ZONN.ai Forensic Report

Case · 0D8DC4A2 · 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 · 48/100

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 72/100) 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 · 4/100

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

  • Noise Patternflagged AI · 95/100

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

Model Agreement

68%

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 20
▸ expand
INA v2 (FLUX/MJ)
4
Bombek1 SigLIP+DINOv2
6
CommFor (4803 Generators)
8
SigLIP AI Detector
20
xRayon ConvNeXtV2
29
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 50
▸ expand
Noise Pattern
95
Color Distribution
10
Error Level Analysis
24
Frequency Analysis
72
Pixel Analysis
45
Edge Consistency
53
Compression Quality
50
Provenance & Metadata3 detectors · mean 45
▸ expand
ICC Profile
35
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
400 × 400 px
Aspect
1.000
File size
21.6 KB
Bytes / pixel
0.138

Frequency Analysis

Radial1.000
DCT0.853
Upsampling1.000
Cross-channel0.012
Power-law β
-3.85
Grid energy
0.221

Edge Consistency

CV 0.433
Cell 1: 3.1521Cell 2: 5.9434Cell 3: 5.8936Cell 4: 0.7782Cell 5: 3.8640Cell 6: 3.0168Cell 7: 3.5816Cell 8: 2.3674Cell 9: 3.2205Cell 10: 2.2672Cell 11: 2.5607Cell 12: 3.9653Cell 13: 3.3817Cell 14: 2.4193Cell 15: 2.5320Cell 16: 6.7729

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

Range: 0.77826.7729

Noise Fingerprint

Variance
8.32
Std deviation
2.88
Mean
-0.0
Spatial corr.
0.754
Mean Δ
0.82
σ
0.93
CV
1.134
Uniformity
-0.134

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 29, 2026, 7:57 PM
Analyzed byAnonymous