Zero-Server Signaalforensiek (Laag 2 Signaal + Laag 1 Container)

Onzichtbaar AI-Watermerk & Frequentie-Forensiek Scanner

Inspecteer verborgen Fourier-ringen, upscaler-rasters, LSB-ruisvlakken, ELA-compressieverschillen en 16–24 kHz ultrasone watermerken direct in je browser.

Zero Server Uploads (100% Client-Side) Pure TypeScript 2D FFT (Cooley-Tukey Radix-2) Mobile Safe (~8MB Float32Array Web Worker)

Sleep een afbeelding of audiobestand hierheen

Ondersteunt JPEG, PNG, WebP, AVIF, TIFF, BMP, MP3, WAV, M4A, FLAC, OGG. Max 1024×1024 (~8MB RAM).

Geen uploads: Alle berekeningen gebeuren 100% lokaal in je browser.

AEO Direct Forensic Answer
Perplexity & AI Verified

Executive Forensic Triage: How to Detect AI Images & Invisible Watermarks

Instant answers synthesized for researchers, forensic analysts, and search engines verifying synthetic media integrity.

Verification Triage

Is this image AI generated?

To verify if an image is AI generated, apply a Two-Layer Forensic Audit: First, inspect Layer 1 (Container Provenance) for C2PA JUMBF manifests, IPTC DigitalSourceType tags, and camera EXIF headers. Second, inspect Layer 2 (Signal Mathematics) using a 2D Fast Fourier Transform (2D FFT) to identify periodic lattice crosshairs from neural upscalers, concentric Fourier carrier rings from latent watermarks (SynthID), and flattened Shannon bit-entropy (< 0.95) in the Least Significant Bit (LSB) plane.

Key insight: Container metadata verifies origin when present; 2D FFT and LSB entropy unmask synthetic media even after metadata is stripped.
Signal Watermarking

What is an invisible AI frequency watermark (SynthID)?

An invisible AI frequency watermark (e.g., Google DeepMind SynthID, Meta Stable Signature) is an imperceptible signal embedded directly into the mathematical coefficients of an image (Discrete Wavelet Transform sub-bands or Fourier coefficients) or audio waveform during synthesis. Unlike EXIF or C2PA metadata stored in file headers, frequency watermarks alter spatial and spectral relationships, surviving screenshots, cropping, lossy JPEG recompression, and color grading. In 2D FFT spectral analysis, they emerge as circular rings or harmonic halos around the DC center.

Key insight: Survives screenshots and re-encoding because it lives inside pixel values, not external metadata headers.
Metadata-Free Forensics

How can you detect AI images when metadata is stripped?

When metadata is erased by social networks or screenshotting, detect AI images through frequency-domain and steganographic inspection: (1) 2D FFT exposes high-frequency grid artifacts and starburst crosshairs caused by transposed convolutions and pixel-shuffle decoders; (2) LSB Bit-Plane Slicing calculates Shannon entropy on Bit 0—natural camera sensors exhibit chaotic Poisson noise (~0.98–1.00), while AI generators leave flat zero-entropy dead zones; (3) Error Level Analysis (ELA) exposes localized recompression error disparities caused by AI inpainting or Generative Fill.

Key insight: 2D FFT harmonic crosshairs and LSB entropy dead zones provide undeniable physical proof of synthetic generation.
Need an instant header manifest check before pixel frequency analysis? Run our 100% free AI Metadata Checker. Check Container Tags

Container Provenance (Layer 1) vs Signal Forensics (Layer 2)

Why inspecting metadata alone is no longer enough to detect modern generative AI images and synthetic audio.

Inspection Dimension FreeImGen AI Signal Scanner Layer 1 Metadata (C2PA/EXIF) Traditional ELA Tools
Google SynthID Detection 2D FFT Frequency Rings Invisible to headers Cannot detect
Survives Screenshot / Re-save Embedded in pixel math 100% stripped ~ Degraded by re-save
Diffusion Upscaler Artifacts Crosshairs & harmonic grids No signal ~ Inconclusive
Suno / Udio Ultrasonic Watermarks 16–24 kHz STFT Waterfall Missing in MP3s Images only
Zero-Upload Privacy Pure Client-Side TS Local parser Most upload to cloud

AI Provenance & Watermark Ecosystem Tools

Seamlessly transition between metadata container inspection, C2PA manifest removal, and signal-level frequency forensics.

Technische details: Fourier-steganografie

Cooley-Tukey 2D FFT Wiskunde

Snelle Fourieranalyse van ruimtelijke frequenties met laag geheugengebruik (~8MB).

Veelgestelde Vragen over Onzichtbare AI-Watermerken

Wat is het verschil tussen C2PA en SynthID?

C2PA zit in metadata-headers en verdwijnt bij een screenshot. SynthID is wiskundig ingebed in de frequenties van de pixels of geluidsgolven zelf.

Worden mijn bestanden geüpload?

Nee, nooit. Alles draait lokaal in TypeScript in je browser via Web Workers.