
The swiss-army knife of digital forensics for debunking fake news and synthetic media.
The InVID-WeVerify Verification Plugin is a critical technical asset for journalists, fact-checkers, and human rights defenders, specifically designed to address the proliferation of disinformation and synthetic media. Its architecture integrates a multi-layered forensic suite directly into the browser, enabling real-time analysis of digital content across social platforms. By 2026, the tool has evolved to include advanced neural networks for deepfake detection, capable of identifying temporal inconsistencies and GAN-generated artifacts in high-definition video. The plugin leverages a distributed server-side processing model to handle heavy forensic tasks—such as Error Level Analysis (ELA) and Discrete Cosine Transform (DCT) mapping—without degrading local browser performance. It functions as a meta-search engine for verification, aggregating results from Google, Bing, Yandex, TinEye, and Reddit to trace the provenance of media. Its market position is solidified as the industry standard for open-source intelligence (OSINT), bridging the gap between raw data collection and judicial-grade digital evidence. As AI-generated misinformation becomes more sophisticated, InVID-WeVerify serves as a decentralized gatekeeper, providing a unified dashboard for metadata extraction, optical character recognition (OCR), and historical analysis of social media accounts.
Identifies areas within an image that are at different compression levels, highlighting potential digital modifications.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Utilizes a dedicated neural network to detect facial inconsistencies and biometric anomalies in video streams.
Algorithms that split videos into manageable frames for reverse search on multiple engines simultaneously.
Deep scan of media files to retrieve GPS coordinates, camera types, and timestamps.
Advanced query syntax for Twitter and Facebook to find the first instance of a shared media item.
Extracts text from images and videos and translates it to the user's native language.
Maps the spread of a single image hash across multiple social media ecosystems.
Confirming the authenticity of user-generated content (UGC) from conflict zones.
Registry Updated:2/7/2026
Detecting if a video of a political candidate is AI-generated.
Identifying if a claimant has photoshopped damage onto a vehicle.