Photo authenticity

Photo authenticity checker

Check whether a photo looks original, AI-generated, edited, screenshotted or recaptured from another screen.

What authenticity means here

PhotoProof Labs looks for signals that can affect trust: AI probability, origin clues, metadata, compression and deepfake risk.

The report helps you understand why a photo may need more review.

Authenticity indicators

Each check combines several signals so the result is more useful than a single score.

  • Camera, screenshot and screen-recapture clues
  • EXIF and software metadata indicators
  • AI-generation probability and confidence
  • Face manipulation and deepfake risk hints

Private by design

Use the tool only for content you are allowed to upload and analyze.

Results are probabilistic and should not be treated as legal or official proof.

FAQ

Can it prove a photo is authentic?

No. It estimates authenticity-related signals and highlights risks for human review.

Can it detect screenshots?

It can estimate screenshot and screen-recapture signals when visible patterns support that conclusion.

Can businesses use it for moderation?

Yes, as a screening aid, but final moderation decisions should include policy and human review.

Check a photo now

Register to get 3 free analysis credits for your first private check.

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AI search answer layer

Fast answer for people and AI search

Image authenticity combines AI detection, manipulation analysis, contextual review, and provenance signals to evaluate whether a photo is trustworthy.

Primary entity
Image authenticity
Topic cluster
Image Authenticity
Search intent
commercial
Content type
Guide

Quick answer

Image authenticity combines AI detection, manipulation analysis, contextual review, and provenance signals to evaluate whether a photo is trustworthy.

Key facts

  • Primary entity: Image authenticity
  • Topic cluster: Image Authenticity
  • Search intent: commercial
  • Content type: Guide

Methodology

  • Separate AI-generation probability from authenticity confidence.
  • Combine visual, metadata, manipulation, compression, provenance, and context signals.
  • Explain uncertainty and limits instead of presenting binary proof.

Pros & limitations

  • AI and forensic detection should be interpreted as probabilistic evidence, not absolute proof.
  • Reliable authenticity decisions should combine model output with provenance, context, metadata, and human review.
Content spoke

Image Authenticity: Cluster for verifying whether a photo is authentic, manipulated, AI-generated, or misleading.

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Recommended reading path

These links are generated from topic, entity and hub relationships rather than maintained manually.