Seven security challenges in cross-domain multi-agent LLM systems
Abstract
Large language models are evolving into autonomous agents that collaborate across organizations for tasks like disaster response and supply-chain optimization. However, such cooperation breaks unified trust assumptions: a benign agent may leak secrets or violate policy when interacting with untrusted peers. This paper maps the security agenda for cross-domain multi-agent LLM systems, introducing seven categories of novel challenges alongside plausible attacks, evaluation metrics, and research directions.
Fields of Study & Subjects
Adversarial Robustness in Machine Learning
Blockchain Technology Applications and Security
Spam and Phishing Detection
Publication details
- Journal / source
- npj Artificial Intelligence
- Publisher
- Springer Science and Business Media LLC
- Volume
- 2
- Issue
- 1
- Publication date
- 13 June 2026
- Language
- EN