Securing the Model Context Protocol: Defending LLMs Against Tool Poisoning and Adversarial Attacks

This article focuses on the critical security aspects of Large Language Models (LLMs), specifically addressing vulnerabilities related to tool poisoning and adversarial attacks. The research likely explores methods to harden the model context protocol, which is crucial for the reliable and secure operation of LLMs. The use of 'ArXiv' as the source indicates this is a pre-print, suggesting ongoing research and potential for future peer review and refinement.