ZONN.ai Forensic Report

Case · 8461E428 · IMAGE

Analyzed byAnonymous
ZONN Analysis
0

Very likely real

Most signals point to a real, human-captured source. Detection tools are not perfect — treat this as a strong indication, not a verdict.

Signal ConfidenceLimited · 42/100

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.

AI generator fingerprints detected

AI evidence

Frequency analysis (FFT score 68/100) shows modern diffusion-style upsampling patterns, but the ML models say "real". This combination is a known blind spot for newer generators (SDXL, FLUX, Midjourney v6) — the verdict above may be misleading.

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).

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)read real · 0/100

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

  • Error Level Analysisread real · 1/100

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

Model Agreement

55%

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 31
▸ expand
INA v2 (FLUX/MJ)
0
Bombek1 SigLIP+DINOv2
10
SigLIP AI Detector
26
CommFor (4803 Generators)
31
xRayon ConvNeXtV2
67
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 51
▸ expand
Error Level Analysis
1
Noise Pattern
78
Pixel Analysis
75
Frequency Analysis
68
Color Distribution
36
Compression Quality
48
Edge Consistency
52
Provenance & Metadata3 detectors · mean 54
▸ expand
ICC Profile
62
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
492 × 624 px
Aspect
0.788
File size
77.3 KB
Bytes / pixel
0.258

Frequency Analysis

Radial0.835
DCT0.712
Upsampling1.000
Cross-channel0.228
Power-law β
-2.59
Grid energy
0.433

Edge Consistency

CV 0.466
Cell 1: 7.7676Cell 2: 10.3563Cell 3: 6.4131Cell 4: 5.9776Cell 5: 8.0310Cell 6: 19.6077Cell 7: 14.1009Cell 8: 7.1067Cell 9: 8.0538Cell 10: 13.7239Cell 11: 12.2244Cell 12: 6.7968Cell 13: 5.7971Cell 14: 5.7894Cell 15: 3.2982Cell 16: 5.2887

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

Range: 3.298219.6077

Noise Fingerprint

Variance
53.14
Std deviation
7.29
Mean
0.0
Spatial corr.
2.170
Mean Δ
1.74
σ
2.57
CV
1.478
Uniformity
-0.478

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 16, 2026, 11:16 PM
Analyzed byAnonymous