Description: Mumbai Cyber Police reportedly uncovered a coordinated investment fraud campaign that used purported deepfake videos of Indian stock market experts to mislead investors. Between July 1 and July 18, 2025, the videos reportedly circulated on social media as paid promotions by a Bengaluru-based firm, Valueleaf, allegedly contracted by a Hong Kong company, First Bridge. Four individuals were arrested.
Editor Notes: The reported timeline of events is as follows: (1) in early July 2025, a prominent Indian stock expert reportedly discovered deepfake videos of himself circulating online and reported them to Mumbai Cyber Police; (2) between July 1 and July 18, 2025, the videos were reportedly distributed on social media, spreading false share-trading claims; (3) in mid-July, Meta reportedly flagged the content, prompting the perpetrators to expand their ad accounts and shift their domain to Dubai; (4) by late July, the videos were reportedly removed after being flagged as misinformation; and (5) in October 2025, police arrested four individuals linked to Bengaluru-based firm Valueleaf and charged them under BNS and IT Act provisions; (6) the incident ID was added to the AIID on 10/18/2025.
Entities
View all entitiesAlleged: Unknown deepfake technology developer and Unknown voice cloning technology developer developed an AI system deployed by Valueleaf and First Bridge, which harmed Unnamed Indian stock market experts , Indian investors , Investors and General public of India.
Alleged implicated AI systems: Unknown deepfake technology and Unknown voice cloning technology
Incident Stats
Incident ID
1235
Report Count
1
Incident Date
2025-07-01
Editors
Daniel Atherton
Incident Reports
Reports Timeline
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In a major breakthrough, the Mumbai Cyber Police have exposed a sophisticated fraud network that used deepfake videos of prominent Indian stock market experts to deceive investors. The police have arrested four individuals from Bengaluru fo…
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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