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Achilles Heel of Distributed Multi-Agent Systems

Yiting Zhang, Yijiang Li, Tianwei Zhao, Kaijie Zhu, Haohan Wang, Nuno Vasconcelos

TL;DR

The paper tackles trustworthiness in Distributed Multi-Agent Systems (DMAS), where heterogeneous third-party LLM-backed agents are remotely hosted and coordinated by a central controller. It systematically analyzes four core challenges—free ride, malicious attacks, communication delay, and unstable connections—and validates their impact through experiments across seven frameworks and four tasks, observing up to an 80% performance drop and 100% attack success in certain scenarios. The findings underscore significant reliability and security vulnerabilities in DMAS and position the work as a red-teaming tool to guide secure design and further research. The study highlights the need for robust defenses, resilient exception handling, and architecture-aware mitigation strategies to enable practical, trustworthy distributed agent ecosystems.

Abstract

Multi-agent system (MAS) has demonstrated exceptional capabilities in addressing complex challenges, largely due to the integration of multiple large language models (LLMs). However, the heterogeneity of LLMs, the scalability of quantities of LLMs, and local computational constraints pose significant challenges to hosting these models locally. To address these issues, we propose a new framework termed Distributed Multi-Agent System (DMAS). In DMAS, heterogeneous third-party agents function as service providers managed remotely by a central MAS server and each agent offers its services through API interfaces. However, the distributed nature of DMAS introduces several concerns about trustworthiness. In this paper, we study the Achilles heel of distributed multi-agent systems, identifying four critical trustworthiness challenges: free riding, susceptibility to malicious attacks, communication inefficiencies, and system instability. Extensive experiments across seven frameworks and four datasets reveal significant vulnerabilities of the DMAS. These attack strategies can lead to a performance degradation of up to 80% and attain a 100% success rate in executing free riding and malicious attacks. We envision our work will serve as a useful red-teaming tool for evaluating future multi-agent systems and spark further research on trustworthiness challenges in distributed multi-agent systems.

Achilles Heel of Distributed Multi-Agent Systems

TL;DR

The paper tackles trustworthiness in Distributed Multi-Agent Systems (DMAS), where heterogeneous third-party LLM-backed agents are remotely hosted and coordinated by a central controller. It systematically analyzes four core challenges—free ride, malicious attacks, communication delay, and unstable connections—and validates their impact through experiments across seven frameworks and four tasks, observing up to an 80% performance drop and 100% attack success in certain scenarios. The findings underscore significant reliability and security vulnerabilities in DMAS and position the work as a red-teaming tool to guide secure design and further research. The study highlights the need for robust defenses, resilient exception handling, and architecture-aware mitigation strategies to enable practical, trustworthy distributed agent ecosystems.

Abstract

Multi-agent system (MAS) has demonstrated exceptional capabilities in addressing complex challenges, largely due to the integration of multiple large language models (LLMs). However, the heterogeneity of LLMs, the scalability of quantities of LLMs, and local computational constraints pose significant challenges to hosting these models locally. To address these issues, we propose a new framework termed Distributed Multi-Agent System (DMAS). In DMAS, heterogeneous third-party agents function as service providers managed remotely by a central MAS server and each agent offers its services through API interfaces. However, the distributed nature of DMAS introduces several concerns about trustworthiness. In this paper, we study the Achilles heel of distributed multi-agent systems, identifying four critical trustworthiness challenges: free riding, susceptibility to malicious attacks, communication inefficiencies, and system instability. Extensive experiments across seven frameworks and four datasets reveal significant vulnerabilities of the DMAS. These attack strategies can lead to a performance degradation of up to 80% and attain a 100% success rate in executing free riding and malicious attacks. We envision our work will serve as a useful red-teaming tool for evaluating future multi-agent systems and spark further research on trustworthiness challenges in distributed multi-agent systems.

Paper Structure

This paper contains 29 sections, 22 figures, 10 tables.

Table of Contents

  1. Introduction
  2. Trustworthiness Challenges in Distributed Multi-Agent Systems
  3. Free Ride
  4. Malicious Attacks
  5. Communication Delay
  6. Unstable Connection
  7. Experiments
  8. Settings
  9. Analysis on Experimental Results
  10. Free Ride
  11. Malicious Attack
  12. Communication Delay
  13. Unstable Connection
  14. Related Works
  15. Multi-Agent Systems
  16. ...and 14 more sections

Figures (22)

  • Figure 1: Distributed multi-agent system with third-party agents hosted on different servers connected and managed by the control system.
  • Figure 2: Overview of trustworthiness challenges of distributed multi-agent systems.
  • Figure 3: Task performance of different frameworks under free ride in code generation task.
  • Figure 4: Task performance of different frameworks under free ride in mathematical reasoning task.
  • Figure 5: Task performance of different frameworks under free ride in general reasoning task.
  • ...and 17 more figures