Cursor Privacy Mode & Data Security: What You Need to Know

Before you paste proprietary code into an AI-powered IDE, you need to know where it goes. This guide breaks down how Cursor handles your data, what Privacy Mode actually does, and how to build a safe workflow for sensitive projects.

How Cursor Handles Your Code by Default

Cursor is a fork of VS Code with AI features layered on top. When you use AI chat, autocomplete, or command-k editing, your code snippets are sent to model providers — primarily Anthropic and OpenAI — to generate responses.

By default, Cursor:

• Sends relevant code context to cloud LLM APIs to power chat and completions
• Logs some metadata for debugging and product improvement
• Does not use your code to train models (this is explicitly stated in their policy)

info

Cursor's terms state they do not train on your code. However, the code is still transmitted to third-party providers (Anthropic, OpenAI) whose data handling policies apply at that layer.

The key point: default Cursor is not "local-only." If you open a file containing API keys, database schemas, or proprietary algorithms, that context may leave your machine.

What Is Privacy Mode and How to Enable It

Privacy Mode is Cursor's answer to data sensitivity concerns. When enabled, it changes how the IDE handles telemetry and logging.

How to Enable Privacy Mode

Open Cursor Settings (Ctrl/Cmd + ,) and search for Privacy Mode:

Settings > General > Privacy Mode

Toggle it on. You will also see related options for:

• Crash reporting: disable to stop sending stack traces
• Usage analytics: disable to stop sending feature usage data

What Privacy Mode Actually Does

• Disables telemetry and analytics sent to Cursor's servers
• Prevents crash reports from including code snippets
• Reduces the amount of metadata logged about your usage

warning

Privacy Mode does not stop your code from being sent to LLM providers. It only affects Cursor's own telemetry. If you ask the AI chat a question about your code, that code still goes to Anthropic or OpenAI unless you are using a local model.

What Data Gets Sent to the Cloud

Understanding the data flow helps you make informed decisions. Here is the breakdown:

Feature	Data Sent	Destination
AI Chat (Cmd+L)	Selected code + prompt	Anthropic / OpenAI
Cmd+K inline edit	Surrounding code + instruction	Anthropic / OpenAI
Tab autocomplete	Current line + context	Anthropic / OpenAI
Cursor Tab (predictions)	File context	Cursor's servers / providers
Telemetry (if enabled)	Usage patterns, errors	Cursor's servers

The context window sent with each request includes the file you have open, nearby lines, and sometimes related files from the project. It is not your entire codebase, but it can be meaningful chunks.

tip

If you are reviewing a file with hardcoded secrets, close the AI chat panel or switch to a local model before opening that file. Cursor typically sends context from the active editor.

Enterprise and Team Security Considerations

For teams handling regulated data or working under strict compliance requirements, the default setup is often not enough.

What Teams Should Know

• Cursor does not currently offer a self-hosted or air-gapped enterprise version
• There is no built-in SSO or audit logging of AI requests at the code-snippet level
• Data residency controls are limited compared to dedicated enterprise AI platforms

Mitigations for Teams

1. Use local models for sensitive projects. See the local LLM setup guide for configuration steps.
2. Establish clear policies about which projects can use cloud AI features.
3. Review the .cursorignore file — you can exclude sensitive files from being indexed or sent as context.

Example .cursorignore:

# .cursorignore
.env
.env.local
secrets/
config/production.yml
*.key
*.pem

info

The .cursorignore file works similarly to .gitignore. Files listed here are excluded from Cursor's codebase indexing and are less likely to be pulled into AI context windows.

Recommended Workflow for Sensitive Projects

If you work on code that cannot be exposed to third-party APIs, here is a practical workflow:

1. Segment your work: Keep sensitive projects in a separate workspace or VS Code window without AI features.
2. Use .cursorignore aggressively: Exclude config files, test data, and anything with PII.
3. Enable Privacy Mode: At minimum, turn off telemetry.
4. Run a local model for that project. It is slower but keeps everything on your machine.
5. Audit before asking: If you must use cloud AI, manually select only the non-sensitive snippet you need help with, rather than letting Cursor infer context from the whole file.

warning

Do not rely on Privacy Mode alone for compliance. It does not encrypt your prompts or prevent code from reaching LLM providers. For HIPAA, SOC 2, or similar requirements, treat cloud AI features as external data processors.

Cursor vs GitHub Copilot: Privacy Comparison

Developers often compare Cursor and Copilot on privacy. Here is how they stack up:

Aspect	Cursor	GitHub Copilot
Code used for model training	No (stated policy)	No (stated policy)
Telemetry disabled option	Yes (Privacy Mode)	Yes (github.copilot.advanced settings)
Local model support	Yes (via OpenAI-compatible API)	No
Enterprise self-hosted option	No	No (Copilot Enterprise is cloud-hosted)
Audit logs of AI requests	Limited	Limited
Data retention by provider	Subject to Anthropic/OpenAI policies	Subject to OpenAI policy

Neither tool offers a fully air-gapped solution out of the box. Cursor's advantage is local model support, which lets you opt out of cloud providers entirely. Copilot requires GitHub/OpenAI infrastructure for all completions.

tip

If your organization already has an Azure OpenAI or enterprise Anthropic agreement with custom data handling terms, check whether Cursor can be configured to route through those endpoints. This is sometimes possible with custom base URL settings.

Checking What Cursor Knows About Your Project

Cursor indexes your codebase to provide better context. You can see what is indexed and manage it:

1. Open the Command Palette (Ctrl/Cmd + Shift + P)
2. Search for Cursor: Show Indexed Files or check the AI panel settings
3. Review the file list and add exclusions as needed

If a file should never appear in AI context, add it to .cursorignore and restart Cursor.

Final Thoughts

Cursor is a powerful tool, but its AI features are fundamentally cloud-dependent by default. Privacy Mode is a good first step for reducing telemetry, but it is not a complete security solution. For developers working with sensitive code, the practical choices are:

• Use local models and accept the capability trade-off
• Use .cursorignore and manual context control to limit exposure
• Keep the most sensitive projects in a plain VS Code instance without AI extensions

Understand the data flow, configure the tools honestly, and build a workflow that matches your project's risk level.