ZONN.ai Forensic Report

Case · A0EF1E5A · 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 ConfidenceLimited · 50/100

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.

ML detectors see this image differently

Note

ML scores span a wide range (2–91). Different architectures read different feature spaces; the majority vote strengthens the consensus, but no single model is fully reliable here.

Photo-editor traces in metadata

Note

The file carries traces of a photo editor (Adobe Photoshop, Adobe Lightroom). The image has been edited at some point — this can mean a retouched real photo or AI-generated then post-processed.

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

  • CommFor (4803 Generators)read real · 2/100

    CommFor detector trained across 4,803 generator variants for broad coverage.

  • xRayon ConvNeXtV2read real · 3/100

    ConvNeXtV2 detector trained on FLUX, DALL-E 3, SDXL, SD3.5, and Midjourney v6.

Model Agreement

34%

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 28
▸ expand
CommFor (4803 Generators)
2
xRayon ConvNeXtV2
3
SigLIP AI Detector
5
INA v2 (FLUX/MJ)
91
Bombek1 SigLIP+DINOv2
15
Manipulation Map (IML-ViT)
50
Pixel & Frequency Forensics7 detectors · mean 39
▸ expand
Color Distribution
10
Noise Pattern
22
Error Level Analysis
40
Frequency Analysis
41
Pixel Analysis
57
Edge Consistency
51
Compression Quality
50
Provenance & Metadata3 detectors · mean 45
▸ expand
ICC Profile
35
Metadata
50
C2PA Provenance
50

Image Quality

Dimensions
377 × 624 px
Aspect
0.604
File size
107.2 KB
Bytes / pixel
0.466

Frequency Analysis

Radial0.318
DCT0.586
Upsampling1.000
Cross-channel0.018
Power-law β
-2.07
Grid energy
0.621

Edge Consistency

CV 0.475
Cell 1: 8.7404Cell 2: 38.3769Cell 3: 23.2514Cell 4: 8.5959Cell 5: 15.4700Cell 6: 52.6165Cell 7: 37.0868Cell 8: 13.4646Cell 9: 23.6821Cell 10: 35.5071Cell 11: 46.4294Cell 12: 21.6378Cell 13: 26.8630Cell 14: 44.1974Cell 15: 37.9309Cell 16: 17.3229

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

Range: 8.595952.6165

Noise Fingerprint

Variance
248.81
Std deviation
15.77
Mean
-0.0
Spatial corr.
6.790
Mean Δ
2.38
σ
2.14
CV
0.899
Uniformity
0.101

Provenance

Source Dossier

PlatformDirect upload
Author
Content Typeimage
Analyzed OnMay 14, 2026, 6:17 PM
Analyzed byAnonymous