In this session, the speaker aims to shed light on exploiting Large Language Models (LLMs) through adversarial attacks. The speaker will cover the common LLM use cases, highlight emerging threats, and delve into LLM adversarial attacks with practical examples to illustrate their impact. The presentation will introduce the concept of LLM red teaming, emphasizing its critical role in evaluating and enhancing LLM security for AI trustworthiness. Ultimately, this speech seeks to elevate the audience's understanding and encourage proactive strategies to safeguard against these adversarial threats.