AI RESEARCH
GraphSteal: Structural Knowledge Stealing from Graph RAG via Traversal Reconstruction
arXiv CS.CL
•
ArXi:2605.28645v1 Announce Type: cross Retrieval-Augmented Generation (RAG) enhances LLMs by grounding generation in query-relevant external evidence. Beyond unstructured text corpora, Graph RAG integrates knowledge graphs into the retrieval pipeline, enabling LLMs to access entities, relations, and multi-hop dependencies encoded in structured knowledge. However, the same structured knowledge that empowers Graph RAG also creates a new privacy attack surface.