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Incident 1268: Meta's Automated Ad and Targeting Systems Reportedly Enabled Large-Scale Fraud Revenue

Description: Internal Meta documents reviewed by Reuters reportedly show that the company's automated ad and targeting systems generated major revenue from fraudulent ads and exposed users to billions of scam impressions daily. Enforcement was limited by internal revenue guardrails. In one example, a Royal Canadian Air Force recruiter's account was hacked and used to run a crypto scam that defrauded several colleagues after repeated reports allegedly went unanswered.

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Alleged: Meta developed an AI system deployed by Meta , Unknown scammers and Unknown fraudsters, which harmed Unnamed Royal Canadian Air Force recruiter , Meta users , social media users and Epistemic integrity.
Alleged implicated AI systems: Meta Platforms , Meta ad approval pipeline , Meta ad ranking algorithm and Social media

Incident Stats

Incident ID
1268
Report Count
2
Incident Date
2025-11-06
Editors
Daniel Atherton

Incident Reports

Reports Timeline

+1
Meta is earning a fortune on a deluge of fraudulent ads, documents show
Facebook’s fraud files
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Meta is earning a fortune on a deluge of fraudulent ads, documents show

Meta is earning a fortune on a deluge of fraudulent ads, documents show

reuters.com

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Facebook’s fraud files

Facebook’s fraud files

doctorow.medium.com

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Meta is earning a fortune on a deluge of fraudulent ads, documents show
reuters.com · 2025

Meta internally projected late last year that it would earn about 10% of its overall annual revenue -- or $16 billion -- from running advertising for scams and banned goods, internal company documents show.

A cache of previously unreported …

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Facebook’s fraud files
doctorow.medium.com · 2025

A blockbuster Reuters report by Jeff Horwitz analyzes leaked internal documents that reveal that: 10% of Meta's gross revenue comes from ads for fraudulent goods and scams, and; the company knows it, and; they decided not to do anything abo…

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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