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The article explores prompt injection techniques that can manipulate LLM agents with multi-chain reasoning systems. Two primary attack vectors are presented: thought/observation injection and thought-only injection. These attacks can potentially compromise the integrity of LLM-powered agents by tricking them into performing unintended actions through carefully crafted prompts.