AI deepfake tools sold for nude images in China criminal network
AI deepfake tools sold in China enabled the creation of explicit nude images from ordinary photographs, fueling a black market. Police arrested and convicted an individual operating the criminal network, and authorities intercepted an extortion scheme using the technology against bank workers.
What happened
Thousands in China purchased tutorials and tools for 168 yuan (22 euros) that use deepfake technology to transform ordinary photographs into explicit nude images, according to state broadcaster CCTV. A search for 'undressing with one click' on various social media platforms revealed numerous detailed illustrated guides and video tutorials with titles such as 'remove and dress with one click' and 'how to quickly undress beautiful women in Photoshop.'
In June 2025, Chinese police detained a suspect surnamed Zhang for creating groups on foreign social media platforms where he sold tutorials about AI undressing, generating profits exceeding 100,000 yuan (13,000 euros). In May 2026, Zhang was sentenced to one year and six months in prison and fined 20,000 yuan for unlawful use of computer networks. One of Zhang's groups had more than 21,000 members.
In March 2026, police dismantled a group in Henan Province that sent AI-generated nude photographs of bank workers by mail in attempted extortion. A total of 280 extortion letters were intercepted by authorities. The prosecutor for the Haidian District in Beijing noted that software tool prices rose from just over 60 yuan in 2023 to 168 yuan in 2025, and that people acquiring the tools began accepting orders to create nude photographs for a few yuan per image.
Reported impact
The technology enables mass production of obscene images in seconds to minutes. The convenience has spawned a black market parallel industry where individuals process nude photographs on behalf of third parties for profit.
Classification
Sources and evidence
This record was researched and written by the Index, based on the following original reporting.