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Data Security Commitment

Nebula Lab takes user data security seriously with multiple protection measures. We’re committed to providing secure, reliable AI services.

Core Security Measures

End-to-End Encryption

TLS 1.3 Encryption

All data transmission uses TLS 1.3 protocol encryption:
  • Latest encryption standard for strongest protection
  • Prevents data interception or tampering
  • End-to-end encryption from user to server

Minimal Data Storage

Relay Platform Advantage As a relay platform, Nebula Lab:
  • Doesn’t store request content: No saving of API request inputs/outputs
  • Can’t view user data: Technical team cannot access conversation content
  • Immediate deletion: Content cleared after processing
  • Privacy first: Maximum user privacy protection
As a relay platform, our job is to forward requests securely and efficiently, not store user data. This design fundamentally protects your privacy.

Limited Logging

Basic Log Scope We only log essential information for billing and troubleshooting:
  • Model name: For billing and statistics
  • Token counts: Input and output token counts
  • Timestamps: For log analysis and debugging
  • Response status: Success or error states
What we DON’T log
  • ❌ Conversation content
  • ❌ User input text
  • ❌ AI output responses
  • ❌ Images or file content
  • ❌ Personal identity information

Short-term Log Retention

Log Retention Period

Retention: Only 7 daysReasons:
  • Data security: Reduce data breach risk
  • Resource optimization: Minimize storage costs
  • Privacy protection: Minimal data retention
  • Compliance: Meet data protection regulations
After 7 days, all logs are automatically deleted and cannot be recovered.

Access Control

Strict Permission Management

Authorized Access Only
  • Least privilege: Only authorized personnel can access logs
  • Anonymization: Log data is anonymized
  • Necessity review: Access only when necessary (e.g., troubleshooting)
  • Audit trail: Complete audit logs for all access

Technical Team Management

  • Background checks: Thorough personnel vetting
  • NDAs: Strict data confidentiality agreements
  • Regular training: Data security and privacy training
  • Permission rotation: Regular access review and rotation

Security Framework

Regular Security Audits

Continuous Improvement Nebula Lab conducts regular security assessments:
  • Vulnerability scanning: Regular system security checks
  • Code review: Review potential security risks in code
  • Infrastructure checks: Server and network security evaluation
  • Process optimization: Continuous security process improvement

Compliance

Regulatory Commitment
  • Data protection laws: Strict GDPR, PIPL compliance
  • Industry standards: AI service security standards
  • Regulatory requirements: Cooperation with authorities
  • International standards: ISO 27001 reference

Security Best Practices

User Recommendations

  • Rotate API Keys regularly
  • Don’t hardcode Keys in code
  • Use environment variables for sensitive info
  • Avoid sensitive personal info in requests
  • Use anonymized data for testing
  • Handle confidential content carefully
  • Use HTTPS for API access
  • Use service in secure network environments
  • Keep client software updated

Platform Protections

  • Multi-layer defense: Multiple security measures deployed
  • Real-time monitoring: 24/7 security monitoring and threat detection
  • Incident response: Complete security incident response mechanism
  • Backup & recovery: Regular backups and disaster recovery drills

Transparency Commitment

Security Incident Notification

If a security event may affect user data, we commit to:
  • Timely notification: Within 24 hours of discovery
  • Detailed explanation: Event details and scope
  • Remediation: Steps taken to address the issue
  • Prevention: Future prevention measures

Support

For data security questions, contact us:

Technical Support

Email: mla@nebula-data.comTopics:
  • Data security policy
  • Privacy protection measures
  • Security best practices
  • Security incident reporting
We continuously improve security measures to provide safer, more reliable AI services.