ZONN.ai Forensic Report

Case · C92B2BF9 · 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 · 31/100

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 49/100 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 31/100. 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

  • Noise Patternflagged AI · 97/100

    Sensor-noise (PRNU) fingerprint check. Real cameras leave camera-unique noise.

  • Color Distributionread real · 10/100

    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 57
▸ expand
Noise Pattern
97
Color Distribution
10
Frequency Analysis
83
Edge Consistency
75
Error Level Analysis
35
Pixel Analysis
57
Compression Quality
43
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
5120 × 2880 px
Aspect
1.778
File size
4.82 MB
Bytes / pixel
0.342

Frequency Analysis

Radial1.000
DCT0.762
Upsampling1.000
Cross-channel0.568
Power-law β
-3.56
Grid energy
0.358

Edge Consistency

CV 0.130
Cell 1: 2.3322Cell 2: 2.4197Cell 3: 2.3486Cell 4: 2.4303Cell 5: 2.4141Cell 6: 2.3717Cell 7: 2.4522Cell 8: 2.5622Cell 9: 2.8708Cell 10: 3.1773Cell 11: 3.0370Cell 12: 3.1585Cell 13: 2.7942Cell 14: 3.0655Cell 15: 3.1497Cell 16: 3.3973

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

Range: 2.33223.3973

Noise Fingerprint

Variance
1.56
Std deviation
1.25
Mean
0.0
Spatial corr.
0.684
Mean Δ
1.06
σ
1.03
CV
0.976
Uniformity
0.024

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 11, 2026, 8:48 PM
Analyzed byAnonymous