AI incident #777 ·

South Korea Reportedly Experienced a Surge of Explicit Deepfake Pornography

Open on the AI Incident Database 7 news reports Synced from the AIID API · record last edited 5 Sep 2026

What happened

At the end of August 2024, South Korean authorities reportedly began investigating a significant surge in the creation and dissemination, often via Telegram, of explicit deepfake pornography created without consent from the stolen social media content of female classmates, teachers, and neighbors.

Editor's notes (AI Incident Database)

In one report, seven suspects were arrested, six of whom were teenagers. Another report mentions a graduate of Seoul National University in his 40s. One of the Telegram channels dedicated to the deepfakes was reported to have 220,000 members. One report indicates that between January 1 and August 25, 781 deepfake victims sought assistance from the state agency handling digital sex crimes, with 288 of those victims, or approximately 37%, being minors. This incident ID is for cataloguing the reporting on this pronounced flurry of deepfake pornography incidents in South Korea at the end of summer 2024.

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 (7)

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

  1. South Korea faces deepfake porn 'emergency'
    bbc.com · Jean Mackenzie, Nick Marsh · AIID #4036
  2. South Korea Is Facing Deepfake Porn Crisis
    bloomberg.com. · Catherine Thorbecke · AIID #4051
  3. 他们给AI投币1美元,百万女性被拖入地狱|深氪lite
    baijiahao.baidu.com · Deng Yongyi, Zhou Xinyu, Qiu Xiaofen · AIID #4052

Who was involved

Alleged harmed party
Women and girls Women Victims of non-consensual deepfakes Victims of deepfake abuse Privacy General public of South Korea General public Epistemic integrity
On AIID: Women and girls, Women, Victims of non-consensual deepfakes, Victims of deepfake abuse, Privacy, General public of South Korea, General public, Epistemic integrity

AI systems implicated

TelegramSynthetic media generation technologyDeepfake technology

Classification (MIT AI Risk Repository taxonomy)

Causal entity
AI
Intent
Intentional
Timing
Post-deployment
Harm level
Sectors
Countries

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)

  • Misinformation and Manipulation

    "Recent studies have demonstrated that LLMs can be exploited to craft deceptive narratives with levels of persuasiveness similar to human-generated content (Pan et al., 2023b; Spitale et al., 2023), to fabri- cate fake n...

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

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