Description: A criminal group in China used AI face-swapping technology to bypass face recognition systems on major platforms, steal personal data, and sell it to fraud syndicates. The group generated convincing video simulations from static photos to breach accounts, reportedly earning 200,000 yuan. After an investigation by the Hangzhou Public Security Bureau, four suspects were arrested across the provinces of Anhui, Guizhou, and Zhejiang.
Entities
View all entitiesAlleged: Unknown deepfake detection technology developers developed an AI system deployed by Hu Mouyun , Hu Mouliang , Zhang Mouguo and Wu Mouhao, which harmed Chinese citizens , Zhejiang citizens , Anhui citizens and Guizhou citizens.
Incident Stats
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
4.3. Fraud, scams, and targeted manipulation
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- Malicious Actors & Misuse
Entity
Which, if any, entity is presented as the main cause of the risk
Human
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Intentional
Incident Reports
Reports Timeline
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Convert a static face photo into a "face recognition" function, then log in to other people's accounts to collect personal information, and then sell the information to fraud gangs...Recently, this case of using AI technology to infringe on…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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