Stop guessing if an image is real. Start understanding it.

SignalLens analyzes images using multiple forensic signals and produces a clear, explainable reasoning trace — Runs locally. Images do not need to leave your machine.

SignalLens
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SignalLens

Beta Available for Download

Current version: SignalLens 0.0.1-beta
Platform: Windows
Package type: portable ZIP
Code signing: unsigned beta build  

SHA256 checksum: E8F6751FE1C31CE11CBC87350AEDACF168207546192138359CA226ECC5530720

SignalLens
SignalLens
Size: 338 MB
Version: 0.0.1 beta
Download33 Downloads

Who is this for?

Built for: OSINT researchers, journalists, investigators, creators, platform reviewers, and anyone who needs to understand whether an image is real, edited, synthetic, or ambiguous. This beta is best suited for users who are comfortable testing software and inspecting local output folders.

Why SignalLens Exists

As synthetic media improves, even authentic photographs are increasingly being mistaken for AI-generated imagery.
Major news organizations now devote significant editorial effort to image verification, while simplistic detector scores continue to produce unreliable and conflicting results.
SignalLens was created to explore a more explainable forensic approach.

SignalLens - Local Visual Forensics

We’ve lost the ability to trust what we see:

AI images are no longer obviously fake. Real images are edited, filtered, and enhanced.

Tools respond with a single number: AI-generated: 87% That’s not evidence. That’s a guess.

A different approach

SignalLens doesn’t guess.
It analyzes.
  • Extracts multiple forensic signals
  • Interprets them using structured reasoning
  • Produces clear, human-readable explanations

SignalLens Architecture

SignalLens is used for:
• Investigating suspicious images
• Verifying online content
• Understanding AI vs real ambiguity
• Exploring how images are constructed

You don’t just get a score. You get the evidence behind the conclusion.

SignalLens does not only show a verdict: Full Forensic Evidence Package

Every analysis creates a local audit trail SignalLens stores overlays, heatmaps, masks, FFT outputs, metadata signals, JSON results, logs, summaries, and a reasoning trace under .\analyzed\

The output includes:

  • Dedicated Folders: Logs, prepared images, and summaries.
  • Generated Artifacts:
    • ELA overlays and FFT spectra
    • Patch heatmaps and boundary masks
    • Subject and region masks
    • JSON signal files and HTML summaries
    • Complete reasoning traces

signallens
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