Cursor Enterprise Security: AI-Optimized Reference

Critical Version Requirements

MINIMUM VERSION: 1.3 or higher (July 2025+)

• FAILURE RISK: Earlier versions contain critical remote code execution vulnerabilities
• IMPACT: Complete machine compromise via malicious repositories
• URGENCY: Immediate security risk - update before deployment

Security Vulnerabilities (Patched)

CVE-2025-54135 "CurXecute" - Remote Code Execution

• ATTACK VECTOR: Malicious .cursor-mcp files in GitHub repositories
• IMPACT: Arbitrary code execution when opening crafted repositories
• PATCH STATUS: Fixed in v1.3 with MCP server validation and user consent prompts
• PREVENTION: Corporate firewall rules blocking unknown MCP servers

CVE-2025-54136 "MCPoison" - Persistent Code Execution

• ATTACK VECTOR: Bypassed MCP trust mechanisms maintaining persistence
• IMPACT: Long-term machine compromise, data exfiltration, supply chain attacks
• PERSISTENCE: Survives session restarts and project changes
• PATCH STATUS: Fixed in v1.3

Enterprise Configuration Requirements

Network Whitelist (Required Domains)

# Core API endpoints
api2.cursor.sh      # Main API requests
api3.cursor.sh      # Cursor Tab completions (HTTP/2 REQUIRED)
repo42.cursor.sh    # Codebase indexing (HTTP/2 REQUIRED)

# Regional endpoints
api4.cursor.sh
us-asia.gcpp.cursor.sh
us-eu.gcpp.cursor.sh
us-only.gcpp.cursor.sh

# Updates and extensions
marketplace.cursorapi.com
cursor-cdn.com
downloads.cursor.com
anysphere-binaries.s3.us-east-1.amazonaws.com

CRITICAL: HTTP/2 support required for core features. Legacy proxies will cause silent failures.

Bandwidth Planning

• Per developer per day: ~500MB during heavy usage
• Cursor Tab completions: ~50KB per minute per active developer
• Codebase indexing: 10-100MB initial sync, then incremental
• Chat requests: 1-5MB per complex conversation
• Background agents: 5-20MB per automated task
• SPIKE RISK: Initial rollout can cause 10x normal traffic

Privacy Mode Implementation

Architectural Enforcement

• INFRASTRUCTURE: Physically separate servers for privacy mode
• HEADER CHECK: x-ghost-mode header routes to isolated infrastructure
• DATA RETENTION: Zero retention with model providers when enabled
• PROPAGATION TIME: <30 seconds for team-level policy changes
• FAILSAFE: Defaults to privacy mode when in doubt

Privacy Mode Limitations

DOES NOT PROTECT AGAINST:

• Local machine compromises
• Malicious VS Code extensions
• Network interception (use HTTPS)
• Cursor client vulnerabilities

SOC 2 Compliance Coverage

COVERED

• Security controls for cloud data processing
• Availability guarantees
• Processing integrity of AI requests
• Privacy controls for user data

NOT COVERED

• Local machine security
• Third-party model provider compliance
• VS Code extension marketplace
• Local file access permissions
• AI-generated code security

Deployment Anti-Patterns

"Shadow IT" Rollout (AVOID)

FAILURE POINTS:

• No centralized privacy controls
• Budget surprises from usage-based billing
• Compliance audit failures
• Accidental commit of AI-suggested secrets

Successful "Pilot Program" Pattern

REQUIREMENTS:

• 20-30 senior developers maximum
• Team-level Privacy Mode enforced from day one
• Complete firewall configuration before start
• Usage monitoring for cost patterns
• Security training on AI coding risks
• Clear incident escalation procedures

Cost Management

Pricing Model (Post-August 2025)

• BUDGET ESTIMATE: $40-60 per developer per month for heavy usage
• SPIKE RISK: Background Agents can cost $50+ per day per developer
• MONITORING: Usage stats shown at 50% quota consumption
• CONTROLS: Hard spending limits available via admin API

Cost Control Strategies

• Set hard limits to prevent budget surprises
• Monitor usage patterns during rollout (expect 2-3x normal usage initially)
• Restrict expensive models (GPT-5) for cost control
• Train developers on efficient AI usage patterns

Security Monitoring Gaps

BLIND SPOTS (No Built-in Detection):

• Code exfiltration via AI chat
• Abnormal usage pattern detection
• Data classification integration
• Sensitive code paste alerts
• Incident forensic capabilities

REQUIRED ADDITIONAL CONTROLS:

• Data Loss Prevention (DLP) systems
• Custom usage anomaly detection
• Code classification enforcement
• Comprehensive audit logging

Tiered Security Model

Tier 1 - Public/Open Source Code

• Standard Cursor with all features enabled
• Normal usage tracking only

Tier 2 - Internal Business Logic

• Privacy Mode enforced
• Codebase indexing disabled for sensitive repos
• Background Agents restricted to approved tasks

Tier 3 - Regulated/Classified Code

• NO CURSOR USAGE PERMITTED
• Air-gapped development environments required

Critical Decision Factors

Enterprise Readiness Assessment

READY FOR DEPLOYMENT:

• SOC 2 Type II certified
• Critical CVEs patched (v1.3+)
• Privacy Mode architectural enforcement
• Enterprise SSO integration available

DEPLOYMENT BLOCKERS:

• No on-premises/air-gapped deployment option
• Limited audit logging capabilities
• Extension security risks
• Vendor risk (startup with uncertain future)

vs GitHub Copilot Comparison

Factor	Cursor	GitHub Copilot	Impact
Privacy Mode	Zero data retention	Data used for training	Critical for sensitive code
On-Premises	Not available	Available (Enterprise Server)	Dealbreaker for air-gapped environments
Recent CVEs	RCE vulnerabilities (patched)	No recent critical issues	Temporary security disadvantage
Vendor Risk	Startup, uncertain future	Microsoft-backed	Long-term sustainability concern
Network Complexity	Multiple endpoints, HTTP/2 required	Simpler configuration	Higher operational overhead

Implementation Checklist

Pre-Deployment (Required)

• Verify Cursor version 1.3+ across all installations
• Configure corporate firewall with all required domains
• Verify HTTP/2 support in corporate proxy
• Enable team-level Privacy Mode enforcement
• Set up usage monitoring and cost alerts
• Configure SSO integration
• Define data classification tiers
• Establish incident response procedures

Security Controls (Critical)

• Block unknown MCP servers at firewall level
• Implement extension allowlist management
• Set up additional DLP monitoring
• Configure spending limits and alerts
• Train developers on AI security risks
• Establish code review processes for AI-generated code

Resource Requirements

Technical Expertise Needed

• NETWORK ADMIN: Firewall configuration and HTTP/2 proxy setup
• SECURITY TEAM: Privacy mode validation and incident response
• DEVELOPER TRAINING: 2-4 hours on secure AI coding practices
• ONGOING MONITORING: Dedicated security analyst time for usage pattern review

Time Investment

• INITIAL SETUP: 2-3 weeks for complete enterprise configuration
• PILOT PROGRAM: 4-6 weeks with 20-30 developers
• FULL ROLLOUT: 8-12 weeks depending on organization size
• SECURITY REVIEW: 40-60 hours for complete risk assessment