ZONN.ai Forensic Report

Case · 8D0742A6 · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Probably AI-generated

More signals lean toward AI generation than real, but some give weaker readings. Treat with caution.

Signal ConfidenceLimited · 43/100

Analysed Specimen

Original analysed image
Forensic suspicion heatmap
OriginalHeatmap
POS55/100
No flagged regions

Heads up — 2 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.

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).

ML detectors see this image differently

Note

ML scores span a wide range (15–99). Different architectures read different feature spaces; the majority vote strengthens the consensus, but no single model is fully reliable here.

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

  • INA v2 (FLUX/MJ)flagged AI · 99/100

    BEiT-Large dual-head classifier trained on FLUX, Midjourney, and real photo corpora.

  • SigLIP AI Detectorflagged AI · 96/100

    SigLIP visual-language model probing semantic vs perceptual coherence.

Model Agreement

38%

Variance across 6 ML detectors. Higher agreement means the models converged on the same reading; lower agreement means treat the verdict with care.

Evidence — 16 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 Models6 detectors · mean 57
▸ expand
INA v2 (FLUX/MJ)
99
SigLIP AI Detector
96
Bombek1 SigLIP+DINOv2
15
xRayon ConvNeXtV2
38
CommFor (4803 Generators)
41
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 44
▸ expand
Pixel Analysis
17
Error Level Analysis
17
Noise Pattern
80
Frequency Analysis
75
Color Distribution
26
Compression Quality
45
Edge Consistency
49
Provenance & Metadata3 detectors · mean 45
▸ expand
ICC Profile
35
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
884 × 1103 px
Aspect
0.801
File size
83.9 KB
Bytes / pixel
0.088

Frequency Analysis

Radial1.000
DCT0.825
Upsampling1.000
Cross-channel0.166
Power-law β
-3.63
Grid energy
0.263

Edge Consistency

CV 0.524
Cell 1: 3.2041Cell 2: 12.7687Cell 3: 9.0870Cell 4: 1.7441Cell 5: 5.6364Cell 6: 5.1207Cell 7: 16.4763Cell 8: 4.3598Cell 9: 4.7888Cell 10: 7.0204Cell 11: 5.5071Cell 12: 6.8102Cell 13: 5.6837Cell 14: 6.1371Cell 15: 5.2390Cell 16: 6.3546

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

Range: 1.744116.4763

Noise Fingerprint

Variance
51.91
Std deviation
7.20
Mean
-0.0
Spatial corr.
1.624
Mean Δ
1.40
σ
1.75
CV
1.252
Uniformity
-0.252

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 30, 2026, 1:52 PM
Analyzed byAnonymous