Maosen Zhang, Jianshuo Dong, Yutong Zhang, Jie Zhang, Tianwei Zhang, Han Qiu · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.27574 · cited by 0 works (OpenAlex) · open-access PDF
Multi-agent systems are increasingly deployed to coordinate multiple large language model (LLM) agents. However, this also creates new attack surfaces: malicious agents may have chances to exploit the coordination. In this paper, we propose and study the \textit{show-up attack}, in which a malicious subagent manipulates the supervisor into involving it in tasks beyond its assigned scope. To evaluate this risk, we propose SUA-Arena, which implements 6 attack strategies and contains 188 test cases. Then, we evaluate 6 frontier LLMs and find that all of them are vulnerable to show-up attacks. For example, GPT-5.6-Sol as a supervisor suffers an ASR of up to 0.93. Mitigation strategies such as prompting and restricted communication fail to reduce the risk consistently. These results show that multi-agent systems need explicit mechanisms for enforcing authority boundaries.
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Topics: Supervisor, Exploit, Computer security, Computer science, Test (biology), Key (lock)
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