Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems

Computer Science > Cryptography and Security [Submitted on 28 May 2025 (v1), last revised 26 Jun 2026 (this version, v4)] Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems Ronny Ko, Jiseong Jeong, Shuyuan Zheng, Chuan Xiao, Tae-Wan Kim, Makoto Onizuka, Won-Yong Shin Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership. Yet, cross-domain collaboration shatters the unified trust assumptions behind current alignment and containment techniques. An agent benign in isolation may, when receiving messages from an untrusted peer, leak secrets or violate policy, producing risks driven by emergent multi-agent dynamics rather than classical software bugs. This position paper maps the security agenda for cross-domain multi-agent LLM systems. We introduce seven categories of novel security challenges, for each of which we also present plausible attacks, security evaluation metrics, and future research guidelines. Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2505.23847 [cs.CR]   (or arXiv:2505.23847v4 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2505.23847 Focus to learn more Submission history From: Ronny Ko [view email] [v1] Wed, 28 May 2025 18:19:03 UTC (600 KB) [v2] Thu, 5 Jun 2025 14:07:18 UTC (600 KB) [v3] Tue, 15 Jul 2025 16:18:29 UTC (600 KB) [v4] Fri, 26 Jun 2026 12:09:53 UTC (421 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2025-05 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)