ZONN.ai Forensic Report

Case · 4FC31E7F · 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 · 43/100

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 (15–100). 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.

  • CommFor (4803 Generators)read real · 15/100

    CommFor detector trained across 4,803 generator variants for broad coverage.

Model Agreement

41%

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 46
▸ expand
INA v2 (FLUX/MJ)
100
CommFor (4803 Generators)
15
xRayon ConvNeXtV2
19
Bombek1 SigLIP+DINOv2
29
SigLIP AI Detector
63
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 47
▸ expand
Color Distribution
18
Error Level Analysis
20
Noise Pattern
79
Frequency Analysis
76
Pixel Analysis
35
Edge Consistency
58
Compression Quality
45
Provenance & Metadata3 detectors · mean 45
▸ expand
ICC Profile
35
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
1080 × 1105 px
Aspect
0.977
File size
124.4 KB
Bytes / pixel
0.107

Frequency Analysis

Radial1.000
DCT0.839
Upsampling1.000
Cross-channel0.197
Power-law β
-3.73
Grid energy
0.242

Edge Consistency

CV 0.346
Cell 1: 6.1925Cell 2: 4.9255Cell 3: 12.5831Cell 4: 3.6517Cell 5: 10.3750Cell 6: 7.9390Cell 7: 11.0004Cell 8: 11.9727Cell 9: 8.1312Cell 10: 8.6798Cell 11: 7.8008Cell 12: 5.5535Cell 13: 4.8792Cell 14: 5.4081Cell 15: 6.3527Cell 16: 5.9249

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

Range: 3.651712.5831

Noise Fingerprint

Variance
53.74
Std deviation
7.33
Mean
-0.0
Spatial corr.
1.774
Mean Δ
1.56
σ
1.87
CV
1.196
Uniformity
-0.196

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 25, 2026, 2:03 PM
Analyzed by@muzip