This paper analyzes the security vulnerabilities of the Model Context Protocol (MCP), identifying tool poisoning as the most critical client-side threat, and proposes a multi-layered defense strategy.

This paper introduces a component-centric framework and a novel detector, Connor, to understand and detect sophisticated, multi-component attacks targeting the Model Context Protocol (MCP) servers.

The paper introduces mcp-sec-audit, a comprehensive toolkit that assesses Model Context Protocol (MCP) servers for over-privileged and insecure tool capabilities.

The paper introduces a defense-placement taxonomy for the Model Context Protocol (MCP) to systematically analyze security gaps, revealing that many vulnerabilities stem from architectural misalignment…

The paper introduces MCP Pitfall Lab, a comprehensive security testing framework that rigorously assesses and validates developer pitfalls in Model Context Protocol (MCP) tool servers under realistic…

This paper investigates Description-Code Inconsistency (DCI) in Model Context Protocol (MCP) servers, finding that 9.93% of real-world tools exhibit inconsistencies that create security blind spots.

This study provides the first measurement of authentication security in real-world remote Model Context Protocol (MCP) servers, finding pervasive and critical authentication weaknesses, particularly i…

The paper introduces MCPSHIELD, a comprehensive formal security framework that systematically characterizes and provides a defense-in-depth architecture for the rapidly adopted but insecure Model Cont…

VIPER-MCP is a novel, end-to-end automated framework that detects and dynamically confirms the exploitability of taint-style vulnerabilities in Model Context Protocol (MCP) servers, achieving high-fid…

enclawed is a configurable, hard-fork hardening framework for AI assistant gateways that enforces strict security controls, verifiable trust, and auditable connectivity for regulated environments.

The paper introduces AIP, a novel protocol using Invocation-Bound Capability Tokens (IBCTs) to provide verifiable identity and secure delegation across Model Context Protocol (MCP) and Agent-to-Agent…

The Device Context Protocol (DCP) introduces a compact, safety-first communication standard designed to allow LLMs to reliably control resource-constrained physical microcontrollers, significantly imp…

This paper introduces a new benchmark to test Tool Description Poisoning (TDP) attacks on LLM agents, demonstrating that even advanced models like GPT-4o are highly vulnerable and that current defense…

The paper proposes an architectural proxy (MCP) to enforce robust, reliable tool access control for LLM agents, demonstrating that this structural enforcement is necessary because prompt-based restric…

SecureMCP proposes a novel, policy-enforced framework that integrates Role-Based Access Control (RBAC) with an MCP server to provide multi-layer, fine-grained defense against malicious LLM-generated S…

This paper introduces MCP-38, a novel, protocol-specific threat taxonomy of 38 categories designed to address critical, unaddressed attack surfaces within the Model Context Protocol (MCP) system.

The paper identifies Mid-Session Tool Injection (MSTI) as a novel threat in the WebMCP protocol, demonstrating that attackers can manipulate the visible or perceived set of tools available to AI agent…

The paper introduces AgentSecBench, a security evaluation framework that measures prompt injection, privacy leakage, and tool-use integrity in LLM agents by defining formal security games and testing…

The paper proposes a graph-based framework for detecting attacks in LLM agent tool-call traffic, finding that content-level embeddings are crucial for high accuracy and that tree ensembles on these em…

This paper develops and evaluates supervised machine learning models to detect malicious tool descriptions within the Model Context Protocol (MCP), achieving high detection rates in both binary and mu…