Zscaler and Cursor Help Enterprises Secure AI-Assisted Development at the Endpoint

As AI coding workflows extend beyond the editor, Zscaler helps enterprises understand how Cursor is used on managed devices and apply the right security controls.

AI-assisted development is becoming part of how enterprises build software, and organizations are using Cursor to bring these capabilities into everyday development workflows. But a Cursor workflow can extend beyond the editor. To complete a task, an agent may access files, run commands, use skills, call Model Context Protocol (MCP) tools, connect to external services, or install software packages on the device.

Zscaler and Cursor are partnering to help enterprises secure agentic activity on managed devices. Cursor provides enterprise controls for its platform, while Zscaler complements them with endpoint visibility and policy controls to help engineering and security teams better manage risk.

Extending AI governance to the endpoint

Engineering and security teams need to understand where Cursor is deployed, how it is being used, and what related tools and integrations are active across the enterprise. Zscaler AI Endpoint Security helps provide that visibility on managed devices.

That visibility matters because AI coding activity rarely stays within a single tool or session. An agent may load instructions from a skill, connect to an external service, or add a software dependency as part of its work. To see the full picture, security teams need to connect those interactions to the user, device, and development session.

The Zscaler-Cursor partnership helps organizations:

• Identify Cursor deployments, including unmanaged installations, and see which tools, extensions, and integrations are present across managed devices.
• Understand how Cursor agents interact with development resources, software dependencies, and external services during their work.
• Apply endpoint policies that reflect organizational requirements for tools, data, and agent activity.
• Investigate unexpected activity with relevant user, device, application, and session context.

Combining inventory with observed activity gives security teams a clearer view of how tools are used, what data they access, and whether they connect to internal services.

Supporting secure enterprise adoption

This approach helps developers continue using approved Cursor capabilities while giving security teams a more consistent way to manage endpoint risk. Organizations can tailor policies by user, team, and device instead of applying broad restrictions across every development workflow.

Security and engineering teams can use shared visibility and activity context to refine controls over time. This helps organizations address unmanaged usage, configuration drift, risky integrations, and data exposure without unnecessarily interrupting legitimate development work.

For security operations teams, this creates a clearer path from detection to investigation. Instead of starting with an isolated command or tool call, analysts can review related activity and determine whether it reflects expected development work, a control that needs tuning, or behavior that requires further review.

Organizations can also apply data-handling controls when AI-assisted development involves sensitive information, helping support privacy, governance, and compliance requirements.

Looking ahead

By combining Cursor’s enterprise platform controls with Zscaler’s endpoint visibility and policy controls, the partnership helps customers better understand how AI-assisted development is used across managed devices and respond with the right controls. That gives enterprises a stronger foundation for adopting AI-assisted development in a way that supports both developer productivity and security requirements.

We’re excited to bring this innovation to life and to continue working together on the shared goal of helping enterprises adopt AI-assisted development securely and responsibly.