The classic security triad maps onto AI systems with new twists. Confidentiality now includes the model leaking training data, system prompts, or other users' context through its outputs — not just a database breach. Integrity means the model's behavior stays as intended: no injected instructions silently changing what it does. Availability covers both classic denial-of-service and a new variant — resource-exhaustion attacks that run up your inference bill or degrade quality for everyone else.
The useful shift is realizing that 'confidential data' now includes things baked into the model itself: a system prompt is effectively a secret the model is asked to keep, and it's much easier to accidentally leak than a database credential.
NEDA replaced its human-staffed helpline with an AI chatbot named Tessa shortly before the incident came to light: the chatbot gave callers seeking help for eating disorders concrete advice about calorie restriction and weight loss — the exact opposite of appropriate guidance for that population, and a direct integrity failure, since the bot's actual behavior diverged sharply from its intended purpose. NEDA suspended the chatbot once the pattern was publicly reported, and the case became a widely cited example in AI-safety discussions of what happens when a system's behavior isn't verified to match its stated purpose before deployment in a sensitive context.