arXiv AI By Mehrdad Rostamzadeh, Sidhant Narula, Mohammad Ghasemigol, Daniel Takabi

TrustShiftProbe: Characterizing, Benchmarking, and Defending Staged Trust Attacks on MCP Servers

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The paper introduces TrustShiftProbe, a framework that characterizes and defends against staged trust attacks on Model Context Protocol (MCP) servers. It defines a temporal threat model where a compromised server behaves benignly during conditioning and later delivers adversarial payloads, and presents a multi‑tier runtime defense called SHIELD that reduces attack success from 69.5% to 42.7%. The work also provides a taxonomy of nine TrustShift variants across different execution mechanisms and objectives.

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