Description: Researchers attributed a September 2026 influence campaign targeting U.S. Democratic Senate candidates to the Russia-linked Matryoshka/Operation Overload network. The campaign reportedly used AI-cloned celebrity voices and fabricated, news-branded videos to spread false or unsubstantiated claims on social media. Celebrities and CNN rejected the manipulated statements and unauthorized branding, which were intended to influence U.S. voters before the midterms.
Entities
View all entitiesAlleged: Voice cloning technology developers , Synthetic media generation technology developers and Deepfake technology developers developed an AI system deployed by Synthetic media creators , Storm-1679 , Russian state-linked actors , Pro-Russian information manipulation actors , Operation Overload , Matryoshka , Information manipulation actors in Russia , Information manipulation actors , Influence operation groups and Deepfake creators, which harmed Voters in the United States , Voters , Public figures , Politicians in the United States , Politicians , Political candidates targeted by deepfakes , Epistemic integrity , Democratic integrity , deepfaked celebrities and Celebrities.
Alleged implicated AI systems: X (Twitter) , Voice cloning technology , TikTok , Social media platforms , Deepfake technology and Bluesky
Incident Stats
Incident ID
1702
Report Count
2
Incident Date
2026-09-10
Editors
Daniel Atherton
Incident Reports
Reports Timeline
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The Russian government has been targeting Americans with covert online disinformation operations seeking to undermine public confidence in November’s midterm elections, using a familiar playbook in an attempt to inject chaos into the voting…
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A few days ago, an X user called роман---which is Russian for the name "Roman"---posted a purported Mother Jones video that reported that the Democratic National Committee paid a whopping $259 million to Mark Thompson, the head of CNN, so t…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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