The Phantom Menace in Your Knowledge Base
Retrieval-Augmented Generation (RAG) may seem like a fortress of AI reliability—until you realize the breach happens at the front door, not in the model. Large Language Models (LLMs) have become the backbone of enterprise AI assistants. Yet as more systems integrate RAG pipelines to improve their factuality and domain alignment, a gaping blindspot has emerged—the document ingestion layer. A new paper titled “The Hidden Threat in Plain Text” by Castagnaro et al. warns that attackers don’t need to jailbreak your model or infiltrate your vector store. Instead, they just need to hand you a poisoned DOCX, PDF, or HTML file. And odds are, your RAG system will ingest it—invisibly. ...