ZONN.ai Forensic Report

Case · 75C2FB66 · IMAGE

MAnalyzed by@muzip
ZONN Analysis
0

Very likely AI-generated

Most signals point to AI generation. 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 — 4 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).

ML detectors see this image differently

Note

ML scores span a wide range (15–100). 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

  • SigLIP AI Detectorflagged AI · 100/100

    SigLIP visual-language model probing semantic vs perceptual coherence.

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

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

Model Agreement

36%

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 75
▸ expand
SigLIP AI Detector
100
INA v2 (FLUX/MJ)
100
xRayon ConvNeXtV2
97
Bombek1 SigLIP+DINOv2
86
CommFor (4803 Generators)
15
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 46
▸ expand
Color Distribution
28
Error Level Analysis
29
Frequency Analysis
71
Pixel Analysis
35
Compression Quality
56
Noise Pattern
55
Edge Consistency
45
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

AI-typical dimensions
Dimensions
1024 × 1024 px
Aspect
1.000
File size
177.7 KB
Bytes / pixel
0.174

Frequency Analysis

Radial1.000
DCT0.749
Upsampling1.000
Cross-channel0.090
Power-law β
-2.85
Grid energy
0.376

Edge Consistency

CV 0.643
Cell 1: 36.2583Cell 2: 4.8585Cell 3: 8.1981Cell 4: 45.8287Cell 5: 23.4515Cell 6: 4.7724Cell 7: 5.6946Cell 8: 33.6754Cell 9: 21.2421Cell 10: 15.1500Cell 11: 8.4547Cell 12: 14.5716Cell 13: 20.8813Cell 14: 28.3348Cell 15: 17.4516Cell 16: 8.9379

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

Range: 4.772445.8287

Noise Fingerprint

Variance
100.87
Std deviation
10.04
Mean
0.0
Spatial corr.
4.630
Mean Δ
2.20
σ
2.35
CV
1.068
Uniformity
-0.068

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 18, 2026, 5:16 PM
Analyzed by@muzip