Cases › produced harmful content › LR-2026-0353
Academics deepfaked on TikTok and Instagram to promote supplements
Preliminary Why: Publisher not yet named · subject to change
Status: no action reported
No source states: loss or records, developer and model, agent tool, could do, deployer, industry.
Severity moderate: Test applied: data or systems of others touched with a bounded scope stated. Real named professionals' likenesses were used in videos on one account, which had accrued more than 365,000 views before it was banned.
Social media accounts, including @better_healthy_life on TikTok, posted AI-generated deepfake videos of real doctors and academics promoting health supplements. One video showed a real professor, David Taylor-Robinson, talking about menopause in footage he never recorded. He reported the posts with his children; TikTok said they broke its community guidelines but left them online with restricted visibility. TikTok said the delay was caused by a moderating error. The videos were later removed for breaching its impersonation and misinformation policies, and the account was permanently banned. Full Fact also found similar deepfakes on Facebook, Instagram, X and YouTube, and the supplement company said the affiliate accounts were unaffiliated with it.
What happened
What was done
No source states an action or fix.
Risks
Also84 incidents
Rising: 6 vs 3.8 a week
Sorted by rule from the case's fields; not yet read from the sources.
Controls
ModelNot effective Abuse monitoring and account enforcement
Control failure chain
L1 · ModelProvider not namedModel provider
Model version not linked to a model card.
Other controls for this risk at this layer, not mentioned in the sources: Marking machine-made output, Content safety classifiers.
L2 · HarnessHarness not namedAgent framework vendor
No source mentions a control at this layer.
L3 · ApplicationDeployer not namedDeployer
No source mentions a control at this layer.
Other controls for this risk at this layer, not mentioned in the sources: People told they are dealing with AI.
L4 · Infrastructure / targetOrganisation hit
No source mentions a control at this layer.
Other controls for this risk at this layer, not mentioned in the sources: Phishing and fraud filters.
EffectiveNot effectiveNot effective (bypassed)Did not existNot stated in sourcesNot yet checkedAttacker's ownOrder: model · harness · application · target
Controls for this risk: result in this incident
| Control | Part of the system | Result |
|---|---|---|
| Abuse monitoring and account enforcement | L1 Model | Not effective |
| Content safety classifiers | L1 Model | Not stated in sources |
| Marking machine-made output | L1 Model | Not stated in sources |
| People told they are dealing with AI | L3 Application | Not stated in sources |
| Phishing and fraud filters | L4 Infrastructure / target | Not stated in sources |
Similar incidents
Evidence
No source states: what the AI was doing, what it reached or did, how it was caught, when it happened, when it was found, how many records were exposed, the direct loss, a count of the other parties affected, any court case, the cause, what set it off, what was done.
Show every field, with its source and grade
What happened
Impact
Notes on gaps
The sources describe deepfake videos made by unidentified accounts. Wellness Nest's denial of involvement is reported as its claim and not adopted.
LR-2026-0353 · version 1 · published 2026-11-01 after automatic checks; not yet checked field by field by a person · JSON