# What is a Deepfake?

> A deepfake is audio, video, or imagery generated or significantly manipulated with artificial intelligence to resemble a person, object, place, entity, or event and falsely appear authentic or truthful.

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## Content

Deepfakes can support entertainment, accessibility, education, and creative work; they become a security concern when used without authorization or context to deceive, impersonate, harass, or influence decisions.

Creation methods include face or body replacement, synthetic speech, lip synchronization, and generation of an entire scene. Risk depends on the content, consent, presentation, audience, and resulting action — not simply on whether artificial intelligence was involved. A convincing fake can strengthen social engineering, but authentic media can also be edited, mislabeled, or presented out of context.

### Key points

- **Verification:** Check the claimed source, publication history, surrounding context, and independent reporting; confirm high-impact requests through a known channel rather than relying on a familiar face or voice.
- **Organizational controls:** Define approval paths for payments, account recovery, public statements, and sensitive instructions so one recording or live call cannot authorize a consequential action.
- **Technical evidence:** Preserve the original file, message, account details, timestamps, and available provenance metadata for qualified analysis instead of repeatedly transcoding or reposting the material.
- **Important limitation:** Visual inspection and automated detectors can both fail, while watermarks and provenance records may be absent, removed, or misinterpreted. No single signal proves that content is authentic, synthetic, truthful, or malicious.

### Related terms

[AI security](<https://yellowcube.eu/glossary/ai-security/>) · [Social engineering](<https://yellowcube.eu/glossary/social-engineering/>) · [Vishing](<https://yellowcube.eu/glossary/vishing/>) · [Identity theft](<https://yellowcube.eu/glossary/identity-theft/>) · [Internet fraud](<https://yellowcube.eu/glossary/internet-fraud/>)

### Sources

[NIST AI 100-4: Reducing Risks Posed by Synthetic Content](https://www.nist.gov/publications/reducing-risks-posed-synthetic-content-overview-technical-approaches-digital-content) · [European Commission: AI Act Article 50 transparency guidance](https://digital-strategy.ec.europa.eu/en/faqs/transparency-obligations-under-article-50-ai-act)

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