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AI incident #1163 ·

Purported Face‑Swap Technology Reportedly Used to Circumvent Financial Platform's Facial Recognition Security in Nanjing, China

Open on the AI Incident Database 2 news reports Synced from the AIID API · record last edited 4 Sep 2026

What happened

In Nanjing, Jiangsu Province, a defendant (Fu Mou) was convicted in October 2024 for allegedly using AI‑powered face‑swap software to bypass an unnamed financial platform's facial recognition system. Authorities reported that he obtained over 1.95 million pieces of personal data, accessed 23 victims' payment accounts, changed passwords for several, and used one linked bank card to make purchases. Prosecutors said only one platform was successfully breached.

Editor's notes (AI Incident Database)

Timeline note: The reporting indicates that the suspect in the case was sentenced in October 2024. The incident ID date of 10/15/2024 is an approximation. Public reporting on this incident appears to have emerged on 07/18/2025. Suspect name note: Chinese legal reporting often partially anonymizes defendants' names by publishing only the surname followed by the character 某 (Mou), meaning "a certain" or "someone." In this case, the reported perpetrator is identified as 符某 (Fu Mou), indicating that the surname is Fu but the given name has not been disclosed.

Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.

News reports (2)

Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.

  1. 男子买195万条个人信息盗刷1万多元 男子AI换脸盗刷他人账户1万多获刑
    k.sina.com.cn · 央视网, CCTV News · AIID #5602
  2. “AI換臉”可以繞過人臉識別防線？
    big5.cctv.com · 央视网, CCTV Online · AIID #5601

Who was involved

Alleged harmed party
Unnamed financial payment platform Individuals affected by compromise of 1.95 million+ personal records 23 unnamed victims whose payment accounts were accessed
On AIID: Unnamed financial payment platform, Individuals affected by compromise of 1.95 million+ personal records, 23 unnamed victims whose payment accounts were accessed

AI systems implicated

Synthetic video generation technologySynthetic media generation technologyFinancial payment platformsFace-swap technologyDeepfake technologyAI-enabled decision support systems

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
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Sectors
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Countries
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Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 4.3.

  • Impersonation/identity theft

    "Impersonation/identity theft - Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • IP/copyright loss

    "IP/copyright loss - Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Dehumanisation/objectification

    "Dehumanisation/objectification - Use or misuse of a technology system to depict and/or treat people as not human, less than human, or as objects."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Defamation/libel/slander

    "Defamation/libel/slander - Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group, or organisation."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Financial and business

    "Financial and Business - Use or misuse of a technology system in a manner that damages the financial interests of an individual or group, or which causes strategic, operational, legal or financial harm to a business or...

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Cheating/plagiarism

    "Cheating/plagiarism - Use of another person’s or group’s words or ideas without consent and/or acknowledgement."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Cybersecurity

    "LLMs may exacerbate cybersecurity risks in various ways (Newman, 2024). Firstly, LLMs may significantly amplify the effectiveness of deceptive operations aimed at tricking people into disclosing sensitive information or...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

  • Domain-Specific Misuses

    "Improvements in LLMs may exert greater pressure to apply LLMs to various domains, such as health and education (Eloundou et al., 2023). Crude efforts to use LLMs in such domains, however, may incur harm and should be di...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Linked by AIID editors or by its text-similarity model.

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