San Jose resident Margaret Loke lost nearly $1 M in a social engineering attack. The criminals executed a standard pig butchering scenario, combining a romance scam with simulated high-yield trading.
The scheme relied on months of psychological manipulation. The attacker, posing as a businessman, built trust through messaging apps. Unlike primitive phishing, this attack was designed to completely drain the victim’s liquidity.
The scammer convinced Loke to transfer funds to a controlled platform that displayed fabricated trading profits. The fake exchange interface maintained an illusion of success, showing a balance of $2.4 M, which encouraged further deposits.
To finance these deposits, the victim liquidated her pension savings and secured a loan against her real estate.
The situation reached its breaking point when she attempted to withdraw funds. The platform expectedly froze the assets, and her handler demanded an additional $1 M to unlock the account — a standard scam mechanic designed to extract the last remaining resources.
When her partner began making threats, Loke grew suspicious and fed the details into ChatGPT. The AI analyzed the patterns — withdrawal freezes, fees to unlock funds, and refusal to meet in person — and identified the incident as fraud. The recommendation to contact law enforcement was the sole trigger that finally forced the victim to accept the reality of the scam.
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