ZONN.ai Forensic Report

Case · D4CD80EB · IMAGE

ZAnalyzed by@zonner
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 · 49/100

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

  • 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

52%

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 82
▸ expand
SigLIP AI Detector
100
INA v2 (FLUX/MJ)
100
xRayon ConvNeXtV2
98
Bombek1 SigLIP+DINOv2
97
CommFor (4803 Generators)
45
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 51
▸ expand
Error Level Analysis
12
Noise Pattern
82
Frequency Analysis
77
Color Distribution
37
Edge Consistency
41
Pixel Analysis
57
Compression Quality
53
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
82.2 KB
Bytes / pixel
0.080

Frequency Analysis

Radial1.000
DCT0.847
Upsampling1.000
Cross-channel0.221
Power-law β
-3.49
Grid energy
0.229

Edge Consistency

CV 0.782
Cell 1: 1.7280Cell 2: 8.9692Cell 3: 5.0804Cell 4: 1.7277Cell 5: 1.9080Cell 6: 7.3809Cell 7: 17.4224Cell 8: 1.7781Cell 9: 1.8336Cell 10: 5.7806Cell 11: 6.8693Cell 12: 1.7894Cell 13: 6.5042Cell 14: 11.8446Cell 15: 19.1463Cell 16: 10.2271

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

Range: 1.727719.1463

Noise Fingerprint

Variance
44.72
Std deviation
6.69
Mean
0.0
Spatial corr.
1.666
Mean Δ
1.49
σ
1.96
CV
1.317
Uniformity
-0.317

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 16, 2026, 10:55 AM
Analyzed by@zonner