AI Exposure Is Part of Your Attack Surface Now
AI is embedded across apps, cloud services, APIs, and automated agents. That means risk doesn't live in a single tool. It cuts across identities, data, infrastructure, and how people use these systems.
As Liat Hayun, SVP of Product Management at Tenable, put it: "AI risk is an extension of the attack surface. It does not live in a single asset. It emerges across applications, infrastructure, identities, and data, and only becomes visible when those connections are understood together."
For many organizations, those connections have been missing. That's the gap Tenable is addressing by expanding Tenable One with AI Exposure and treating AI as part of exposure management, not a side project.
Bring AI into the exposure management workflow
Security teams already track vulnerabilities and attack surface risk. The friction has been fitting AI into those same workflows, especially when AI tools roll in fast and outside formal IT.
"With Tenable One, organizations can see, protect and manage AI risk alongside all other areas of risk for a more precise risk reduction strategy," Hayun said. "We're empowering security teams to address AI risk leveraging the platform they already use to manage all other forms of security risk."
Translation for managers: you don't need a separate AI security program to start reducing AI exposure. Fold it into the platform, process, and dashboards you already use.
From isolated signals to real context
Alerts without context waste cycles. Tenable's approach maps how AI interacts with data, identities, and systems so teams can see why a specific exposure matters and what to do about it.
"Tenable One provides a complete, risk-aware view of where AI operates, how it's connected, where exposure is created, what data or processes it touches, who has access, and how users interact with it," Hayun explained. "In short, Tenable One enables organizations to see, protect and govern AI usage across the enterprise."
- Know where AI runs (apps, cloud, agents, integrations)
- See the data it touches and who has access
- Understand the attack paths and prioritize by real business impact
What's different about Tenable's AI approach
Many vendors bolt AI fields onto existing views and stop there. Tenable is leaning into depth and integration.
"Unlike point solutions that cover only one piece of the AI security puzzle, Tenable offers a comprehensive AI security solution that delivers on AI discovery, proaction, and governance," Hayun said.
- Correlates misconfigurations, unsafe integrations, prompt injections, misbehaving agents, and shadow AI
- Surfaces the AI exposures most likely to drive impact across environments
Why this matters for MSSPs and multi-tenant teams
Managed providers need separation, clear access controls, and repeatable outcomes across clients. "Tenable One AI Exposure is available in Tenable One, and is offered within the Tenable One workspace," Hayun said. "This means that MSSPs can manage each of their clients from their MSSP multi-tenant portal without worry of data bleed between instances, as well as RBAC controls at both the MSSP and Client tenant level."
That structure keeps operations clean while showing value. "Tenable One AI Exposure helps clients provide measurable risk reductions by not only alerting them to potential exposure of valuable data or misuse of AI models, but also provides controls to block their models from responding to requests that may lead to those issues."
What leaders should do this quarter
- Weeks 1-4: Build an AI inventory. Discover apps, agents, models, and third-party tools in use across SaaS, cloud, and endpoints. Tag data sensitivity and identity paths.
- Weeks 5-8: Integrate AI into your risk scoring. Correlate AI usage with data access, misconfigs, and identity privilege. Prioritize exposures by business process and blast radius.
- Weeks 9-12: Enforce controls. Block risky prompts, restrict model access to least privilege, and put guardrails on data egress. Test playbooks for prompt injection and misuse.
Metrics that make AI risk visible
- AI asset coverage: % of apps, models, agents, and integrations discovered
- Mean time to detect unauthorized AI use
- Mean time to remediate AI exposures
- % of AI workflows with least-privilege access and data egress controls
- Quarter-over-quarter reduction in open AI-related exposures
Helpful references
If you need to raise your team's AI fluency quickly, explore practical courses by role at Complete AI Training.
The takeaway
AI is now woven into how businesses operate, which means it also changes the attack surface. Treat AI risk as a first-class exposure, not an add-on. The question isn't whether to govern it, but how quickly you can bring AI into the same risk conversations you already have for everything else.
Your membership also unlocks:
