ZONN.ai Forensic Report

Case · C0E5EFB8 · IMAGE

VAnalyzed by@vxqxqxq
ZONN Analysis
0

Very likely real

Most signals point to a real, human-captured source. Detection tools are not perfect — treat this as a strong indication, not a verdict.

Signal ConfidenceLimited · 47/100

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.

AI generator fingerprints detected

AI evidence

Frequency analysis (FFT score 71/100) shows modern diffusion-style upsampling patterns, but the ML models say "real". This combination is a known blind spot for newer generators (SDXL, FLUX, Midjourney v6) — the verdict above may be misleading.

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).

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 ConvNeXtV2read real · 3/100

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

Model Agreement

56%

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 19
▸ expand
INA v2 (FLUX/MJ)
0
xRayon ConvNeXtV2
3
SigLIP AI Detector
5
Bombek1 SigLIP+DINOv2
5
CommFor (4803 Generators)
49
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 47
▸ expand
Color Distribution
19
Noise Pattern
73
Frequency Analysis
71
Error Level Analysis
32
Pixel Analysis
35
Compression Quality
45
Edge Consistency
51
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
640 × 960 px
Aspect
0.667
File size
84.4 KB
Bytes / pixel
0.141

Frequency Analysis

Radial1.000
DCT0.815
Upsampling1.000
Cross-channel0.032
Power-law β
-3.44
Grid energy
0.278

Edge Consistency

CV 0.487
Cell 1: 6.0554Cell 2: 9.6826Cell 3: 17.2744Cell 4: 9.7972Cell 5: 3.3435Cell 6: 8.4862Cell 7: 13.6491Cell 8: 7.2798Cell 9: 4.7659Cell 10: 13.2794Cell 11: 7.9034Cell 12: 5.7376Cell 13: 23.8428Cell 14: 14.5029Cell 15: 11.9406Cell 16: 8.9832

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

Range: 3.343523.8428

Noise Fingerprint

Variance
65.95
Std deviation
8.12
Mean
-0.0
Spatial corr.
2.485
Mean Δ
1.69
σ
1.74
CV
1.026
Uniformity
-0.026

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnAug 30, 2026, 11:26 PM
Analyzed by@vxqxqxq