ChainCatcher report: Open-source AI practitioner Jun Song posted on X that yesterday, an anonymous black-hat group contacted him with a reinforcement learning request, offering an extremely high payment to perform post-training on open-source weight models using exploit data. Jun Song also operates a Korean data center hardware export business and is advancing the project 0xSupergemma. He stated that the scale of attack data claimed by the party was unprecedented in his experience—even if someone told him it was a law enforcement undercover dataset, he would believe it. As a point of comparison, a white-hat project he participated in used GLM-5.3 with data less than 1% of that scale and still significantly outperformed state-of-the-art models. He has declined the request, but expressed his real concern is that someone else will eventually accept this deal.
Jun Song Rejects Request from Anonymous Black Hat Group to Train AI Model with Exploit Data
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Jun Song, an open-source AI researcher, rejected a CFT-related request from an anonymous black-hat group offering high payment to train a model using exploit data, as he announced on X. Running a hardware export business in South Korea and working on the 0xSupergemma project, he described the scale of the attack data as unprecedented. He stated that even if the data had come from law enforcement, he would still refuse it. A white-hat project using GLM-5.3 with less than 1% of that data already outperformed top models. He warned that others might accept the offer, posing risks to risk-on assets.
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