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Incident 921: Hong Kong Authorities Seize HK$34M in Alleged Deepfake Scam Targeting Victims in Taiwan, Singapore, and Malaysia

Description: Hong Kong police arrested 31 people linked to a deepfake scam syndicate that allegedly defrauded victims in Taiwan, Singapore, and Malaysia. The group used AI-generated images to impersonate wealthy women, training recruits to discuss luxury lifestyles, finance, and cryptocurrency to gain trust. Scammers reportedly persuaded victims to invest in fraudulent schemes, with police intercepting HK$34 million in illicit proceeds.
Editor Notes: See also Incident 1066.

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Alleged: Unknown deepfake technology developers and Unknown AI-generated image creators developed an AI system deployed by Hong Kong-based deepfake scam syndicate, which harmed Victims of romance scams in Taiwan , Victims of romance scams in Singapore , Victims of romance scams in Malaysia , Hong Kong financial regulators investigating fraud and Cryptocurrency investors defrauded by AI-generated profiles.
Alleged implicated AI systems: Social media platforms used for fraud , Cryptocurrency trading platforms , AI-generated deepfake image platforms and AI-driven text and chatbot manipulation tools

Incident Stats

Incident ID
921
Report Count
1
Incident Date
2025-01-05
Editors
Daniel Atherton

Incident Reports

Reports Timeline

+1
How Hong Kong deepfake scam group taught recruits to pass as rich, single women
How Hong Kong deepfake scam group taught recruits to pass as rich, single women

How Hong Kong deepfake scam group taught recruits to pass as rich, single women

scmp.com

How Hong Kong deepfake scam group taught recruits to pass as rich, single women
scmp.com · 2025

Learning Japanese, playing golf and tasting red wine worth more than HK$100,000 (US$12,850) a bottle were among the topics of conversation prompts a scam syndicate taught recruits to help pass as rich, single women, Hong Kong police have re…

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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