Agent Reasoning Hijacking affecting LLM agents that use chain-of-thought reasoning and external tools. This flaw allows attackers to inject adversarial strings that manipulate the agent's thinking process, leading it to perform unintended malicious actions like data theft or unauthorized access. The sources detail how this attack works, its potential impact on various LLM models and real-world applications, and recommend several mitigation strategies such as input sanitization and reasoning monitoring to defend against it. The research paper "UDora" is highlighted as a key resource for understanding and addressing this significant threat to LLM agent security.