atlas

Research map / Multi-agent systems and games / LLM agents

MCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents

NeurIPS 2026 · Multi-agent systems and games › LLM agents · approach: Agent safety and attack benchmarks · 0 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's full text. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Introduces MCPHunt, a canary-based benchmark measuring non-adversarial cross-boundary credential propagation in multi-server MCP agents across 5 models, 147 tasks, and 9 mechanism families.

Problem

Multi-server MCP agents can propagate credentials across trust boundaries during faithful, non-adversarial task execution, yet no benchmark measures this compositional data-propagation risk.

Approach

Canary-based taint tracking with format-authentic secrets reduces propagation detection to string matching; environment-controlled risky/benign/hard-negative conditions and CRS stratification separate task-mandated transfer from policy-violating propagation.

Key results

Surprising findings

Limitations

Experimental setup

Datasets: 147 researcher-designed MCP tasks

Benchmarks: MCPHunt

Metrics: policy-violating propagation rate propagation rate utility rate Wilson 95% CI Cohen's kappa

Baselines: MCP-SafetyBench MCPSecBench MSB TOP-Bench AgentLeak

Builds on: Model Context Protocol TOP-Bench NeMo Guardrails

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy