Securing Multi-Agent GIS Systems: Risk Evaluation and Prompt Hardening Optimization
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Computer Science > Cryptography and Security
Title:Securing Multi-Agent GIS Systems: Risk Evaluation and Prompt Hardening Optimization
Abstract: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
arXiv-issued DOI via DataCite
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