Cursor Security Issues
Known vulnerabilities, privacy concerns, and security best practices for Cursor IDE. Stay informed and protect your development workflow.
Check if your AI-generated code has security vulnerabilities.
Known Security Issues
MCP Server Code Execution Vulnerability
Model Context Protocol (MCP) servers in Cursor can execute arbitrary code on your machine. Malicious or compromised MCP servers could potentially access files, execute commands, or exfiltrate data.
Mitigation Steps
- Only use MCP servers from trusted sources
- Review MCP server code before installation
- Run Cursor with minimal file system permissions
- Monitor network activity from Cursor processes
Context Injection via Malicious Code
Code opened in Cursor is sent to AI models for context. Malicious code containing prompt injection attacks could potentially influence AI responses, leading to generation of insecure or malicious code.
Mitigation Steps
- Be cautious when opening untrusted repositories
- Review AI-generated code carefully
- Don't auto-accept AI suggestions for security-critical code
- Use Privacy Mode for sensitive projects
Code Sent to External Servers
Cursor sends code context to Anthropic and OpenAI servers for AI processing. While encrypted in transit, this means proprietary code leaves your machine. Privacy Mode disables this but also disables AI features.
Mitigation Steps
- Enable Privacy Mode for sensitive projects
- Review Cursor's data retention policies
- Consider self-hosted alternatives for classified work
- Use .cursorignore to exclude sensitive files
Extension Supply Chain Risks
Cursor supports VS Code extensions, inheriting their supply chain risks. Malicious extensions could access code, credentials, and system resources.
Mitigation Steps
- Only install extensions from verified publishers
- Review extension permissions before installing
- Keep extensions updated
- Audit installed extensions regularly
Accidental Credential Exposure in AI Prompts
Developers frequently paste code containing API keys, passwords, or secrets into Cursor's AI chat. These credentials are sent to external AI providers and may be logged or used for training.
Mitigation Steps
- Never paste real credentials into AI prompts
- Use placeholder values when seeking AI help
- Enable Privacy Mode for credential-heavy work
- Rotate any credentials that may have been exposed
Cursor Security Features
Privacy Mode
AvailableDisables sending code to external AI servers. Your code stays local, but AI features are disabled.
Recommended: Use for proprietary or sensitive codebases
.cursorignore
AvailableExclude specific files or directories from AI context, similar to .gitignore.
Recommended: Add .env files, credentials, and sensitive configs
SOC 2 Compliance
EnterpriseCursor claims SOC 2 Type II compliance for enterprise customers.
Recommended: Verify compliance documentation for enterprise use
Local Model Support
LimitedRun AI models locally to avoid sending code to external servers.
Recommended: Consider for maximum privacy, but reduced capabilities
Security Best Practices
Workspace Security
- Enable Privacy Mode for sensitive or proprietary projects
- Add .env, credentials, and secrets to .cursorignore
- Use separate Cursor workspaces for client/sensitive projects
- Regularly audit which files Cursor has access to
MCP Server Safety
- Only install MCP servers from official or verified sources
- Review MCP server source code before installation
- Monitor system resources when using MCP servers
- Disable unused MCP servers
Extension Security
- Only install extensions from VS Code Marketplace verified publishers
- Review extension permissions and changelogs
- Uninstall unused extensions
- Keep extensions updated to patch vulnerabilities
Code Generation Safety
- Always review AI-generated code before using
- Don't auto-accept AI suggestions for auth, crypto, or security code
- Be suspicious of AI suggestions when working in untrusted repos
- Test AI-generated code thoroughly before deployment
Check Your Cursor-Built App's Security
Built something with Cursor? Our scanner checks for the common vulnerabilities in AI-generated code - exposed secrets, auth issues, and misconfigurations.
Get Starter ScanFrequently Asked Questions
Is Cursor safe to use for work projects?
Cursor can be safe for work projects with proper precautions. Enable Privacy Mode for sensitive code, use .cursorignore for credentials, and review AI-generated code carefully. For highly confidential work, consider whether sending any code context to external servers is acceptable under your company's security policies.
Does Cursor store my code?
According to Cursor's privacy policy, code sent to their servers is used for AI processing but not stored long-term or used for training without consent. However, code is processed by third-party AI providers (Anthropic, OpenAI) who have their own data policies. Enable Privacy Mode to keep all code local.
What is the MCP vulnerability in Cursor?
MCP (Model Context Protocol) servers can execute arbitrary code on your machine with the same permissions as Cursor. While this is how MCP is designed to work (it's not a bug), it means installing untrusted MCP servers is equivalent to running untrusted code. Only use MCP servers from sources you trust completely.
How do I enable Privacy Mode in Cursor?
Go to Cursor Settings → Privacy → Enable 'Privacy Mode'. This prevents your code from being sent to external AI servers. Note that this disables most AI features - you'll need to use local models for AI assistance in Privacy Mode.
Can Cursor access my entire file system?
Cursor has access to files in your workspace and any files you explicitly open. It doesn't automatically scan your entire file system. However, MCP servers you install may have broader access depending on their configuration. Review MCP server permissions carefully.
Should I use Cursor for security-sensitive development?
For security-sensitive development, enable Privacy Mode and carefully review all AI-generated code. Be especially cautious with AI suggestions for authentication, encryption, and access control. Consider whether the AI productivity benefits outweigh the additional attack surface for your specific threat model.