Every image and video carries invisible forensic data — GPS coordinates, device fingerprints, editing history, and sometimes concealed payloads. Below are the six evidence categories our analysis pipeline surfaces. Curated real-world cases are being added now.
Our analysis pipeline examines photos and videos across seven distinct evidence layers — each with real-world privacy and authenticity implications. Cases demonstrating each category are being published now.
Smartphones embed precise latitude and longitude into every photo they capture. A single image can silently expose a home address, workplace, or the location of a private meeting — often without the photographer ever knowing it is there. Our analysis resolves GPS coordinates to named locations and flags proximity to sensitive sites.
JPEG files contain quantisation tables (DQT) unique to each camera model, sensor, and firmware revision. By matching these signatures against a database of thousands of devices, we detect mismatches between the claimed camera and the actual encoder — exposing re-encoding, software conversion, and AI-generated imagery masquerading as a real photograph.
Re-saving a JPEG after editing alters the local compression entropy in mathematically detectable ways. ELA maps these compression-level differences across the image, highlighting pasted regions, inserted objects, removed elements, and text overlays that carry a different error signature from the surrounding original content.
Photo editing software embeds author names, computer usernames, email addresses, and editing timestamps directly into image file headers. These fields frequently survive social media re-uploads and can reveal the real identity of an anonymous poster, the complete editing history of a manipulated image, or the organisation that produced it.
Inconsistencies between encoder fingerprints, quantisation profiles, colour spaces, and EXIF data indicate post-processing, format conversion, screenshot capture, or AI generation. Each mismatch type carries a specific forensic implication — from social media re-compression to deliberate metadata stripping — with a calibrated severity rating.
Steganography conceals data inside ordinary images or videos, hiding the very existence of the payload rather than just its meaning. Our proprietary detection engine identifies statistical anomalies consistent with LSB and frequency-domain hidden payloads — including Vaultify-encoded content — even when the file passes all standard format validation checks.
Multiple independent signals identify AI-generated images and video: frequency-domain patterns unique to AI image generators, C2PA provenance declarations from tools like DALL-E and Midjourney, absent camera metadata, and motion gradient statistics that deviate from real-camera physics for AI-generated video. When faces are present, each face is examined independently for signs of AI face-swapping and digital manipulation — surfacing alterations that survive visual inspection.
snapWONDERS is actively being expanded and modernised. We are preparing curated real-world cases — actual analysis results with full editorial commentary explaining exactly what was found and why it matters. The first cases below are in preparation now.
Above: preview of the case study format currently being built. Published cases will show full editorial commentary and actual analysis results.
A photograph shared publicly — the EXIF GPS field contained exact residential coordinates. Full analysis with map resolution and severity breakdown.
Case being prepared — 70% complete
An image presented as unedited. ELA surface map identified a pasted region with mismatched compression entropy. The splice boundary and severity score explained.
Case being prepared — 50% complete
A file with EXIF claiming a specific camera model. The DQT signature matched a desktop photo editor, not the stated device. What this reveals about editing provenance.
Case being prepared — 40% complete
More cases covering metadata identity leaks, encoding anomalies, and steganography detection are being added.
The tools below run the same forensic pipeline used to produce every case on this page.
Upload any JPEG, PNG, HEIC, WebP, or RAW image and get its full forensic report — GPS, camera fingerprint, ELA, steganography detection, and more.
Analyse NowSubmit an MP4, MKV, WebM, or AVI and get a forensic breakdown — codec fingerprint, DRM detection, GPS atoms, encoder trail, and hidden content checks.
Analyse NowConceal any file inside an ordinary photo or video — encrypted with AES-256-GCM, invisible to every analyser including this one.
Get StartedUpload a photo or video that has a Vaultify payload and extract everything hidden inside it.
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