Template theft is the unauthorized copying of stored biometric templates, such as face vectors, fingerprint patterns, or iris records. A template is not the raw image itself; it is the mathematical data a system uses to compare and verify identity. If attackers steal that data, they may be able to replay it, clone it, or use it to build convincing fraudulent identities.
In cyber security, template theft is serious because biometrics are hard to change. A password can be reset, but a compromised face or fingerprint template may remain useful for years. Attacks often target poorly protected databases, insecure backups, or devices that store templates without strong encryption or access control. Defenses include least-privilege access, encryption at rest and in transit, hardware-backed key storage, logging, and template protection schemes that make stolen data harder to reuse. In border and access-control systems, template theft can undermine both identity verification and trust in automated screening.