Pre-deployment testing is the set of security and safety checks performed before a model, system, or service is released to users. In AI and cyber security, it can include capability evaluations, adversarial red-teaming, abuse-case analysis, prompt injection checks, and review of logging, access controls, and guardrails.
This step matters because many failures are easiest to catch before launch. A model may look safe in controlled demos but still generate phishing text, assist malware development, leak sensitive data, or amplify social engineering once it is exposed to real users. Defenders use pre-deployment testing to reduce that risk, document residual issues, and decide whether release controls are strong enough. In practice, it acts as a release gate: if the system fails important tests, deployment is delayed, restricted, or redesigned before it reaches an attacker’s hands.