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AI incident #1501 ·

Texas Man Arturo Hernandez Allegedly Published AI-Generated Deepfake Pornography Depicting Women in TAKE IT DOWN Act Case

Open on the AI Incident Database 2 news reports Synced from the AIID API · record last edited 7 Sep 2026

What happened

DOJ alleged that Texas defendant Arturo Hernandez published about 113 albums of AI-generated deepfake pornography depicting about 50 identifiable women, including non-public figures and recent high school graduates, during a period anchored to May 2025. Prosecutors said non-explicit source images were allegedly transformed into sexualized depictions. The case was among the first prosecutions announced under the TAKE IT DOWN Act.

Editor's notes (AI Incident Database)

See also Incident 1500. DOJ announced the Arturo Hernandez and Cornelius Shannon prosecutions together because the complaints were unsealed on the same day under the TAKE IT DOWN Act. Reporting suggests that the two men did not appear to be connected, and the complaints describe distinct alleged conduct, so the cases are treated as separate incident IDs. Timeline notes: (1) Reporting suggests an anchor date of 05/19/2025 for this incident ID. (2) 05/2025–05/2026, prosecutors allege that Hernandez published about 113 albums depicting about 50 identifiable women, including non-public figures. (3) 05/20/2026, the criminal complaint was unsealed and the suspect was arrested in Bedias, Texas. (4) 05/26/2026, the incident ID was created.

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. Two Individuals Arrested for Publishing AI Deepfake Pornography In Violation Of TAKE IT DOWN Act
    justice.gov · John Marzulli, Denise Taylor, United States Department of Justice · AIID #7320
  2. Two men charged with creating AI-generated porn under new law targeting ‘deepfakes’
    apnews.com · Jake Offenhartz · AIID #7319

Who was involved

Alleged harmed party
Women and girls Women Victims of non-consensual deepfakes Victims of deepfake abuse Public figures Privacy Epistemic integrity Celebrities
On AIID: Women and girls, Women, Victims of non-consensual deepfakes, Victims of deepfake abuse, Public figures, Privacy, Epistemic integrity, Celebrities

AI systems implicated

Synthetic media generation technologySynthetic image generation technologyMedia-sharing platformsDeepfake technologyDeepfake pornography websites

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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