ZONN.ai Forensic Report

Case · 8041B4BB · IMAGE

Analyzed byAnonymous
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 · 26/100

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 26/100. 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 · 82/100

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

  • Error Level Analysisread real · 31/100

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

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 54
▸ expand
Frequency Analysis
82
Error Level Analysis
31
Color Distribution
36
Noise Pattern
62
Pixel Analysis
57
Compression Quality
56
Edge Consistency
53
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
181.6 KB
Bytes / pixel
0.177

Frequency Analysis

Radial1.000
DCT0.785
Upsampling1.000
Cross-channel0.508
Power-law β
-3.04
Grid energy
0.323

Edge Consistency

CV 0.445
Cell 1: 4.6646Cell 2: 21.6280Cell 3: 23.1831Cell 4: 4.5311Cell 5: 10.4865Cell 6: 24.8876Cell 7: 25.4459Cell 8: 9.3978Cell 9: 7.8568Cell 10: 14.9011Cell 11: 20.1635Cell 12: 17.3918Cell 13: 29.5757Cell 14: 27.1390Cell 15: 21.6526Cell 16: 24.1487

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

Range: 4.531129.5757

Noise Fingerprint

Variance
77.65
Std deviation
8.81
Mean
-0.0
Spatial corr.
4.411
Mean Δ
2.99
σ
3.10
CV
1.036
Uniformity
-0.036

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 10, 2026, 10:40 AM
Analyzed byAnonymous