ZONN.ai Forensic Report

Case · 0F3A6C40 · IMAGE

XAnalyzed by@xrex
ZONN Analysis
0

Probably AI-generated

More signals lean toward AI generation than real, but some give weaker readings. Treat with caution.

Signal ConfidenceLimited · 48/100

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.

ML detectors disagree with each other

Note

2 models confidently say "AI" (Ml Python Siglip, Itsnotai V2) while 3 confidently say "real" (Ml Commfor, Xrayon Convnext, Bombek1). This image sits at the edge of what ML can decide — manual review is recommended.

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 (3–94). 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

  • xRayon ConvNeXtV2read real · 3/100

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

  • INA v2 (FLUX/MJ)flagged AI · 94/100

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

Model Agreement

29%

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 48
▸ expand
xRayon ConvNeXtV2
3
INA v2 (FLUX/MJ)
94
SigLIP AI Detector
93
CommFor (4803 Generators)
22
Bombek1 SigLIP+DINOv2
23
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 54
▸ expand
Noise Pattern
87
Frequency Analysis
76
Color Distribution
29
Error Level Analysis
33
Edge Consistency
58
Pixel Analysis
45
Compression Quality
53
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

AI-typical dimensions
Dimensions
2048 × 2048 px
Aspect
1.000
File size
345.7 KB
Bytes / pixel
0.084

Frequency Analysis

Radial1.000
DCT0.812
Upsampling1.000
Cross-channel0.211
Power-law β
-3.64
Grid energy
0.282

Edge Consistency

CV 0.341
Cell 1: 6.4280Cell 2: 6.0679Cell 3: 12.6736Cell 4: 3.2652Cell 5: 8.0453Cell 6: 10.1512Cell 7: 6.4629Cell 8: 5.0995Cell 9: 12.9317Cell 10: 9.7603Cell 11: 7.0667Cell 12: 6.3440Cell 13: 8.3652Cell 14: 9.4601Cell 15: 5.2418Cell 16: 5.7435

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

Range: 3.265212.9317

Noise Fingerprint

Variance
22.14
Std deviation
4.71
Mean
-0.0
Spatial corr.
1.895
Mean Δ
1.65
σ
1.65
CV
1.000
Uniformity
0.000

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnJul 14, 2026, 5:39 PM
Analyzed by@xrex