Securing Cloud Assets in the AI Era: What Enterprises Must Know

As organizations accelerate AI adoption, the security perimeter around cloud environments is shifting faster than most governance frameworks can keep up. Dark Reading is hosting a virtual event bringing together cloud architects, CISOs, and AI specialists to address the rising attack surface introduced by generative AI workloads, autonomous agents, and large language models deployed across multi-cloud and hybrid infrastructures.

The discussion will examine practical strategies for protecting AI pipelines, training data, and inference endpoints from data poisoning, model theft, and prompt injection attacks. Speakers will cover misconfiguration risks in services like AWS Bedrock, Azure OpenAI, and Google Vertex AI, where overly permissive IAM roles and exposed APIs continue to be a leading cause of cloud breaches. Attendees will learn how to harden containerized AI workloads, enforce least-privilege access, and detect anomalous behavior across distributed cloud assets.

Beyond architecture, the event emphasizes continuous validation. Security teams are encouraged to routinely run an SSL/TLS checker on public-facing AI endpoints and use a port scanner to identify unintended exposure of model APIs and Jupyter notebook instances. A DNS leak test is also recommended to verify that queries from cloud-based AI workloads are not leaking metadata through misconfigured resolvers.

With regulators in the EU, U.S., and Asia drafting new AI-specific compliance requirements, the session will also map emerging frameworks such as the EU AI Act and NIST's AI Risk Management Profile to actionable cloud security controls, helping enterprises build a defensible posture before the next wave of AI-driven threats arrives.