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In an era where AI coding assistants handle vast amounts of proprietary code, security isn't just a feature—it's a foundational promise. Cursor, the AI-driven fork of VS Code, has pulled back the curtain on its security practices in a comprehensive disclosure, addressing mounting developer concerns about data leakage, infrastructure vulnerabilities, and compliance in tools that process sensitive intellectual property. This transparency comes as enterprises increasingly grapple with the trade-offs between AI productivity gains and supply chain risks.

The Bedrock: Certifications and Infrastructure

Cursor's security stance starts with SOC 2 Type II certification—a rigorous audit validating its controls over data security, availability, and confidentiality. Annual third-party penetration testing supplements this, with reports available via trust.cursor.com. Yet the real revelation lies in its infrastructure map. Code data routes through a multi-cloud ecosystem:

  • Core Providers: AWS hosts primary servers (US, Tokyo, London), while Cloudflare acts as a security-focused reverse proxy. Secondary workloads run on Microsoft Azure and Google Cloud Platform (GCP).
  • AI Inference Partners: Fireworks (for custom models), OpenAI, Anthropic, Google Vertex AI, and xAI process code data under zero data retention agreements. Crucially, requests hit Cursor's AWS servers first, even when users supply their own API keys.
  • Sensitive Data Handling: Turbopuffer stores obfuscated code embeddings (file names encrypted client-side), while Exa/SerpApi see search queries derived from code. Non-code subprocessors like Datadog and Slack receive only metadata.

"None of our infrastructure is in China. We do not directly use any Chinese company as a subprocessor," the documentation states, a pointed assurance amid geopolitical data-sovereignty debates.

Privacy Mode: The Ironclad Guarantee

For teams in regulated industries, Cursor's privacy mode—enforced by default for team users—is the crown jewel. It ensures code data is never stored by model providers or used for training. Over 50% of users leverage this, backed by a parallel infrastructure:

# Simplified privacy enforcement flow
if privacy_mode_enabled:
    route_request_to(privacy_replica)
    disable_logging()  # Code data never persisted
else:
    route_request_to(standard_replica)
  • Redundant Checks: Requests carry an x-ghost-mode header, with servers defaulting to privacy if missing. Team enforcement syncs every 5 minutes, with cache fallbacks assuming privacy.
  • Physical Isolation: Separate service replicas and queues for privacy/non-privacy traffic minimize cross-contamination risks. Log functions in privacy mode are no-ops unless explicitly vetted.

AI, Indexing, and Client-Side Risks

AI requests—triggered by chat, Cursor Tab suggestions, or background tasks—send code snippets and context to servers. Codebase indexing, enabled by default, uses Merkle trees to sync only changed files:

  • Obfuscation Limits: File paths are encrypted but leak directory structures. Embeddings stored in Turbopuffer could theoretically be reversed, per academic research.
  • Client Vulnerabilities: As a VS Code fork, Cursor inherits Microsoft's security advisories but diverges critically: Workspace Trust is disabled by default (avoiding confusion with privacy mode), and extension signatures aren’t verified—a acknowledged gap.

Implications for Development Teams

The disclosure underscores Cursor's enterprise readiness while highlighting caveats:
- Risk Mitigation: Use .cursorignore to block sensitive files, disable indexing, or enforce team-wide privacy mode.
- Data Control: Account deletion purges all data within 30 days (though trained models may retain historical non-privacy inputs).
- Transparency Trade-offs: The inability to direct-route AI requests to private enterprise deployments (e.g., Azure OpenAI) remains a limitation for air-gapped environments.

As AI tools become embedded in development workflows, Cursor’s blueprint sets a benchmark for operational security—not through perfection, but through auditable, engineer-centric transparency. For developers, it’s a reminder: in the age of AI, trust is built byte by encrypted byte.

Source: Cursor Security Documentation