Data Leakage Through AI — What Your LLM Knows
Training data exposure, context window leaks, PII handling, and protecting sensitive data in AI applications
Every time you send data to an AI model, you're making a trust decision. You're trusting that the data you send won't be stored, won't be used for training, won't appear in someone else's conversation, and won't be extracted through clever prompting.
That's a lot of trust. And the boundaries of what's safe to share with AI systems are murkier than most developers realize.
Data leakage through AI happens in three ways: through the training data (what the model already knows), through the context window (what you tell the model during your session), and through the output (what the model reveals in its responses). Each vector requires different defenses.
Training Data Exposure
LLMs are trained on massive datasets. Those datasets contain code from GitHub, text from the web, books, art
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