AEGIS: Real-Time Latent-Space Backdoor Detection for Dependable and Secure Small Language Model Inference

Summary

AEGIS is a non-invasive runtime framework that detects backdoor-induced anomalies in transformer hidden states without retraining the protected model. It monitors equidistant internal layers, compresses their pooled activations into a 64-dimensional latent space, and flags inputs by cosine distance from a clean-data centroid. Across Mistral-7B, Qwen2.5-7B, a QLoRA-backdoored Qwen2.5-1.5B and a BadNets-backdoored Vision Transformer, it reports AUROC values of 0.95 to 1.00 and prefill detection latency of 0.47 to 2.40 ms.

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