAG) (33.99 MB)
005 1 4 Understanding the OWASP Top-10 Risks for LLMs (20.87 MB)
006 1 5 Exploring the MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) Framework (25.81 MB)
001 Learning objectives (6.53 MB)
002 2 1 Defining Prompt Injection Attacks (66.05 MB)
003 2 2 Exploring Real-life Prompt Injection Attacks (17.2 MB)
004 2 3 Using ChatML for OpenAI API Calls to Indicate to the LLM the Source of Prompt Input (38.21 MB)
005 2 4 Enforcing Privilege Control on LLM Access to Backend Systems (15.89 MB)
006 2 5 Best Practices Around API Tokens for Plugins, Data Access, and Function-level Permissions (10.19 MB)
007 2 6 Understanding Insecure Output Handling Attacks (8.39 MB)
008 2 7 Using the OWASP ASVS to Protect Against Insecure Output Handling (19.99 MB)
001 Learning objectives (4.93 MB)
002 3 1 Understanding Training Data Poisoning Attacks (21.82 MB)
003 3 2 Exploring Model Denial of Service Attacks (9.88 MB)
004 3 3 Understanding the Risks of the AI and ML Supply Chain (36.21 MB)
005 3 4 Best Practices when Using Open-Source Models from Hugging Face and Other Sources (52.31 MB)
006 3 5 Securing Amazon BedRock, SageMaker, Microsoft Azure AI Services, and Other Environments (67.84 MB)
001 Learning objectives (6.51 MB)
002 4 1 Understanding Sensitive Information Disclosure (18.11 MB)
003 4 2 Exploiting Insecure Plugin Design (12.09 MB)
004 4 3 Avoiding Excessive Agency (14.82 MB)
001 Learning objectives (4.48 MB)
002 5 1 Understanding Overreliance (21.21 MB)
003 5 2 Exploring Model Theft Attacks (16.43 MB)
004 5 3 Understanding Red Teaming of AI Models (49.01 MB)
001 Learning objectives (6.76 MB)
002 6 1 Understanding the RAG, LangChain, Llama Index, and AI Orchestration (59.3 MB)
003 6 2 Securing Embedding Models (29.23 MB)
004 6 3 Securing Vector Databases (41.59 MB)
005 6 4 Monitoring and Incident Response (23.4 MB)]
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