ZONN.ai Forensic Report

Case · 61553485 · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Very likely AI-generated

Most signals point to AI generation. Detection tools are not perfect — treat this as a strong indication, not a verdict.

Signal ConfidenceLimited · 51/100

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 (0–100). 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

  • CommFor (4803 Generators)read real · 0/100

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

  • INA v2 (FLUX/MJ)flagged AI · 100/100

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

Model Agreement

30%

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 69
▸ expand
CommFor (4803 Generators)
0
INA v2 (FLUX/MJ)
100
xRayon ConvNeXtV2
98
SigLIP AI Detector
90
Bombek1 SigLIP+DINOv2
76
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 49
▸ expand
Color Distribution
17
Noise Pattern
78
Error Level Analysis
25
Frequency Analysis
75
Compression Quality
56
Pixel Analysis
45
Edge Consistency
47
Provenance & Metadata3 detectors · mean 45
▸ expand
ICC Profile
35
Metadata
50
C2PA Provenance
50

Image Quality

AI-typical dimensions
Dimensions
1024 × 1024 px
Aspect
1.000
File size
394.9 KB
Bytes / pixel
0.386

Frequency Analysis

Radial1.000
DCT0.869
Upsampling1.000
Cross-channel0.129
Power-law β
-4.00
Grid energy
0.196

Edge Consistency

CV 0.597
Cell 1: 3.5169Cell 2: 2.2478Cell 3: 4.6451Cell 4: 5.5028Cell 5: 3.0715Cell 6: 2.6147Cell 7: 11.2689Cell 8: 6.3571Cell 9: 7.5620Cell 10: 6.7692Cell 11: 13.7419Cell 12: 14.1696Cell 13: 9.1000Cell 14: 12.7168Cell 15: 20.5823Cell 16: 8.6942

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

Range: 2.247820.5823

Noise Fingerprint

Variance
56.70
Std deviation
7.53
Mean
0.0
Spatial corr.
1.925
Mean Δ
1.46
σ
1.63
CV
1.118
Uniformity
-0.118

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 15, 2026, 8:24 AM
Analyzed byAnonymous