ZONN.ai Forensic Report

Case · 4DCC47E7 · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Inconclusive

Signals are mixed or weak. We can't tell with confidence — context, source, and your own judgement matter here.

Signal ConfidenceWeak · 28/100

Analysed Specimen

Analysed content
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.

Multiple detectors unreachable

Note

2 ML detectors did not respond (Ml Python Siglip, Ml Commfor). The verdict was computed with reduced evidence; reliability is lower than usual.

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).

Signals do not converge

Note

Score 48/100 lands in the middle of the inconclusive zone. Detectors did not agree on a story — review multiple lines of evidence below.

Weak overall confidence

Note

Aggregate verdict confidence is 28/100. Several detectors returned uncertain answers or were offline. Read the verdict as a guideline, not as a final answer.

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

  • Frequency Analysisflagged AI · 72/100

    Fast-Fourier inspection. Diffusion outputs leave periodic spectral peaks.

  • Color Distributionread real · 31/100

    Global color distribution shape vs natural-photo baselines.

Model Agreement

100%

Variance across 2 ML detectors. Higher agreement means the models converged on the same reading; lower agreement means treat the verdict with care.

Evidence — 12 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 Models2 detectors · mean 50
▸ expand
SigLIP AI Detector
50
CommFor (4803 Generators)
50
Pixel & Frequency Forensics7 detectors · mean 55
▸ expand
Frequency Analysis
72
Color Distribution
31
Noise Pattern
66
Error Level Analysis
37
Compression Quality
63
Edge Consistency
62
Pixel Analysis
57
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
1.79 MB
Bytes / pixel
1.789

Frequency Analysis

Radial1.000
DCT0.788
Upsampling1.000
Cross-channel0.088
Power-law β
-3.41
Grid energy
0.318

Edge Consistency

CV 0.275
Cell 1: 12.8950Cell 2: 16.2653Cell 3: 15.3176Cell 4: 11.7051Cell 5: 20.1201Cell 6: 14.9841Cell 7: 11.7297Cell 8: 17.1225Cell 9: 10.9598Cell 10: 16.6009Cell 11: 9.4260Cell 12: 19.7700Cell 13: 5.9957Cell 14: 20.7681Cell 15: 11.7896Cell 16: 14.1108

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

Range: 5.995720.7681

Noise Fingerprint

Variance
76.49
Std deviation
8.75
Mean
-0.0
Spatial corr.
3.468
Mean Δ
2.12
σ
2.01
CV
0.950
Uniformity
0.050

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 10, 2026, 10:41 AM
Analyzed byAnonymous