ZONN.ai Forensic Report

Case · E8F242E8 · IMAGE

MAnalyzed by@muzip
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 · 45/100

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 (0–93). 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.

Why this verdict

  • INA v2 (FLUX/MJ)read real · 0/100

    BEiT-Large dual-head classifier trained on FLUX, Midjourney, and real photo corpora.

  • xRayon ConvNeXtV2flagged AI · 93/100

    ConvNeXtV2 detector trained on FLUX, DALL-E 3, SDXL, SD3.5, and Midjourney v6.

Model Agreement

39%

Variance across 6 ML detectors. Higher agreement means the models converged on the same reading; lower agreement means treat the verdict with care.

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.

ML Models6 detectors · mean 34
▸ expand
INA v2 (FLUX/MJ)
0
xRayon ConvNeXtV2
93
SigLIP AI Detector
14
CommFor (4803 Generators)
19
Bombek1 SigLIP+DINOv2
27
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 50
▸ expand
Color Distribution
17
Frequency Analysis
74
Error Level Analysis
28
Noise Pattern
63
Compression Quality
60
Pixel Analysis
57
Edge Consistency
49
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
C2PA Provenance
50
Metadata
50

Image Quality

Dimensions
1254 × 1254 px
Aspect
1.000
File size
3.38 MB
Bytes / pixel
2.255

Frequency Analysis

Radial1.000
DCT0.802
Upsampling1.000
Cross-channel0.147
Power-law β
-3.42
Grid energy
0.298

Edge Consistency

CV 0.521
Cell 1: 4.1259Cell 2: 12.6146Cell 3: 18.6938Cell 4: 12.2734Cell 5: 14.9963Cell 6: 10.5397Cell 7: 6.3698Cell 8: 4.7183Cell 9: 11.5244Cell 10: 12.0987Cell 11: 24.6515Cell 12: 28.9574Cell 13: 8.7297Cell 14: 11.0097Cell 15: 15.4316Cell 16: 27.7015

Per-region edge density (4 × 4 grid). Uneven distribution may indicate localized editing or splicing; uniform fields are typical of fully synthetic outputs.

Range: 4.125928.9574

Noise Fingerprint

Variance
89.07
Std deviation
9.44
Mean
-0.0
Spatial corr.
3.470
Mean Δ
2.07
σ
2.25
CV
1.087
Uniformity
-0.087

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 19, 2026, 4:24 PM
Analyzed by@muzip