Agentic AI Defense: Decode-Time Provenance Binding for MCP

Reported by arXiv cs.CR (Eric Yocam, Varghese Vaidyan, Paris Kalathas, Patrick Tague, Bruce DeBruhl, Yong Wang)

Summary by Cyber Security News26 Oct 2026, 05:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.31974

arXiv:2610.31974v1 Announce Type: new Abstract: Agentic AI systems using the Model Context Protocol (MCP) are vulnerable to indirect prompt injection through untrusted tool outputs. We demonstrate cross-modal trust laundering, in which instructions concealed in an email-signature image using least-significant-bit (LSB), discrete cosine transform (DCT), or metadata steganography bypass text scanners and enter a multi-agent workflow when decoded by a tool.

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