Security standards for LLM integrations are lagging behind as risks lie within the applications built around them

The text highlights the disparity in security attention between the integration of Large Language Models (LLMs) into applications and the LLMs themselves. While security research often focuses on social harms, biases, or the LLMs in isolation, less emphasis is placed on assessing the traditional security properties of confidentiality, integrity, and availability within the entire integrated application. NVIDIA, having implemented numerous LLM-powered applications, emphasizes the importance of understanding common and impactful attacks, effectively assessing LLM integrations from a security perspective, and designing secure integrations from the ground up

The discussion by Richard Harang, Principal Security Architect at NVIDIA, emphasizes the need to address security challenges across the entire LLM application ecosystem to mitigate non-transferable risks effectively. ```
https://www.youtube.com/watch?v=Rhpqiunpu0c