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You train a churn model. It shows 91% AUC on your held-out test set. You deploy it. It performs no better than a naive baseline. You've just been bitten by data leakage — and the root cause is almost always the same: your training features were compu...

Understanding the Risks of Prompt Injection in LLMs: A Practical Approach to Security Context and Problem The integration of Large Language Models (LLMs) into enterprise applications has become a common practice, driving innovation and boosting produ...
Introduction In the growing landscape of AI, deploying large language models (LLMs) in production has become commonplace. However, while these models offer unprecedented capabilities, they also introduce new security concerns that must be addressed i...