Offensive & Defensive AI: Exploiting and Securing LLMs, RAG, and Agentic Systems

Online, Available in English and Arabic

Topics:

• Building AI Systems (Understanding the Attack Surface)
• LLM architecture (practical view for security) 
• Prompt engineering and failure modes 
• RAG pipelines and data flow 
• Agentic AI systems (tools, memory, execution) 
• Attack surface mapping for AI systems 
• Lab 1: Build a basic LLM application
• Lab 2: Build a RAG pipeline with document retrieval
• Lab 3: Create a simple AI agent with tool access
• Prompt injection (direct and indirect) 
• Data exfiltration via LLMs 
• Retrieval poisoning (RAG attacks) 
• Tool abuse and privilege escalation in agents 
• Multi-agent risk scenarios 
• Lab 4: Exploit LLM using prompt injection
• Lab 5: Execute data leakage attack via RAG
• Lab 6: Abuse agent tools for unintended actions

Overview

Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic systems are rapidly being deployed across enterprises, often without adequate security controls. 

This hands-on training focuses on the emerging AI attack surface, teaching participants how to exploit and secure AI systems. Participants will build AI workflows, perform real-world attacks such as prompt injection and data exfiltration, and implement practical guardrails to mitigate these risks.

By the end of this course, the participant will be able to: 

• Build LLM-based applications and RAG pipelines
• Develop agentic AI systems with tool integration
• Identify and exploit vulnerabilities in AI systems
• Perform attacks such as prompt injection and data exfiltration
• Implement security guardrails to protect AI systems.