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Leaking is one of the sneakiest risks in AI systems because it often happens without anyone realizing it. In this lesson, you’ll learn the two major types of leakage (prompt leaking vs data leaking), why they matter for real AI products, and how “harmless” interactions can accidentally expose system prompts or even (in rare cases) training data. This is a core concept for anyone using AI copilots, agents, or chatbots - because leaks can destroy a company’s moat, expose private logic, and create serious security incidents. What you’ll learn: What leaking means in LLM security (unintentional disclosure) Prompt leaking: how system instructions can be exposed (often via prompt injection) Why system prompts are often the “secret sauce” for startups and AI products Data leaking: when models reveal pieces of their training data under certain conditions The “lossy compression” idea—and why training data extraction is surprising Why this is a big deal for safety, privacy, and deployment