MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents
Haonan Li, Tianjun Sun, Yongqing Wang, Qisheng Zhang

TL;DR
MCPHunt is a benchmark framework that detects and analyzes credential propagation across multi-server MCP trust boundaries, revealing significant policy violations and aiding in prompt-level mitigation strategies.
Contribution
It introduces a controlled environment with novel detection and stratification methods to isolate and study non-adversarial credential propagation in multi-server MCP systems.
Findings
Policy-violating propagation rates reach up to 41.3% across models.
Propagation is pathway-specific and concentrated in browser-mediated data flows.
Prompt mitigation reduces policy violations by up to 97%, with some utility loss.
Abstract
Multi-server MCP agents create an information-flow control problem: faithful tool composition can turn individually benign read/write permissions into cross-boundary credential propagation -- a structural side effect of workflow topology, not necessarily malicious model behavior. We present MCPHunt, to our knowledge the first controlled benchmark that isolates non-adversarial, verbatim credential propagation across multi-server MCP trust boundaries, with three methodological contributions: (1) canary-based taint tracking that reduces propagation detection to objective string matching; (2) an environment-controlled coverage design with risky, benign, and hard-negative conditions that validates pipeline soundness and controls for credential-format confounds; (3) CRS stratification that disentangles task-mandated propagation (faithful execution of verbatim-transfer instructions) from…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
