Description: An individual or group allegedly used AI-based face modification tools to impersonate FTX claimants in video calls, reportedly defrauding two companies of over $5.6 million in the secondary claims market. The perpetrator reportedly used forged IDs, deepfake-style visuals, and claim data likely obtained from public records or a prior breach at Kroll. Funds were alleged to have been laundered through exchanges including Binance, CoinEx, and Gate.io.
Editor Notes: Please consult the full report prepared by Inca Digital on this incident at the following URL: https://inca.digital/intelligence/ftx-debt-fraud/.
Entities
View all entitiesAlleged: Unknown deepfake technology developer and Unnamed providers of synthetic video generation software developed an AI system deployed by Fraudster using aliases Lim Chee Chong and Teh Jin Loon, which harmed Two unnamed companies that purchased fraudulent FTX debt claims , FTX estate , Kroll , Public trust in FTX bankruptcy claims resolution process , Cryptocurrency market participants exposed to fraudulent claims resale and Claims verification and due diligence infrastructures in secondary debt markets.
Alleged implicated AI systems: Unknown deepfake technology , ProtonMail , FTX claims portal , Kroll’s claims database , CoinEx , Binance , Gate.io and Orbeon Forms
Incident Stats
Incident ID
1067
Report Count
2
Incident Date
2025-02-18
Editors
Daniel Atherton
Incident Reports
Reports Timeline
Inca Digital identified fraudulent activity in the secondary market of FTX debt claims trading. An individual/group operating under multiple aliases defrauded at least two separate companies for $5.6 million and proceeded to launder the ent…
A sophisticated fraud scheme involving deepfake technology has led to the theft of at least $5.6 million from companies purchasing fake FTX liquidation claims, according to Inca Digital. The scam, uncovered ahead of FTX’s scheduled payouts …
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.
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