AI Security Fundamentals: Risks, Frameworks & Tools

Modern AI applications introduce security challenges that traditional defenses cannot address. LLM based systems, retrieval pipelines, agents, data connectors, and vector databases expose new attack paths that organizations must understand and control. This course gives you a complete, practical, and engineering focused approach to securing GenAI systems across their entire lifecycle.

You will learn how attackers exploit AI models, how sensitive data leaks through prompts and outputs, how RAG pipelines can be manipulated, and how misconfigured tools or connectors expose entire environments. The course shows you how to design secure AI architectures, apply the right controls at the right layers, and build a repeatable security process for any AI powered system. What this course includesA detailed AI Security Reference Architecture for models, prompts, data, tools, and monitoringFull coverage of GenAI threats: injection attacks, data leakage, model misuse, unsafe toolsPractical guardrail design using AI firewalls, filtering, and permissioningAI SDLC guidance for dataset integrity, evaluations, red teaming, and version controlData governance for RAG systems: access control, filtering logic, encryption, secure embeddingsIdentity and authorization models for AI endpoints and tool integrationsAI Security Posture Management workflows for monitoring risk and driftObservability pipelines for logging prompts, responses, decisions, and quality metricsWhat you getArchitecture blueprintsThreat modeling templatesGovernance and policy frameworksSecurity checklists for AI SDLC and RAGEvaluation and firewall comparison matricesA full AI security control stackA clear 30, 60, 90 day adoption roadmapWhy this course is valuableIt is built for real engineering and real enterprise environmentsIt covers the full AI ecosystem instead of focusing on a single controlIt provides the exact artifacts professionals need to secure AI systemsIt prepares you for one of the most in demand skill sets in modern techIf you need a practical, structured, and comprehensive guide to securing LLM and RAG applications, this course gives you the tools, knowledge, and processes required to protect AI systems with confidence and to operate them safely at scale.