Teach engineers how AI changes secure development, including generated-code trust, prompt leakage, vulnerable patterns, and review discipline.

Cover practical secure design, authentication, authorization, input handling, data protection, API safety, and dependency hygiene.

Use guided labs and realistic examples so teams can identify, exploit, and fix common vulnerabilities themselves.

Adapt modules to your stack, maturity, and internal syllabus so the training lands directly in day-to-day engineering work.