A survey providing a taxonomy of TEE platforms, an agent-centric threat model, and open challenges for applying confidential computing to secure agentic AI systems.
Breaking the protocol: Security analysis of the model context protocol specification and prompt injection vulnerabilities in tool-integrated LLM agents
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.CR 3years
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UNVERDICTED 3roles
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The paper systematizes security for LLM agents in agentic commerce into five threat dimensions, identifies 12 cross-layer attack vectors, and proposes a layered defense architecture.
CASCADE is a cascaded hybrid detector that combines fast regex/entropy filtering, BGE embeddings with local LLM fallback, and output pattern checks to achieve 95.85% precision and 6.06% false-positive rate against prompt injection and related attacks in MCP-based systems.
citing papers explorer
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When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI
A survey providing a taxonomy of TEE platforms, an agent-centric threat model, and open challenges for applying confidential computing to secure agentic AI systems.
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SoK: Security of Autonomous LLM Agents in Agentic Commerce
The paper systematizes security for LLM agents in agentic commerce into five threat dimensions, identifies 12 cross-layer attack vectors, and proposes a layered defense architecture.
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CASCADE: A Cascaded Hybrid Defense Architecture for Prompt Injection Detection in MCP-Based Systems
CASCADE is a cascaded hybrid detector that combines fast regex/entropy filtering, BGE embeddings with local LLM fallback, and output pattern checks to achieve 95.85% precision and 6.06% false-positive rate against prompt injection and related attacks in MCP-based systems.