What is a Shadow Model?

A shadow model is an AI model deployed or developed without visibility or approval from the security team. Like shadow IT, shadow models bypass governance, introducing unmanaged risk—from unvetted datasets to insecure endpoints or unclear licensing—and often go undetected in modern development environments.

Detailed Answer (400–500 words)

Shadow models are a growing risk in enterprises adopting AI. These models may be uploaded from open-source repositories, trained by individual teams, or integrated into apps without security review. Because they exist outside formal controls, they often:

• Use noncompliant or unknown datasets
• Contain unsafe or untested logic
• Expose API keys or unmonitored endpoints
• Bypass red teaming, licensing review, or encryption

Shadow models typically emerge in fast-paced environments where innovation is prioritized over governance. Without proper discovery and inventory, security and compliance teams are left in the dark.

Detecting and managing shadow models is essential to maintaining trust, meeting regulatory requirements, and avoiding AI-related breaches.

How PointGuard AI Helps:
PointGuard AI Discovery automatically scans connected AI environments—such as Databricks, Azure, SageMaker, and Vertex AI—to identify all models, notebooks, datasets, and endpoints. It flags unapproved models, tracks ownership, and enables one-click approval or remediation. This prevents shadow AI risk without slowing down innovation.
Learn more: https://www.pointguardai.com/ai-discovery