How to prevent proprietary code leaks from Cursor

The safest way to prevent proprietary code leaks in Cursor is to explicitly control what the editor is allowed to send to the AI models. Cursor gives you settings that let you disable cloud context, disable automatic code uploads, and require manual approval before anything leaves your machine. The second part of protection is your own workflow: never paste sensitive credentials into chats, use environment variables, and restrict which folders Cursor indexes. When configured correctly, Cursor behaves like a local VS Code editor that only shares what you intentionally send.

 

What Actually Prevents Leaks in Cursor

 

Cursor runs locally, but the AI models it uses (OpenAI, Anthropic, etc.) run in the cloud. That means code can leave your machine only when you ask the AI something that requires sending context. The goal is to minimize and control those moments. Below is what truly works and is supported today.

 

• Disable “Automatically send full project context” in Cursor settings. This prevents Cursor from uploading large chunks of your repo without your intent.
• Turn on Manual Approvals so Cursor asks before sending any file or diff to the model.
• Exclude sensitive folders using the built‑in “Ignored Files / Folders” setting so AI tools cannot read or index those directories.
• Never include secrets in code. Use environment variables, .env files, or secret managers instead.
• Block API access at the network level if your company requires hard guarantees (e.g., using a firewall or VPN rules).
• Use self‑hosted models if you absolutely cannot send code to cloud AI. Cursor supports local model configuration, but you must provide your own model server.

 

Step-by-Step: How to Set Cursor to “Safe Mode” for Proprietary Code

 

These steps walk a junior dev through protecting the codebase without needing deep AI knowledge.

• Open Cursor ➝ Settings ➝ Privacy. Turn off anything labeled “auto‑send”, “auto‑context”, or “background indexing”.
• Enable Approval Prompts. This makes Cursor show a popup every time it wants to send code. You click Approve or Deny.
• Configure Ignored Folders. Add things like internal libraries, sensitive scripts, compliance‑related code, or areas with proprietary algorithms.
• Store secrets outside your repo. If you do something like this in Node:

// NEVER commit secrets in code
const apiKey = process.env.INTERNAL_API_KEY  // safe

• Block uploads using network tools. If your company uses a Zero‑Trust model, you can require all outbound traffic to AI endpoints to be blocked unless authorized by IT.
• Optional: Use a self‑hosted LLM endpoint. Cursor lets you set a custom model URL so nothing goes to OpenAI/Anthropic.

 

How Professionals Actually Work Day-to-Day

 

Developers who use Cursor in real production environments follow a pattern:

• They keep sensitive internals in excluded folders so Cursor never picks them up.
• They let Cursor reason on non-sensitive parts like UI components, utility functions, or open-source dependencies.
• They avoid asking the AI questions that would require full‑file uploads unless it’s harmless.
• They use Git as the single source of truth and manually review AI‑generated diffs before committing.

 

Realistic Limitations You Should Understand

 

Cursor cannot “accidentally leak everything” by itself. It only sends data when:

• You type something into the chat that includes code.
• You request a change that requires sending file context.
• You have auto‑send on (which you should disable for proprietary work).

When those are controlled, Cursor is as safe as any cloud‑enabled IDE.

 

Quick Example: Fully Safe Workflow

 

This is how a senior dev usually handles a proprietary codebase:

• AI features turned on only for specific files.
• Sensitive folders excluded.
• Manual approval required.
• No secrets in code. .env is in .gitignore and not shared with Cursor.

This gives you almost all the productivity benefits of Cursor without exposing proprietary logic.

 

If you configure Cursor as described above, you can safely use it in enterprise codebases with very minimal risk of code leakage.