Securing the Tool Layer: A Threat Taxonomy and Runtime Defense Framework for Model Context Protocol Deployments

Saurabh Yergattikar


Abstract
The Model Context Protocol (MCP) has rapidly emerged as the dominant standard for connecting large language models to external tools, databases, and services. Yet this convenience introduces a fundamentally new attack surface that existing LLM safety measures fail to address: adversaries can now compromise AI agents not through the user prompt, but through the tools the agent trusts. We present ShieldMCP, a runtime security framework grounded in two contributions. First, we introduce a structured threat taxonomy derived from analysis of 80+ attack techniques catalogued under the SAFE-MCP initiative within the Linux Foundation’s OpenSSF, spanning 14 tactical categories adapted from the MITRE ATT CK methodology. Second, we describe an interception architecture that performs real-time validation of MCP tool calls and responses, combining structural analysis with semantic intent verification to detect tool poisoning, indirect prompt injection through tool outputs, and supply chain manipulation. In red-team evaluation across five popular LLM backends, ShieldMCP reduces attack success rates from 74% to under 9% for tool poisoning and from 47% to under 6% for indirect prompt injection via tool responses, while adding fewer than 120ms of median latency per tool call. We discuss deployment considerations, the tension between security and agent utility, and lessons applicable to any organization integrating MCP into production workflows. Our framework is categorized as an Emerging system intended for real-world deployment.
Anthology ID:
2026.acl-industry.58
Volume:
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026)
Month:
July
Year:
2026
Address:
San Diego, California, USA
Editors:
Yunyao Li, Georg Rehm, Mei Tu
Venue:
ACL
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Publisher:
Association for Computational Linguistics
Note:
Pages:
865–871
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URL:
https://preview.aclanthology.org/ingest-acl/2026.acl-industry.58/
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Cite (ACL):
Saurabh Yergattikar. 2026. Securing the Tool Layer: A Threat Taxonomy and Runtime Defense Framework for Model Context Protocol Deployments. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), pages 865–871, San Diego, California, USA. Association for Computational Linguistics.
Cite (Informal):
Securing the Tool Layer: A Threat Taxonomy and Runtime Defense Framework for Model Context Protocol Deployments (Yergattikar, ACL 2026)
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https://preview.aclanthology.org/ingest-acl/2026.acl-industry.58.pdf