This research identifies critical security vulnerabilities in federated large language models used for military collaboration, along with defensive strategies to protect allied forces.

• Data sovereignty threats: Prompt injections can lead to unauthorized access to classified information across allied nations
• Operational disruption risks: Malicious inputs can compromise military decision-making systems
• Trust erosion: Security breaches may damage critical alliance relationships
• Mitigation framework: The paper proposes specialized countermeasures for federated military LLM deployments

This research is vital for security professionals as it addresses emerging vulnerabilities at the intersection of AI and military operations, potentially preventing catastrophic security breaches in allied defense systems.

Exploring Potential Prompt Injection Attacks in Federated Military LLMs and Their Mitigation