Securing Multi-Agent GIS Systems: Risk Evaluation and Prompt Hardening Optimization

Computer Science > Cryptography and Security [Submitted on 13 Jun 2026] Securing Multi-Agent GIS Systems: Risk Evaluation and Prompt Hardening Optimization Kyle Gao, Pranavi Kotta, Linlin Xu, Jonathan Li, David A. Clausi Agentic systems are increasingly integrated with geographic information systems (GIS), where multi-agent coordination enables complex conversational and spatial analysis but introduces security risks. This work presents a security-oriented framework for risk identification, evaluation, and mitigation in a multi-agent GIS system while maintaining adaptability to broader agentic architectures. We test the agentic system of a commercial geospatial partner while developing a modular state-machine-based orchestration framework that abstracts agent behavior into reusable components. We evaluate robustness using a red-teaming framework with an adaptive attacker LLM and a deterministic judge that produces binary outcomes with supporting rationales across multi-turn attacks. We further improve resilience with a prompt optimization framework that treats prompts as structured signatures and injects adversarial demonstrations, enabling systematic security improvements without degrading task performance. Comments: Kyle Gao and Pranavi Kotta contributed equally to this work Subjects: Cryptography and Security (cs.CR); Computation and Language (cs.CL) Cite as: arXiv:2606.17092 [cs.CR]   (or arXiv:2606.17092v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.17092 Focus to learn more Submission history From: Kyle Gao [view email] [v1] Sat, 13 Jun 2026 03:15:30 UTC (181 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.CL 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?)