Home Crime Hong Kong Police Bust Deepfake Romance Scam Ring, Seize $10 Million In...

Hong Kong Police Bust Deepfake Romance Scam Ring, Seize $10 Million In Assets

Hong Kong police arrest 31 over deepfake romance scams v2

Hong Kong police have dismantled an elaborate cybercrime syndicate that used cutting-edge artificial intelligence to perpetrate sophisticated romance and investment scams, arresting 31 suspects and recovering approximately $10 million in ill-gotten gains.

The Commercial Crime Bureau revealed Sunday that the criminal network, operating for over a year, targeted victims across multiple countries, including Taiwan, Singapore, Malaysia, and the United States, using deepfake technology to create convincing digital personas.

Superintendent Fung Pui-kei described the group’s insidious methodology, explaining that suspects employed AI face-swapping technology to generate hyper-realistic images of attractive individuals, establishing fake online romantic relationships to manipulate potential victims.

“These criminals weaponized emerging technologies to exploit human emotions,” Fung said. “By creating seemingly genuine connections, they systematically convinced victims to invest in fraudulent platforms.”

The coordinated raid in Kowloon Bay’s industrial district netted 31 individuals aged 20 to 34, most of whom claimed unemployment. Five core members now face conspiracy to defraud charges, scheduled for Monday’s court appearance.

Total financial losses from the scam exceed HK$34 million, marking another significant blow to increasingly sophisticated cybercrime networks exploiting artificial intelligence.

Law enforcement is investigating potential connections to a similar syndicate taken down last October, signaling a potentially broader criminal infrastructure targeting international victims through advanced technological deception.

The case underscores growing concerns about deepfake technologies’ potential for criminal exploitation, highlighting the urgent need for robust digital security measures.