ZONN.ai Forensic Report

Case · C15E8AC6 · 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 · 30/100

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 (42/100) 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 30/100. 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 · 93/100

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

  • Color Distributionread real · 9/100

    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 55
▸ expand
Noise Pattern
93
Color Distribution
9
Frequency Analysis
91
Error Level Analysis
34
Edge Consistency
59
Pixel Analysis
57
Compression Quality
43
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
2560 × 1440 px
Aspect
1.778
File size
722.9 KB
Bytes / pixel
0.201

Frequency Analysis

Radial1.000
DCT0.797
Upsampling1.000
Cross-channel0.839
Power-law β
-3.83
Grid energy
0.305

Edge Consistency

CV 0.319
Cell 1: 2.9754Cell 2: 2.7944Cell 3: 2.8414Cell 4: 2.8325Cell 5: 4.3656Cell 6: 4.4705Cell 7: 5.5477Cell 8: 6.2004Cell 9: 4.2394Cell 10: 5.6517Cell 11: 7.8162Cell 12: 4.5678Cell 13: 3.2643Cell 14: 3.4272Cell 15: 4.1678Cell 16: 3.6601

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

Range: 2.79447.8162

Noise Fingerprint

Variance
10.00
Std deviation
3.16
Mean
0.0
Spatial corr.
1.079
Mean Δ
1.65
σ
1.62
CV
0.983
Uniformity
0.017

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 11, 2026, 8:59 PM
Analyzed byAnonymous