As large language models (LLMs) revolutionize the AI landscape, it’s becoming crucial to understand and address the unique security challenges they present. In this comprehensive course from Pragmatic AI Labs, instructor Alfredo Deza covers the technical knowledge and skills required to identify, mitigate, and prevent security vulnerabilities in your LLM applications. Explore common security threats, such as model theft, prompt injection, and sensitive information disclosure, and learn practical techniques to prevent attackers from exploiting vulnerabilities and compromising your systems. Discover best practices for secure plug-in design, input validation, and sanitization, as well as how to actively monitor dependencies for security updates and vulnerabilities. Along the way, Alfredo outlines strategies for protecting AI systems against unauthorized access and data breaches. By the end of the course, you’ll be prepared to deploy robust, secure, and effective AI solutions.

Note: This course was created by Pragmatic AI Labs. We are pleased to host this training in our library.