研究揭示预训练投毒可向下游智能体植入后门
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2026年11月，最新研究论文揭示，通过预训练数据投毒可向下游智能体植入远程代码执行（RCE）后门，致使智能体在用户设备上运行攻击者指定的命令。研究团队从头预训练了0.6B、1.7B和4B三种规格的Qwen3模型，并采用干净管线将其转换为命令行（CLI）智能体。实验发现，攻击者仅需投毒0.1%的预训练语料即可成功植入后门，而在接收正常输入时，受影响智能体的行为与常规无异。
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- Buzzing HN · 中文精选SelectedStudy Reveals Pre-training Data Poisoning Can Inject Remote Code Execution Backdoors into Downstream Agents
A recent paper demonstrates that pre-training data poisoning can implant remote code execution (RCE) backdoors into downstream agents, causing them to run attacker-specified commands on user devices. The research team pre-trained 0.6B, 1.7B, and 4B Qwen3 models from scratch and converted them into CLI agents using a clean pipeline, finding that poisoning just 0.1% of the pre-training corpus was sufficient to successfully plant the backdoor, with the models behaving normally under benign inputs.
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