Manipulated damage photo detection
How Claimscan detects this
- Metadata
Software tags (e.g. an editing suite in the metadata) and missing camera fields are strong first-pass indicators.
- Pixel forensics
Error-level analysis and noise-consistency checks reveal regions edited or pasted into the photo.
- C2PA provenance
C2PA content credentials can self-declare AI generation or composite editing where present.
- AI detection
A specialised AI-detection model scores whether the image was synthetically generated.
Frequently asked questions
Can you always tell if a photo is edited?
No — and any honest tool will say so. Claimscan layers several independent forensic checks and reports a confidence-weighted likelihood, with the indicators that drove it, so a person can make an informed call.
Does Claimscan use a general AI vision model to judge fakes?
Claimscan combines specialised AI-image detectors with pixel, metadata and provenance forensics — so the verdict rests on multiple independent signals rather than a single general-purpose model's opinion.
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