defense-framework

RAGuard is a layered defense framework for Retrieval-Augmented Generation (RAG) systems that uses adversarial fine-tuning of the retriever and a label-free filter (ZKIP) to achieve zero attack success against corpus poisoning, maintaining high retrieval accuracy.

This paper presents MIPIAD, a multilingual defense framework against indirect prompt injection attacks using a hybrid of Qwen2.5-based classifiers and TF-IDF features with meta-ensemble learning. It demonstrates strong performance on English and Bangla benchmarks, achieving high F1 and AUROC scores while reducing cross-lingual gaps.