ZONN.ai Forensic Report

Case · 2D93FCC6 · 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 · 51/100

Analysed Specimen

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

Heads up — 5 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 73/100) 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.

No metadata at all

AI evidence

The file has no EXIF, XMP, IPTC, or ICC metadata. This is common for social-media re-uploads and for many generator outputs — real camera files almost always carry an ICC profile.

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 (0–97). Different architectures read different feature spaces; the majority vote strengthens the consensus, but no single model is fully reliable here.

No ICC color profile

AI evidence

The image does not embed an ICC color profile. Real camera files almost always carry sRGB or Adobe RGB profiles — a missing profile is often a sign of generator output or re-encoded media.

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 · 2/100

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

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 32
▸ expand
INA v2 (FLUX/MJ)
0
xRayon ConvNeXtV2
2
SigLIP AI Detector
97
Bombek1 SigLIP+DINOv2
4
CommFor (4803 Generators)
40
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 52
▸ expand
Noise Pattern
96
Color Distribution
20
Frequency Analysis
73
Pixel Analysis
35
Error Level Analysis
36
Edge Consistency
58
Compression Quality
45
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
1500 × 500 px
Aspect
3.000
File size
84.0 KB
Bytes / pixel
0.115

Frequency Analysis

Radial1.000
DCT0.886
Upsampling1.000
Cross-channel0.035
Power-law β
-4.11
Grid energy
0.171

Edge Consistency

CV 0.340
Cell 1: 6.2188Cell 2: 5.5021Cell 3: 4.2598Cell 4: 3.1937Cell 5: 4.5603Cell 6: 3.2326Cell 7: 2.7981Cell 8: 2.3206Cell 9: 2.7477Cell 10: 1.9866Cell 11: 2.5223Cell 12: 2.4811Cell 13: 3.8124Cell 14: 3.2870Cell 15: 2.8392Cell 16: 2.5265

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

Range: 1.98666.2188

Noise Fingerprint

Variance
5.00
Std deviation
2.24
Mean
-0.0
Spatial corr.
0.749
Mean Δ
0.95
σ
0.91
CV
0.956
Uniformity
0.044

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 20, 2026, 4:49 PM
Analyzed by@muzip