ZONN.ai Forensic Report

Case · 2809C3A2 · IMAGE

ZONN Analysis
0

Probably real

More signals lean toward real than AI, but some give weaker readings. Worth a second look on close inspection.

Signal ConfidenceLimited · 46/100

Analysed Specimen

Original analysed image
Forensic suspicion heatmap
OriginalHeatmap
POS55/100
No flagged regions

Heads up — 2 things to know

Why this analysis might be off

We highlight every disagreement and unusual signal we found so you can judge for yourself. Stronger warnings come first; informational notes are at the bottom.

Upsampling artifacts in the frequency domain

AI evidence

FFT analysis found strong upsampling patterns — a fingerprint of diffusion-model VAE decoders (latent → pixel-space upscale).

ML detectors see this image differently

Note

ML scores span a wide range (0–84). Different architectures read different feature spaces; the majority vote strengthens the consensus, but no single model is fully reliable here.

Origin Check

Trace this image elsewhere

Cross-reference the source against major reverse-image services. Each link opens in a new tab with the image URL preloaded — ZONN.ai does not re-upload the image.

Evidence — 16 detectors reviewed

What each detector saw

Each detector independently gave this imagea score from 0 (definitely real) to 100 (definitely AI). The score above is their weighted consensus — detectors with higher confidence count more. No single detector decides; you read the spread.

CommFor (4803 Generators)
0
INA v2 (FLUX/MJ)
12
xRayon ConvNeXtV2
84
SigLIP AI Detector
17
Noise Pattern
18
Error Level Analysis
26
Frequency Analysis
72
Color Distribution
30
Bombek1 SigLIP+DINOv2
68
Pixel Analysis
35
ICC Profile
62
Compression Quality
48
Edge Consistency
48
Metadata
50
C2PA Provenance
50
Manipulation Map (IML-ViT)
50

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 14, 2026, 10:02 PM