ZONN.ai Forensic Report

Case · 15A219D0 · IMAGE

WAnalyzed by@walena
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 · 50/100

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

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

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

  • INA v2 (FLUX/MJ)read real · 0/100

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

Model Agreement

64%

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 16
▸ expand
CommFor (4803 Generators)
0
INA v2 (FLUX/MJ)
0
xRayon ConvNeXtV2
2
SigLIP AI Detector
16
Bombek1 SigLIP+DINOv2
26
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 44
▸ expand
Color Distribution
16
Error Level Analysis
25
Frequency Analysis
71
Noise Pattern
32
Pixel Analysis
57
Compression Quality
55
Edge Consistency
51
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
513 × 540 px
Aspect
0.950
File size
506.3 KB
Bytes / pixel
1.872

Frequency Analysis

Radial1.000
DCT0.769
Upsampling1.000
Cross-channel0.054
Power-law β
-3.28
Grid energy
0.347

Edge Consistency

CV 0.487
Cell 1: 5.9256Cell 2: 13.7571Cell 3: 14.7157Cell 4: 15.2016Cell 5: 3.2280Cell 6: 15.8755Cell 7: 13.5743Cell 8: 5.2545Cell 9: 29.3809Cell 10: 31.4579Cell 11: 28.4313Cell 12: 17.8447Cell 13: 32.8455Cell 14: 23.9876Cell 15: 22.5964Cell 16: 25.1021

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

Range: 3.228032.8455

Noise Fingerprint

Variance
195.48
Std deviation
13.98
Mean
0.0
Spatial corr.
4.501
Mean Δ
1.72
σ
1.94
CV
1.132
Uniformity
-0.132

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnJun 13, 2026, 5:55 AM
Analyzed by@walena