This talk will explore the critical aspects of securing GenAI applications, beginning with the unique security challenges they introduce. We will examine key vulnerabilities in depth, including manipulative prompt injection attacks, jailbreaks designed to bypass safety controls, risks related to sensitive data leakage, the generation of inaccurate hallucinations, and the dangers of improper model output handling. The agenda focuses on providing actionable insights through effective mitigation strategies, methods for early vulnerability identification, and adherence to proven best practices, ultimately aiming to equip attendees with the knowledge to build secure, resilient, and trustworthy LLM-powered systems while minimizing deployment risks.