ZONN.ai Forensic Report

Case · 8C561D46 · 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 · 41/100

Analysed Specimen

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

Heads up — 3 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.

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).

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

  • xRayon ConvNeXtV2flagged AI · 97/100

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

  • SigLIP AI Detectorread real · 9/100

    SigLIP visual-language model probing semantic vs perceptual coherence.

Model Agreement

43%

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 41
▸ expand
xRayon ConvNeXtV2
97
SigLIP AI Detector
9
INA v2 (FLUX/MJ)
24
Bombek1 SigLIP+DINOv2
25
CommFor (4803 Generators)
39
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 47
▸ expand
Color Distribution
25
Frequency Analysis
73
Pixel Analysis
35
Error Level Analysis
36
Noise Pattern
63
Compression Quality
43
Edge Consistency
57
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

AI-typical dimensions
Dimensions
1536 × 1024 px
Aspect
1.500
File size
226.1 KB
Bytes / pixel
0.147

Frequency Analysis

Radial1.000
DCT0.826
Upsampling1.000
Cross-channel0.082
Power-law β
-3.47
Grid energy
0.262

Edge Consistency

CV 0.363
Cell 1: 9.4514Cell 2: 5.4476Cell 3: 6.4501Cell 4: 7.1537Cell 5: 11.4199Cell 6: 13.3355Cell 7: 13.1838Cell 8: 10.3490Cell 9: 8.5781Cell 10: 12.0961Cell 11: 19.2402Cell 12: 9.4540Cell 13: 16.8580Cell 14: 16.4256Cell 15: 18.1029Cell 16: 19.7911

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

Range: 5.447619.7911

Noise Fingerprint

Variance
99.51
Std deviation
9.98
Mean
-0.0
Spatial corr.
2.833
Mean Δ
2.12
σ
2.03
CV
0.956
Uniformity
0.044

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 27, 2026, 7:07 PM
Analyzed by@muzip