ZONN.ai Forensic Report

Case · 245181C9 · 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 · 29/100

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.

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.

Just above the real threshold

Note

The score (43/100) is between real (40) and inconclusive. There is not enough confidence to call this a clean "real" verdict.

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).

Weak overall confidence

Note

Aggregate verdict confidence is 29/100. 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 Patternread real · 14/100

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

  • Color Distributionread real · 27/100

    Global color distribution shape vs natural-photo baselines.

Model Agreement

100%

Variance across 3 ML detectors. Higher agreement means the models converged on the same reading; lower agreement means treat the verdict with care.

Evidence — 13 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 Models3 detectors · mean 50
▸ expand
SigLIP AI Detector
50
CommFor (4803 Generators)
50
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 41
▸ expand
Noise Pattern
14
Color Distribution
27
Frequency Analysis
72
Pixel Analysis
35
Error Level Analysis
35
Edge Consistency
59
Compression Quality
48
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
1086 × 1448 px
Aspect
0.750
File size
368.8 KB
Bytes / pixel
0.240

Frequency Analysis

Radial1.000
DCT0.732
Upsampling1.000
Cross-channel0.166
Power-law β
-2.75
Grid energy
0.402

Edge Consistency

CV 0.325
Cell 1: 21.0798Cell 2: 39.1120Cell 3: 50.5183Cell 4: 18.9822Cell 5: 24.9147Cell 6: 32.8832Cell 7: 22.3781Cell 8: 13.7719Cell 9: 39.2528Cell 10: 40.5137Cell 11: 47.6554Cell 12: 35.9634Cell 13: 50.0266Cell 14: 35.0800Cell 15: 45.4404Cell 16: 46.5857

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

Range: 13.771950.5183

Noise Fingerprint

Variance
329.38
Std deviation
18.15
Mean
-0.0
Spatial corr.
8.631
Mean Δ
3.23
σ
3.16
CV
0.980
Uniformity
0.020

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 12, 2026, 8:38 PM
Analyzed byAnonymous