The 5-step framework for closing the AI exposure gap

A practical playbook for governing, discovering, and securing AI across your attack surface

AI is embedded in productivity tools, SaaS platforms, developer libraries, cloud services, and APIs. Every prompt, file upload, agentic workflow, and integration is a potential exposure point that traditional security controls weren't built to monitor. See what security teams need to do to close that gap:

Secure AI and close the exposure gap

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Establish AI governance

Set the ground rules before AI initiatives get ahead of your ability to secure them.

Discover AI across your attack surface

You can’t protect what you can’t see. DLP and CSPM tools are a starting point, but holistic discovery requires specialized tools.

Secure AI agents and workloads

AI is only as safe as the infrastructure it runs on. Proactively hardening environments helps to reduce the risk of model exploitation.

Assess AI usage and interactions

Policy and real-world usage rarely match. You need granular visibility into how your teams interact with Generative AI and autonomous agents.

Contextualize with exposure management

AI risk doesn’t exist in a vacuum. AI security must be correlated with your broader exposure data.

How Tenable helps

Tenable One unifies AI security risks with the rest of your attack surface, giving security teams the visibility and context to understand which AI-related exposures actually put the business at risk, and act on the ones that matter most.

The 5-step framework for closing the AI exposure gap

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