Fictional data is for testing—not deception.

• Software development and quality assurance
• Interface prototypes and product demonstrations
• Automated tests, sample databases, and training exercises
• Testing imports, exports, validation, and formatting

• Fraud, impersonation, identity verification, or account abuse
• Harassment, spam, evasion, or deceptive campaigns
• Creating documents or records intended to appear officially valid
• Attempting to identify, contact, or harm real people

Synthetic combinations may occasionally resemble real people by coincidence. Treat every generated profile as fictional, avoid combining it with real personal data, and remove any record that could create confusion.

Check generated datasets before adding them to screenshots, repositories, demonstrations, or training material. Keep the fictional context clear, remove values that could be misunderstood, and avoid using generated information in workflows that contact people or create real accounts.

Synthetic records reduce reliance on personal information, but they do not make an insecure environment safe. Limit access to test systems, protect credentials, remove unnecessary exports, and keep generated records separate from production customer data.