Sample summary
The file contains limited metadata and several compression/export clues. These are not proof of AI generation, but they justify source verification and deeper review.
Sample report
Image authenticity example report for AI, EXIF and forensic evidence.
This sample shows how OsintNET can explain image authenticity signals without pretending that a single score is absolute proof.
Designed for analysts who need clear signals, not scattered tabs.
Evidence format
Each image finding should separate observed data from interpretation, because missing EXIF, platform recompression and editing workflows can all look similar.
Recommended next steps
Compare with original source files, run reverse-image research, inspect metadata history, review generator trace strings and document confidence carefully.
Common questions
What should an image authenticity report include?
It should include AI-generation indicators, EXIF metadata context, generator traces, compression clues, file-consistency checks, visual forensic signals, confidence and limitations.
Can this report prove an image is fake?
No report should overclaim from weak signals. The goal is to explain evidence, confidence and what should be verified next.
Continue with the next evidence layer.
Image authenticity checker
Review the full authenticity workflow for AI, EXIF and forensic clues.
OsintNET vs AI image detectors
Compare score-only AI detection with evidence-first image review.
Reverse Image OSINT Guide
Use reverse-image research to validate source and context.
Start investigation
Use OsintNET to convert public signals into structured evidence.
Pick the module that matches your target and keep each clue connected to its source, confidence and investigation context.