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Securing GenAI Multi-Agent Systems Against Tool Squatting: A Zero Trust Registry-Based Approach

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arxiv 2504.19951 v1 pith:NKMAAHKB submitted 2025-04-28 cs.CR cs.AI

classification cs.CRcs.AI
keywords toolsquattinggenaimulti-agentprotocolsregistrysystemsagents
verification ladder T0 review T1 audit T2 compute T3 formal
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The rise of generative AI (GenAI) multi-agent systems (MAS) necessitates standardized protocols enabling agents to discover and interact with external tools. However, these protocols introduce new security challenges, particularly; tool squatting; the deceptive registration or representation of tools. This paper analyzes tool squatting threats within the context of emerging interoperability standards, such as Model Context Protocol (MCP) or seamless communication between agents protocols. It introduces a comprehensive Tool Registry system designed to mitigate these risks. We propose a security-focused architecture featuring admin-controlled registration, centralized tool discovery, fine grained access policies enforced via dedicated Agent and Tool Registry services, a dynamic trust scoring mechanism based on tool versioning and known vulnerabilities, and just in time credential provisioning. Based on its design principles, the proposed registry framework aims to effectively prevent common tool squatting vectors while preserving the flexibility and power of multi-agent systems. This work addresses a critical security gap in the rapidly evolving GenAI ecosystem and provides a foundation for secure tool integration in production environments.

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Cited by 8 Pith papers

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

  1. Combating Data Laundering in LLM Training

    cs.CR 2026-04 conditional novelty 6.0 of 10

    Data laundering collapses original-query memorization detectors; SDR recovers useful detection signals by synthesizing training-like rewrites of proprietary data via a goal-details search.

  2. ETDI: Mitigating Tool Squatting and Rug Pull Attacks in Model Context Protocol (MCP) by using OAuth-Enhanced Tool Definitions and Policy-Based Access Control

    cs.CR 2025-06 conditional novelty 5.0 of 10

    ETDI is a proposed MCP security extension that adds signed, versioned tool definitions, OAuth-based permissions, and runtime policy checks to stop tool impersonation and post-approval tool changes.

  3. Detailed analysis of possible new-physics effects in the semileptonic decay $B_s \to D_s^{(*)}\tau\bar{\nu}$

    hep-ph 2026-03 unverdicted novelty 4.0 of 10

    Constraints on beyond-SM Wilson coefficients in B_s → D_s(*) τ ν̄ are derived from data using covariant-quark-model form factors, with full observable predictions for future experiments.

  4. Quantifying Conversation Drift in MCP via Latent Polytope

    cs.CL 2025-08 reject novelty 4.0 of 10

    SecMCP flags MCP conversation drift by thresholding per-layer activation distances from benign anchors, reporting AUROC above 0.915 on Llama3, Vicuna, and Mistral.

  5. Agent Capability Negotiation and Binding Protocol (ACNBP)

    cs.AI 2025-06 reject novelty 4.0 of 10

    ACNBP is a proposed standard for secure agent capability negotiation with an extension mechanism, but it lacks formal verification, experiments, and independent evaluation.

  6. COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents

    cs.AI 2025-06 reject novelty 4.0 of 10

    COALESCE, a framework for skill-based task outsourcing among LLM agents, claims 41.8% simulated and 20.3% real cost reductions, but the validation contains internal contradictions.

  7. A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control

    cs.CR 2025-05 conditional novelty 4.0 of 10

    The authors propose a zero-trust identity and access management framework for AI agents that combines decentralized identifiers, verifiable credentials, a capability-aware naming service, and a global session revocati...

  8. The Age of Sensorial Zero Trust: Why We Can No Longer Trust Our Senses

    cs.CR 2025-07 unverdicted novelty 3.0 of 10

    A position paper argues that organizations should apply Zero Trust verification principles to human sensory perception to defend against deepfake and voice-clone fraud.

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