Discover Shadow AI

Shadow AI now extends far beyond unapproved chatbots, appearing across endpoints, development platforms, open-source models, agent frameworks, and MCP infrastructure. PointGuard AI helps security teams continuously identify these resources, understand their risk, and bring unknown AI under centralized governance.

The Challenge

AI resources can enter the enterprise through desktops, coding assistants, development platforms, agent frameworks, open-source models, MCP servers, and autonomous agents, often with little visibility into ownership, provenance, or security. Discovery alone is not enough: teams also need risk intelligence to determine whether a newly identified model, server, agent, or dependency is safe to use.

The Solution

Use PointGuard AI to turn Shadow AI discovery into a repeatable governance workflow:

1. Discover AI across the enterprise. Continuously identify models, agents, applications, MCP servers, tools, and connections across endpoints, development platforms, provider APIs, and runtime activity.

2. Build a centralized inventory. Consolidate discovered resources into a continuously updated inventory so unknown AI can be assigned ownership, reviewed, approved, restricted, or governed.

3. Assess risk with AI-specific intelligence. Evaluate discovered components using PointGuard AI's Risk Knowledge Base, which includes security scans of more than 300,000 open-source models and 40,000 open-source MCP servers across security, provenance, and delivery metrics.

4. Turn discovery into governance. Correlate discovery and risk intelligence to prioritize investigation and establish policies for which AI components are appropriate for enterprise use.

This approach gives security teams a continuous path from discovery to risk assessment and governance. Learn more about AI Discovery.

Use These PointGuard AI Modules

PointGuard AI provides a complete solution for this use case using these capabilities:

• AI Discovery: Discovers and inventories models, agents, applications, MCP servers, and other AI resources across enterprise environments.
• AI Risk Knowledge Base: Provides risk intelligence for more than 300,000 open-source models and 40,000 open-source MCP servers using security, provenance, and delivery metrics.
• MCP Security Gateway: Discovers and governs MCP servers, tools, connections, and unknown AI resources encountered through MCP traffic.
• Agent Mission Control: Discovers agents and models through runtime activity while providing centralized visibility into agent behavior and connections.