Individual skill
is-this-photo-real
Verify whether an image or video is authentic, original and correctly captioned — provenance checks, error level analysis, noise and JPEG compression analysis, clone and copy-move detection, lighting and shadow consistency, C2PA Content Credentials, deepfake and AI-generation tells, and the honest limits of AI-detector tools. Use when fact-checking a photo or video, checking for a deepfake or AI-generated image, spotting manipulation, or testing whether footage is recycled or miscaptioned. Applies to KYC and onboarding fraud, insurance claim review, disinformation analysis, and evidence admissibility. Reference at useosint.com/skills/is-this-photo-real.
skills/is-this-photo-real/SKILL.md
Source commit 06243a5620b0c9c97502edd4ee9e31995a3bdccd
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- Last checked
- Nov 6, 2026
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- 61
- Repository last updated
- Aug 3, 2026
- License
- MIT
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SKILL.mdcore · 16,045 bytesSKILL.mdcore · 16,045 bytesSKILL.mdcore · 16,045 bytesSKILL.mdcore · 16,045 bytesreference/tool-catalogue.mddoc · 10,989 bytesreference/verification-checklist.mddoc · 8,922 bytes
Read excerpt
# Is this photo real
Verification order is the whole skill: **provenance first, pixels last.** Finding the
earliest copy and reading its caption settles more cases than every forensic filter
combined, and it produces evidence you can show someone. Pixel forensics produces a
colourful heatmap and an argument.
The beginner mistake is running error level analysis on a downloaded JPEG and announcing
the image is fake. The second is looking for deepfakes: the overwhelming majority of
deceptive media is **real footage with a false caption** — right pixels, wrong war,
wrong year, wrong country.
## Triage: what question are you actually answering
