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arxiv 2504.12757 v2 pith:IL5J6XVN submitted 2025-04-17 cs.CR cs.AI

MCP Guardian: A Security-First Layer for Safeguarding MCP-Based AI System

Sonu Kumar , Anubhav Girdhar , Ritesh Patil , Divyansh Tripathi This is my paper
classification cs.CR cs.AI
keywords dataguardianapproachhowevermcp-basedmodelserversaccess
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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As Agentic AI gain mainstream adoption, the industry invests heavily in model capabilities, achieving rapid leaps in reasoning and quality. However, these systems remain largely confined to data silos, and each new integration requires custom logic that is difficult to scale. The Model Context Protocol (MCP) addresses this challenge by defining a universal, open standard for securely connecting AI-based applications (MCP clients) to data sources (MCP servers). However, the flexibility of the MCP introduces new risks, including malicious tool servers and compromised data integrity. We present MCP Guardian, a framework that strengthens MCP-based communication with authentication, rate-limiting, logging, tracing, and Web Application Firewall (WAF) scanning. Through real-world scenarios and empirical testing, we demonstrate how MCP Guardian effectively mitigates attacks and ensures robust oversight with minimal overheads. Our approach fosters secure, scalable data access for AI assistants, underscoring the importance of a defense-in-depth approach that enables safer and more transparent innovation in AI-driven environments.

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Cited by 11 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Parasites in the Toolchain: A Large-Scale Analysis of Attacks on the MCP Ecosystem

    cs.CR 2025-09 unverdicted novelty 8.0

    This paper defines a new Parasitic Toolchain Attack pattern (MCP-UPD) that assembles legitimate tools into privacy-exfiltrating workflows and reports the first large-scale scan of 12230 MCP tools across 1360 servers r...

  2. Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers

    cs.SE 2025-06 conditional novelty 8.0

    First study of 1,899 MCP servers finds eight distinct vulnerabilities (only three traditional), 7.2% with general issues, 5.5% with tool poisoning, and 66% with code smells, urging MCP-specific security practices.

  3. ShareLock: A Stealthy Multi-Tool Threshold Poisoning Attack Against MCP

    cs.CR 2026-06 unverdicted novelty 7.0

    ShareLock applies Shamir's threshold scheme to distribute poisoning payloads across multiple MCP tool descriptions, achieving information-theoretic secrecy and over 90% average attack success rate in multi-tool scenarios.

  4. "What Happens Locally, Leaks Globally": Detecting Privacy Leakage Risks in MCP Servers

    cs.CR 2026-06 unverdicted novelty 7.0

    MCPPrivacyDetector applies cross-language taint analysis to detect protocol-induced privacy leaks in MCP servers, reporting >10% leakage rate across 10,655 real-world instances.

  5. From Component Manipulation to System Compromise: Understanding and Detecting Malicious MCP Servers

    cs.CR 2026-04 unverdicted novelty 7.0

    Presents a component-centric PoC dataset of malicious MCP servers and a two-stage behavioral deviation detector Connor achieving 94.6% F1-score.

  6. AgentBound: Securing Execution Boundaries of AI Agents

    cs.CR 2025-10 conditional novelty 7.0

    AgentBound is the first declarative access control framework for Model Context Protocol servers that generates policies from source code at 80.9% accuracy and blocks most threats in malicious servers with negligible overhead.

  7. Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions

    cs.CR 2025-03 unverdicted novelty 7.0

    MCP lifecycle is defined with four phases and 16 activities; a threat taxonomy of 16 scenarios is constructed, validated via case studies, and paired with phase-specific safeguards.

  8. Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions

    cs.CR 2026-07 conditional novelty 6.0

    SPELLSMITH mitigates taint-style vulnerabilities in MCP servers by augmenting tool descriptions with security constraints and adding LLM self-reflection before tool invocation, reducing attack success rates to near zero.

  9. Unsafe by Flow: Uncovering Bidirectional Data-Flow Risks in MCP Ecosystem

    cs.SE 2026-05 unverdicted novelty 6.0

    MCP-BiFlow detects 93.8% of known bidirectional data-flow vulnerabilities in MCP servers and identifies 118 confirmed issues across 87 real-world servers from a scan of 15,452 repositories.

  10. Semantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulation

    cs.CR 2025-12 unverdicted novelty 6.0

    Descriptor-level manipulation in the Model Context Protocol can drive LLMs to unsafe tool selections in up to 36% of cases; a layered defense of integrity checks, auxiliary-LLM vetting, and runtime guardrails reduces ...

  11. CASCADE: A Cascaded Hybrid Defense Architecture for Prompt Injection Detection in MCP-Based Systems

    cs.CR 2026-04 unverdicted novelty 4.0

    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 pro...