ZONN.ai Forensic Report

Case · 7A71399B · IMAGE

MAnalyzed by@muzip
ZONN Analysis
0

Probably AI-generated

More signals lean toward AI generation than real, but some give weaker readings. Treat with caution.

Signal ConfidenceLimited · 49/100

Analysed Specimen

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

Heads up — 3 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.

ML detectors disagree with each other

Note

2 models confidently say "AI" (Itsnotai V2, Xrayon Convnext) while 3 confidently say "real" (Ml Python Siglip, Ml Commfor, Bombek1). This image sits at the edge of what ML can decide — manual review is recommended.

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 (9–100). 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)flagged AI · 100/100

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

  • xRayon ConvNeXtV2flagged AI · 97/100

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

Model Agreement

27%

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 50
▸ expand
INA v2 (FLUX/MJ)
100
xRayon ConvNeXtV2
97
SigLIP AI Detector
9
Bombek1 SigLIP+DINOv2
19
CommFor (4803 Generators)
25
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 40
▸ expand
Color Distribution
8
Noise Pattern
29
Frequency Analysis
71
Pixel Analysis
35
Error Level Analysis
37
Edge Consistency
55
Compression Quality
48
Provenance & Metadata3 detectors · mean 45
▸ expand
ICC Profile
35
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
1080 × 591 px
Aspect
1.827
File size
151.8 KB
Bytes / pixel
0.243

Frequency Analysis

Radial1.000
DCT0.823
Upsampling1.000
Cross-channel0.013
Power-law β
-3.59
Grid energy
0.266

Edge Consistency

CV 0.394
Cell 1: 19.2307Cell 2: 18.4393Cell 3: 21.7997Cell 4: 18.3462Cell 5: 32.8605Cell 6: 20.0173Cell 7: 23.3998Cell 8: 24.4958Cell 9: 15.7761Cell 10: 11.0392Cell 11: 18.8723Cell 12: 21.3510Cell 13: 13.7590Cell 14: 11.2229Cell 15: 42.2794Cell 16: 38.4394

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

Range: 11.039242.2794

Noise Fingerprint

Variance
278.80
Std deviation
16.70
Mean
0.1
Spatial corr.
5.098
Mean Δ
1.84
σ
1.73
CV
0.939
Uniformity
0.061

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 25, 2026, 1:44 PM
Analyzed by@muzip