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Continuously discover and monitor all AI usage across your organization, including shadow AI, agents, browser plug-ins, and more, with Tenable One AI Exposure. Map complex AI workflows to reveal high-impact exposures and monitor compliance with security and AI acceptable use policies.Key takeawaysNow generally available in the Tenable One Exposure Management Platform, Tenable One AI Exposure gives security teams capabilities to monitor and secure AI-driven workflows. Map complex AI workflows to reveal how applications, infrastructure, identity, agents, and data combine to create high-impact exposure. Protect against AI-specific risks like prompt injection and jailbreak attempts while identifying sensitive data shared through AI prompts.The rapid integration of AI across applications and infrastructure has outpaced the reach of traditional security oversight. As autonomous agents and cloud-based AI become central to the enterprise, security teams are struggling to manage a new class of risk that legacy tools were never designed to see — creating a critical AI exposure management gap.Today, we are launching Tenable One AI Exposure to provide security teams with the capabilities needed to close that gap and mitigate AI security risks. Now generally available within the Tenable One Exposure Management Platform, these capabilities allow organizations to secure their AI-driven workflows without slowing innovation.The AI exposure management gap explainedThe AI exposure management gap refers to three challenges security teams face: whether they can see how employees are using AI, where it’s running, and how AI exposure accumulates across interconnected systems — both within and outside an organization.AI exposure is hard to gauge for a variety of reasons. For one, it doesn’t look like traditional cyber risk. It doesn’t live in one system. It doesn’t announce itself as a vulnerability. And it doesn’t wait for attackers to exploit it before causing harm. AI security risks show up in:Employee-facing AI platforms like ChatGPT, Copilot, and embedded SaaS featuresCloud-based AI services and model pipelinesAPIs, agents, and browser plug-insPublic-facing applications and servicesMuch of this adoption happens outside traditional security workflows. Shadow AI deployments, forgotten test environments, unsafe integrations, and over-permissioned services quietly expand the attack surface, often without security teams realizing they exist.At the same time, AI workloads rely on complex chains of infrastructure, identities, APIs, and data access. A single misconfiguration or overly broad permission can turn routine AI usage into a high-impact exposure.Because AI interactions happen constantly through prompts, uploads, responses, and automated actions, even approved use can unintentionally expose sensitive data without the right visibility and guardrails in place.Finally, AI exposure rarely appears as a single alert or vulnerable asset. Instead, it emerges through connections. For example:An employee uses an approved third-party toolThat tool invokes an internal AI service or agentThe agent has access to sensitive data or systemsA misconfiguration or exposed endpoint makes that access reachableIndividually, each component may appear benign. Together, they create real risk.Traditional security tools tend to look at these elements in isolation: cloud posture here, identity permissions there, application risk somewhere else. Without a way to connect these signals, security teams are left reacting to symptoms instead of managing exposure.Introducing Tenable One AI ExposureTenable One AI Exposure helps teams close this visibility gap by continuously discovering, contextualizing, and prioritizing AI-related exposure across your organization — internal and external, on-premises and cloud — to deliver a complete, risk-aware view of where AI operates, its connections, and where it creates exposure. Unlike point AI cybersecurity tools that surface isolated findings, Tenable One connects the entire activity chain in a single view, showing how AI applications, infrastructure, identity, agents, and data combine to create real risk. By correlating these relationships, Tenable One helps your security teams prioritize the AI exposures that matter most to reduce AI security risks across all environments.How Tenable One helps secure the AI attack surfaceDiscover AI across your organizationYou can’t manage AI risk if you don’t know where AI exists.Tenable One continuously discovers AI usage across internal environments and the external attack surface, helping teams eliminate blind spots and maintain an up-to-date understanding of their AI footprint. This includes visibility into sanctioned and shadow AI across applications, endpoints, cloud workloads, APIs, agents, and publicly exposed services.Security teams can see where AI services are running, which technologies are in use, and how external exposure aligns with internal awareness. Source: Tenable, January 2026 Understand how AI creates exposureDiscovery alone isn’t enough. AI risk emerges from how systems interact.Tenable One maps AI workflows across cloud platforms and services, revealing how AI models, infrastructure, storage, networking, and access controls work together. It highlights vulnerabilities and misconfigurations in AI-related software and cloud resources while providing context about what data and systems those components can reach.By connecting AI infrastructure with identity and access paths, teams gain clarity into where exposure is actually created, not just where AI exists. Source: Tenable, January 2026 Protect AI workloads, services, and accessReducing AI risk means closing the gaps attackers exploit. Tenable One helps teams identify and remediate risky configurations in AI workloads and model environments before they can be abused. It also surfaces excessive permissions and identity weaknesses tied to AI services and agents, enabling teams to enforce least-privilege access and reduce attack paths that put critical AI resources at risk.This identity-driven exposure insight helps security teams focus on the combinations of weaknesses that matter most.Govern AI usage and data flowAI adoption doesn’t have to come at the cost of security or compliance.Tenable One provides visibility into how employees and agents interact with AI platforms, including tools like ChatGPT, Copilot, and embedded generative AI features. It also shows how data flows through those interactions. Teams can identify sensitive data shared through prompts or uploads, enforce AI acceptable use policies, and apply guardrails that guide users toward safer AI behavior. The platform also detects AI-specific threats and misuse, such as prompt injection and jailbreak attempts, and provides high-fidelity context to support fast, confident response. Source: Tenable, January 2026 Secure AI adoption without slowing innovationAI doesn’t have to be your biggest blind spot, and security doesn’t have to be the brake on innovation. With Tenable One AI Exposure, organizations can move forward confidently, knowing they have a proactive, pre-breach approach to managing AI risk across the entire attack surface. New to Tenable? Request a Tenable One AI Exposure demo today.Existing customer? Reach out to your account team to expand your Tenable One coverage to include AI Exposure.
Analysis Summary
# Industry News: Tenable Launches AI Exposure Management Feature to Address Unseen AI Risks
## Summary
Tenable has released "Tenable One AI Exposure," now generally available within its Tenable One Exposure Management Platform. This new capability is designed to address the growing "AI exposure management gap" by continuously discovering, mapping, and monitoring all internal and external organizational use of AI—including shadow AI, agents, and plugins—to help organizations govern usage, enforce policies, and mitigate complex, context-dependent risks like prompt injection.
## Key Details
- Date: Announcement of General Availability (Implied recent, based on context within the article structure)
- Companies Involved: Tenable
- Category: Product Launch / Platform Update
## The Story
The rapid integration of AI into enterprise workflows has created a significant security blind spot, termed the "AI exposure management gap." Legacy security tools are ill-equipped to monitor risks emanating from autonomous agents, cloud-based AI, and employee usage of tools like consumer-facing LLMs (e.g., ChatGPT, Copilot). Tenable One AI Exposure integrates into the existing Tenable One platform to provide continuous discovery of all AI usage, mapping complex workflows that link applications, infrastructure, identity, and data. Crucially, it moves beyond identifying isolated assets by contextualizing how these components interact to form high-impact exposures. The feature specifically aims to identify sensitive data leakage via prompts, enforce acceptable use policies, and detect AI-specific threats such as prompt injection and jailbreaks, allowing security teams to secure AI adoption without impeding business innovation.
## Business Impact
### For the Companies Involved
- **Tenable:** This launch strategically positions Tenable ahead of the curve in the rapidly evolving exposure management space by directly addressing the newest category of digital risk: AI exposure. It deepens the value proposition of the unified Tenable One platform, encouraging cross-sell and upsell opportunities to existing customers seeking comprehensive visibility.
### For Competitors
- Competitors in the broader vulnerability or attack surface management space will now be pressured to rapidly integrate or acquire similar dedicated AI workflow mapping and governance capabilities to avoid appearing behind the curve regarding emerging enterprise risks.
### For Customers
- Customers gain a cohesive, pre-breach approach to AI risk management, reducing the operational burden of managing AI risk across disparate point solutions. They can now manage compliance (e.g., acceptable use policies) alongside traditional technical risks like misconfigurations in AI environments.
### For the Market
- This launch solidifies the concept that AI security requires a dedicated "exposure management" framework, rather than being purely an application security or identity issue. It standardizes the types of visibility required to govern enterprise AI safely.
## Technical Implications
Tenable One AI Exposure leverages context correlation across multiple data sources:
1. **Discovery:** Identifying sanctioned and shadow AI footprint across endpoints, cloud, and external surfaces.
2. **Mapping:** Visualizing complex AI workflows (model, infrastructure, identity, data access paths).
3. **Risk Contextualization:** Identifying high-impact exposure based on the *combination* of weaknesses (e.g., an overly permissive identity linked to an AI agent processing sensitive data).
4. **Threat Detection:** Specifically monitoring for AI-native attack vectors like prompt injection and jailbreaking attempts.
## Strategic Analysis
- **Market Positioning:** Tenable positions itself as a holistic exposure management leader capable of evolving its platform to cover emerging technology risks, differentiating itself from competitors who might offer siloed AI security tools.
- **Competitive Advantage:** The advantage lies in the integration *within* the existing Tenable One platform, promising correlated risk prioritization rather than simply generating more, isolated alerts.
- **Challenges:** Successful adoption hinges on the platform's ability to accurately map complex, often proprietary, AI workflows across diverse customer environments, and to maintain efficacy as AI usage patterns continue to evolve rapidly.
## Industry Reactions
- (No specific external reactions were provided in the context, but the launch suggests the industry has recognized the "AI exposure management gap" as a critical, underserved problem requiring platform-based solutions.)
## Future Outlook
- We expect other major platform vendors to rapidly announce similar, integrated AI governance and exposure mapping features. The market will shift toward rewarding vendors that can correlate traditional security data with new usage patterns endemic to generative AI and autonomous agents.
## For Security Professionals
Security teams can expect to gain centralized visibility into Shadow AI, allowing them to shift from reactive clean-up to proactive policy enforcement for AI platforms. The ability to map data flows and enforce least-privilege access specifically for AI services significantly lowers the bar for securing these crucial new workloads.