ZONN.ai Forensic Report

Case · D8AB2FBF · IMAGE

AAnalyzed by@aivampire
ZONN Analysis
0

Probably real

More signals lean toward real than AI, but some give weaker readings. Worth a second look on close inspection.

Signal ConfidenceWeak · 28/100

Analysed Specimen

Analysed content
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.

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).

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

  • Error Level Analysisread real · 2/100

    Error Level Analysis. Re-saves and diffs to expose uneven compression regions.

  • Pixel Analysisread real · 17/100

    Low-level pixel statistics: saturation cliffs, channel histograms, banding.

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 44
▸ expand
Error Level Analysis
2
Pixel Analysis
17
Frequency Analysis
71
Noise Pattern
66
Color Distribution
40
Edge Consistency
59
Compression Quality
55
Provenance & Metadata3 detectors · mean 58
▸ expand
Metadata
62
ICC Profile
62
C2PA Provenance
50

Image Quality

Dimensions
1254 × 1254 px
Aspect
1.000
File size
1.04 MB
Bytes / pixel
0.693

Frequency Analysis

Radial1.000
DCT0.837
Upsampling1.000
Cross-channel0.020
Power-law β
-3.66
Grid energy
0.245

Edge Consistency

CV 0.325
Cell 1: 4.4349Cell 2: 9.0484Cell 3: 8.8265Cell 4: 4.3673Cell 5: 7.5633Cell 6: 12.0674Cell 7: 11.7360Cell 8: 9.1704Cell 9: 8.9722Cell 10: 11.8767Cell 11: 11.3390Cell 12: 9.6014Cell 13: 4.3425Cell 14: 7.1251Cell 15: 7.6994Cell 16: 4.2959

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

Range: 4.295912.0674

Noise Fingerprint

Variance
100.86
Std deviation
10.04
Mean
0.0
Spatial corr.
2.105
Mean Δ
0.96
σ
1.42
CV
1.470
Uniformity
-0.470

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 10, 2026, 2:41 PM
Analyzed by@aivampire