AI security posture management (AI-SPM)?

• AI-SPM continuously discovers AI models, services, pipelines, and training data across multi-cloud environments, including shadow AI. 
• It shows which human and non-human identities can reach your AI models and training data, flags over-permissioned access, and maps misconfigurations that can turn into attack paths. 
• AI-SPM connects exposure to AI resource sensitivity, exploitability, and business impact, so your teams can focus remediation on actual risk. 
• Used together, AI-SPM and DSPM connect a data exposure to the AI resource it feeds and the identity that could exploit both.

AI security posture management (AI-SPM) identifies and reduces risk to the AI resources and data running across your cloud environments.

An AI-SPM solution: 

• Discovers AI models, services, pipelines, and training data 
• Classifies what it finds
• Maps how AI resources connect to identities and infrastructure
• Flags the misconfigurations, excessive permissions, and exposed data that put those resources at risk

AI-SPM focuses on cloud-native, AI-specific risk. It accounts for the complexity of modern environments: multi-cloud, multi-identity, non-human identities at scale, and rapidly expanding AI adoption.

AI-SPM platforms help your security teams answer four critical questions:

1. Where are our AI models, services, and training data?
2. Which human and non-human identities can access them?
3. Is that access necessary or over-permissioned?
4. Do misconfigurations or exposed training data create an attack path?

Done right, AI-SPM gives you a continuous view of AI risk in context, not just point-in-time snapshots. It shares the same foundation as data security posture management (DSPM), extending sensitive-data discovery to the AI resources that increasingly consume and generate that data.

AI Adoption has become the norm and is a staple in the workplace for many industries. Rapid AI adoption accelerates operations, but it expands your attack surface and increases cyber risk. Teams can stand up a model endpoint, connect a training pipeline, or wire in a third-party AI service in minutes. That flexibility makes it easy to lose track of where AI resources live, what data they touch, and who can reach them.

AI-SPM bridges this gap with visibility into AI resources, their configurations, their access paths, and the identities behind them. 

Tenable One Cloud Exposure, for example, detects AI resources and software across providers, including AWS Bedrock, Amazon SageMaker, Foundry Tools (formerly Azure AI services) and Gemini Enterprise Agent Platform (formerly Vertex AI), so shadow AI and unmanaged models don’t slip through unnoticed.

AI-SPM also strengthens governance and compliance by mapping AI configuration controls and entitlements to sensitive training data. And as cloud security maturity evolves, AI-SPM integrates AI-specific risks into broader exposure management programs while embedding AI-specific controls directly into cloud-native application protection platforms (CNAPP).

1. Automatically discover and classify AI resources

AI-SPM continuously detects AI models, services, workloads, and software components across AWS, Azure, and GCP. Automatic detection and labeling identify every AI resource so nothing runs unmanaged.

2. Identify and protect sensitive training data

AI-SPM classifies sensitive training data, such as company secrets and personally identifiable information (PII), and applies built-in AI configuration policies to protect it. This works hand-in-hand with DSPM, which discovers and classifies sensitive data wherever it lives.

3. Enforce least-privilege AI entitlements

By extending cloud infrastructure and entitlements management (CIEM) to AI, AI-SPM ensures only identities with the correct access policies can reach proprietary AI models. Intuitive access visualizations surface over-permissioned users and non-human identities so you can enforce least privilege.

4. Prioritize AI risk in context

Instead of flooding you with alerts, AI-SPM ties exposure to AI resource sensitivity, its exploitability, and business impact, so teams focus on the risks that actually matter.

5. Remediate with confidence

AI-SPM provides context-driven remediation guidance: revoking excess access, hardening a model configuration, or securing exposed training data. Integration with cloud security posture management (CSPM) and CIEM streamlines enforcement across the cloud stack.

AI-SPM follows a six-phase continuous cycle:

1. Discovery

Scans cloud environments for AI models, managed AI services, training pipelines, and the workloads that support them, including shadow AI running outside approved AI governance.

2. Classification

Automatically labels AI resources and the sensitive training data they consume, based on regulatory frameworks and business logic, with support for custom classification of proprietary models and IP.

3. Access analysis

Evaluates who and what can access AI resources, including human users, machine identities, service accounts, and third-party integrations, and aligns with CIEM capabilities to catch over-permissioned AI entitlements.

4. Posture assessment

Checks AI and machine learning configurations against best-practice policies; flags insecure defaults, disabled logging, public exposure, and unencrypted training data; and connects risks directly to affected AI resources.

5. Risk modeling

Uses exposure graphs to map toxic combinations between misconfigured resources, over-permissioned non-human identities and sensitive AI data, helping teams visualize attack paths and prioritize high-impact risk.

6. Remediation and response

Prioritizes and fixes the exposures that matter most using guided remediation and policy automation across your CNAPP.

AI-SPM delivers value through practical, high-impact use cases that address the biggest emerging AI risks. Here are six ways your organization can use it to reduce risk:

1. Discover every AI model and service, including shadow AI outside AI governance.
2. Protect sensitive training data from exposure, misuse, or poisoning.
3. Enforce least-privilege access to proprietary AI models across human and non-human identities.
4. Sever attack paths where misconfigured resources and over-privileged identities expose AI workloads.
5. Demonstrate AI configuration best practices for AI governance and AI compliance frameworks.
6. Detect risky AI packages and components early in the pipeline.

AI-SPM brings AI-resource insights into your DevSecOps lifecycle, so your teams can shift left and catch risky AI handling before production. Embedded into CI/CD pipelines, AI-SPM flags issues like unsecured model endpoints, exposed training data in test environments, or excessive service-account access to AI resources.

With this visibility, developers can harden configurations, tighten AI entitlements, and secure training data before problems spread across environments. AI-SPM surfaces toxic combinations, such as public access to a model with over-privileged credentials, and provides clear remediation steps to keep security, compliance, and development speed in sync.

Shadow AI is any model, service or AI-powered tool spun up outside your AI governance framework, from unsanctioned SaaS AI apps to forgotten training jobs. It’s an unmonitored surface attackers are eager to exploit. For a deeper look at these risks, see the challenges of securing AI.

AI-SPM addresses shadow AI by extending scanning coverage beyond approved environments. It scans connected accounts and services to find AI resources wherever they live, maps them to the training data and identities they touch, and highlights sensitive exposure. 

Guided remediation then helps you bring shadow AI back under control: securing configurations, revoking risky access, or retiring unmanaged models. By regaining visibility over these unknowns, AI-SPM shrinks your attack surface and eliminates a fast-growing source of untracked AI risk.

Emerging AI regulations and internal governance demand tight control over how your organization configures AI resources and who can access them, with evidence to back it up. AI-SPM automates the workflows that make this manageable. 

AI security posture management continuously discovers and classifies AI resources and their training data, checks configurations and entitlements against policy, and flags drift in risk-scored dashboards. When auditors or governance reviews arrive, you have evidence that maps AI resources to controls and remediation steps, so your AI posture is audit-ready even as environments evolve.

At its core, AI-SPM reduces cloud risk in a targeted, measurable way: 

• Adds AI context to your infrastructure and identity visibility.
• Builds exposure graphs that show how identities, configurations, network paths, and AI resources interact.
• Reveals real attack paths.

Risk scoring prioritizes actual risk: a sandbox model with synthetic data scores lower than a production model exposing proprietary training data. Because monitoring is continuous, risk reduction isn’t a one-time effort. For a broader view of how AI fits into a security program, see AI cybersecurity principles.

AI-SPM and DSPM are deeply complementary:

• DSPM discovers, classifies and secures sensitive data across cloud and SaaS environments. It answers: “Where is our sensitive data, and who can reach it?"
• AI-SPM extends that lens to the AI resources that consume and produce data: models, pipelines, and AI services. It answers: 
  • “Which AI resources touch that data?” 
  • “Are the resources securely configured?” 
  • “Who or what can access the model itself?” 

 Used together within Tenable One Cloud Exposure, DSPM and AI-SPM give you layered visibility, connecting a data exposure to the AI resource it feeds and the identity that can exploit both.

You strengthen your security posture by embedding AI-SPM into your exposure management strategy. Combining AI-SPM with DSPM, CSPM, and CIEM in a unified exposure management platform gives you one view of risk across data, infrastructure, identity, and AI.

• CSPM spots the misconfigured resource.
• CIEM highlights the over-privileged identity.
• DSPM connects findings to the sensitive data at risk.
• AI-SPM ties it all to the AI model or service that could be compromised.

Together, they reveal toxic combinations, like an over-privileged non-human identity reaching a publicly exposed model trained on sensitive data. Individually, those issues may look minor; combined, they form an exploitable attack path. For teams governing broader AI use, this pairs with Tenable AI Exposure in Tenable One.

To reduce AI risk, look for an AI-SPM solution that goes beyond basic discovery and delivers context-driven, actionable intelligence. Prioritize an AI-SPM platform that:

• Supports multi-cloud environments with consistent visibility across AWS, Azure, and GCP AI services.
• Uses agentless, API-based scanning to avoid blind spots and reduce operational overhead.
• Automatically detects and labels AI resources, including shadow AI.
• Classifies and protects sensitive training data with built-in AI configuration policies.
• Extends CIEM to enforce least-privilege AI entitlements across human and non-human identities.
• Maps misconfigurations, identities, and data into real attack paths, not isolated alerts.
• Integrates with DSPM, CSPM, CIEM, and CNAPP for a unified risk view.
• Provides risk scoring and guided remediation to fix the highest-impact exposures first.

Tenable’s AI-SPM capabilities are part of Tenable One Cloud Exposure, a unified cloud security platform that integrates AI-SPM, DSPM, CSPM, CIEM, and vulnerability management. With Tenable, you get deep visibility into:

• Every AI model, service, and pipeline across your multi-cloud environment
• The sensitive training data those resources consume
• Which human and non-human identities can access them
• Which exposure paths pose real, exploitable risk

By mapping AI resources to cloud misconfigurations, over-permissioned entitlements, and exposed data, Tenable helps you find and fix the gaps that matter most. You can also conversationally search, explain, and act on AI risk with Tenable Hexa AI in Tenable One.

Learn how Tenable One Cloud Exposure supports AI security posture management.