How are you approaching security testing for applications that heavily integrate LLM APIs?

Prompt injection is the obvious threat, but there's also data exfiltration through model outputs, context window poisoning, and the challenge of adversarial inputs that work differently across model versions. Traditional fuzzing and static analysis don't map cleanly here—what techniques are actually proving effective in your testing workflows?