AI Risk Wire

Cases › produced harmful content › LR-2026-0740

New York seizes 12 deepfake porn websites after 1,200 people targeted

Preliminary Why: Publisher not yet named · subject to change

Developing: a major or severe case captured in the last 72 hours. Later changes are logged on the corrections page.

Status: no action reported

Severity major
Reported 14 Sep 2026

No source states: loss or records, developer and model, agent tool, could do, deployer, industry.

Severity major: Test: many third parties, a stated count of two or more affected parties. The sources state 1,200 real people depicted without consent.

The Manhattan District Attorney's Office seized twelve websites that used artificial intelligence to create and sell sexually explicit deepfakes. The images and videos depicted 1,200 real people engaging in AI-generated sexual conduct. According to prosecutors, AI image and video tools altered existing photos and videos of real people so they appeared to take part in sexual acts. The resulting content was published, distributed or sold through the sites. The crackdown began after a survivor came forward and reported the alleged crime. The 12 domains were seized under a court order. The investigation into the websites and the people creating or distributing the material remains ongoing.

What happened

1 · What it was doingWebsites used AI image and video tools to alter photos and videos of real people into sexual content.
2 · What went wrongThe altered content was published, distributed or sold through the sites without the people's consent.
3 · How it was caughtA survivor reported images of her on the websites, and that report led to the seizure.

What was done

No source states an action or fix.

Risks

Sorted by rule from the case's fields; not yet read from the sources.

Controls

Not yet read for controls. Controls that mitigate the primary risk:

Model

Marking machine-made output · Abuse monitoring and account enforcement · Content safety classifiers

Application

People told they are dealing with AI

Infrastructure / target

Phishing and fraud filters

Evidence

No source states: what it reached or did, when it happened, when it was found, how many records were exposed, the direct loss, any court case, the cause, what set it off, what was done.

Show the full account: 5 items from the primary sources

What happened, in order

Not dated in the sources:

  • A survivor came forward and reported the alleged crime, which began the crackdown.
  • Investigators shut the sites down after a tip from an unnamed female celebrity.
  • The 12 domains were seized under a court order.
  • The seized domains began displaying notices of a seizure warrant issued by a New York State Supreme Court judge.
  • Prosecutors said they will monitor whether the operations try to return on different domains.
Show every field, with its source and grade

What happened

Earliest source we hold
2026-09-14
D inferred by us from the described behaviour, reason shown
Who caught it
the victim
C one secondary source states it
What went wrong
produced harmful content
D inferred by us from the described behaviour, reason shown

Impact

Other parties affected
1,200
C one secondary source states it
Severity
major
D inferred by us from the described behaviour, reason shown
Why this severity
Test: many third parties, a stated count of two or more affected parties. The sources state 1,200 real people depicted without consent.
D inferred by us from the described behaviour, reason shown

Notes on gaps

The sources describe a law-enforcement seizure of websites, not an AI agent or model incident. The date the activity occurred and the date detected are not stated; only the publication date (2026-09-14, ABC7) and the Monday announcement are given. The victim count of 1,200 is the depicted-person count stated by the sources. The sources say the investigation is ongoing and that the number of deepfake sites in circulation is unclear, with millions said to be online.

LR-2026-0740 · version 1 · published 2026-11-01 after automatic checks; not yet checked field by field by a person · JSON