is-this-photo-real

The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.

---
name: is-this-photo-real
description: >-
  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.

---

# 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

| The claim under test | Do this first | Not this |
|---|---|---|
| "This shows event X in place Y" | `find-the-original-image`, then `geolocate-from-pixels` | Any forensic filter. Recontextualisation leaves no pixel trace at all. |
| "This is an unaltered photograph" | Signal-level analysis, on the least-processed copy you can obtain | Analysing a screenshot or a platform download; both destroy the signal. |
| "This person said this on video" | Provenance, then audio-visual consistency, then face-boundary behaviour frame by frame | An AI-detector score. |
| "This image was AI-generated" | Absent camera physics and incoherent object structure | A detector verdict on its own. |
| "This screenshot is genuine" | Layout, font and interface-version consistency; the underlying record if one exists | Image forensics. Fabricated screenshots are made in a browser, not an image editor. |

Then always ask what the image would look like if the claim were **true**, write it
down, and check for those things specifically. Verification tests a hypothesis;
hunting for anomalies fails, because anomalies are everywhere.

## Method

1. **Get the best copy.** Every re-encode, resize and screenshot destroys forensic
   signal. Chase the original upload or the agency version, not the platform rendition.
   Hash it, work on copies. If all you have is a screenshot, say so and lower every
   downstream conclusion.
2. **Provenance.** Run `find-the-original-image`; for video, extract and search
   keyframes. You want an earlier appearance, a different caption, a photographer
   credit, and an on-page date corroborated through `read-deleted-pages`. An earlier copy
   with a different caption ends the case.
3. **Metadata.** Run `secrets-in-file-metadata`: editing chain, thumbnail-versus-image
   comparison, timestamp inconsistencies, whether MakerNotes fit the claimed device.
4. **Provenance signing.** Check for C2PA Content Credentials.
5. **Internal consistency.** Signage language, plates, currency, uniforms, vehicle
   models, season, weather and shadows against the claimed date and place, via
   `geolocate-from-pixels`. Ordinary detective work, more productive than forensics.
6. **Physical consistency.** Lighting, shadows, reflections, perspective.
7. **Signal-level forensics.** Noise residuals, JPEG quantisation and double compression,
   clone detection, colour-filter-array traces. Easy to over-read, worthless on a
   platform-processed file.
8. **Write what you verified**, not a verdict.

Tools and their failure modes: [reference/tool-catalogue.md](reference/tool-catalogue.md).
Ordered by cost: [