Hands-On Lab Workshop: LLM Security

In this event, you will gain the knowledge and tools to identify, mitigate, and prevent security risks, strengthening the reliability and security of your AI systems. WWT's Prompt Injection and Training Data Poisoning labs help users understand and defend against two major LLM security threats.  The Prompt Injection Lab demonstrates how attackers manipulate LLMs with deceptive inputs to extract sensitive data or execute unintended actions, while the Training Data Poisoning Lab explores how corrupting training or retrieval data can introduce biases , vulnerabilities, or backdoors.

This hands-on interactive session will explore using the labs is to introduce users to the risks of prompt injection and training data poisoning to Large Language Model (LLM) and Retrieval Augmented Generation (RAG) systems. Users will explore both direct and indirect prompt injection, as well as training data poisoning, through real-time queries and examples. 

The lab walks the user through accomplishing the following:

• Lab Architecture, key concepts, terms and technologies.

Goals and Objectives
WWT's Prompt Injection and Training Data Poisoning Labs help users understand and defend against two major LLM security threats:

Prompt Injection Lab:

Demonstrates how attackers manipulate LLMs with deceptive inputs to extract sensitive data or execute unintended actions.

Training Data Poisoning Lab:

Explores how corrupting training or retrieval data can introduce biases, vulnerabilities or backdoors.

By attending these labs, users will gain practical knowledge and skills to identify, mitigate and prevent these security threats, ensuring the safe and ethical use of LLMs.