Query-Efficient Agentic Graph Extraction Attacks on GraphRAG Systems

arXiv:2601.14662v2 Announce Type: replace Abstract: Graph-based retrieval-augmented generation (GraphRAG) systems construct knowledge graphs over document collections to support multi-hop reasoning. While prior work shows that GraphRAG responses may leak retrieved subgraphs, the feasibility of query-efficient reconstruction of the hidden graph structure remains unexplored under realistic query budgets. We study a budget-constrained black-box setting where an adversary adaptively queries the syst