AI Risks & How to Prevent Them – Insights from the 2025 Tenable Cloud AI Risk Report – Tenable Triple-T
As organizations rapidly adopt AI and large language models (LLMs), new and complex cloud security challenges are emerging. From unpatched software vulnerabilities to misconfigured environments exposing sensitive data, the risks to AI workloads are growing. Is your organization secure?
Our session will explore critical insights from recent research, including real-world vulnerabilities and misconfigurations found in self-managed AI developer tools and services across AWS, Google Cloud, and Microsoft Azure. Learn actionable security best practices to protect your AI workloads in dynamic cloud environments.
Jeremy Donohue has nearly 10 years of cyber risk reduction expertise, both on the customer side and as a vendor. He currently holds an Enterprise Security Engineer position at Tenable where he helps some of North America’s largest organizations reduce cyber risk across various attack surfaces. Before joining Tenable 3 years ago, he ran several large-scale vulnerability management programs across various sectors including higher education and healthcare. He has a bachelor’s degree in Cyber Defense from Northern Michigan University.
