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This paper introduces Zero-Shot Embedding Drift Detection (ZEDD), a lightweight framework that detects prompt injection attacks in LLMs by measuring semantic shifts in embedding space, achieving over 93% accuracy with less than 3% false positive rate across multiple architectures.