InVID

A toolkit that supports the verification of videos and images.

URL

https://weverify.eu/verification-plugin/

(v. 0.90; last checked: May 2026)

Description

The InVID Verification Plugin is a comprehensive toolkit designed to assist journalists in verifying content on social networks. It offers a suite of tools to analyze and verify videos and images, including contextual information retrieval, several engines (Google, Lens, Bing, TinEye, Yandex, Baidu, Karma Decay, DBKF), video fragmentation, and metadata extraction. The plugin supports multiple platforms, such as YouTube, Facebook, Twitter, and Instagram, making it a versatile tool for fact-checking and debunking tasks on social networks. (Some Twitter-related features may not work anymore due to the API policy change.) Since v0.85 the plug-in has gained a WACZ disinformation-archiving tool, a Hiya-powered voice-clone detector, and full Hungarian localisation (joining EN, FR, ES, EL, AR, IT & DE).

If you're a journalist, fact-checker, or researcher, take a minute to apply and register to use the advanced tools. To do this, click "Advanced Tools" and then "Register". Register with your professional email address. Once you’re confirmed as registered, enter your email and then copy & paste the code emailed to you.

Features

Video

Video Analysis

Provides contextual information and metadata for YouTube and public Facebook videos, helping users understand the video's background and related comments.

Keyframes

Segments YouTube or Facebook videos into keyframes for detailed analysis and reverse image search, enhancing verification processes.

Thumbnails

Extracts and performs a reverse search of thumbnails from YouTube videos to check for prior usage or manipulation.

Video Rights

Retrieves and displays information on legal rights for YouTube and Twitter videos, helping users understand reuse conditions and copyright issues.

Metadata

Extracts metadata from JPEG images and videos in MP4 or M4V formats, providing details such as creation date, camera settings, and location data.

Deepfake (Restricted Feature)

Uses a machine learning classifier to determine the probability that a video contains AI-manipulated faces, such as face swapping or face reenactment. Access is restricted to registered users.

Image

Magnifier

In a nutshell, Magnifier is the “digital loupe” inside the InVID-WeVerify plug-in: you load any still image (URL or local file) and the module lets you zoom, sharpen and flip it at pixel level, then push the same frame to reverse-image search or the forensic filters.

Deep zoom & live lens – Hover anywhere on the picture and a resizable loupe shows the native pixels at up to ×20, perfect for reading licence plates, shoulder patches or tiny timestamps.
Enhancement tools – One-click buttons apply bicubic up-scaling, edge-sharpen, mirror-flip or 90° rotation so faint characters or mirrored selfies become legible.

Metadata

Extracts metadata from JPEG images and videos in MP4 or M4V formats, providing important information for verification.

Forensic

Provides an enhanced toolkit to detect image forgeries, enabling detailed forensic analysis to identify manipulations.

OCR (Optical Character Recognition)

Extracts text from images, making it easier to analyze and verify textual content within images.

CheckGIF (Restricted Feature)

Compares an original image with a tampered one, including cropped images, and generates a GIF highlighting differences. Access is restricted to registered users.

This plugin will not be able to solve the question of the correct pronunciation of GIF.

Synthetic Image (Restricted Feature) - Determines the probability that an image is AI-generated, using machine learning to assess potential manipulations. Access is restricted to registered users.

Deepfake (Restricted Feature)

The Deepfake tab in the InVID-WeVerify verification plug-in is an experimental video-forensics tool built by ITI CERTH under the EU-funded vera.ai project. You paste a video URL (or upload a local clip) and the service breaks the file into frames, detects every visible face, and runs an ensemble of five CNN-based detectors (Xception, EfficientNet-B4, Capsule-Forensics ++ & two proprietary lightweight models). The ensemble outputs a 0–1 probability score that the footage contains AI-manipulated faces (face-swap / reenactment). Results are colour-coded (green < 0.30, amber 0.30-0.60, red > 0.60) and accompanied by per-frame thumbnails so you can jump straight to suspicious segments. All processing happens on CERTH’s servers; only hash-anonymised frames are stored for 30 days to improve the model.

Geolocalizer (Locked Feature)

The Geolocalizer (locked / beta) lets you upload or paste any still-image link; the plug-in then calls an experimental CERTH service that estimates where on Earth the picture was taken. It does this entirely by visual analysis—no EXIF GPS is required. You get a latitude/longitude guess, a rough confidence band, and a set of visually similar reference pictures you can open in a map viewer for manual comparison. Accuracy is usually “city-level” (±25 km) for landmarks and distinctive skylines, but drops on rural or indoor scenes. The module is being developed under the EU vera.ai programme and is still labelled experimental, so double-check every hit with classic open-source techniques.

All heavy lifting happens on ITI CERTH servers; the plug-in strips EXIF and hashes the file name before upload. Hash-anonymised embeddings are kept for 30 days to retrain the model, then purged.

Treat results as leads—cross-check with Street View, SunCalc and local news imagery.

Provenance (C2PA)

It reads an image or video's C2pa data. C2PA stands for the Coalition for Content Provenance and Authenticity, an open standard backed by Adobe, Microsoft, Google, the BBC and others. It embeds a tamper-evident “manifest” (hashed, then signed) in JPEG, PNG, MP4, WebP and AVIF files. If someone alters pixels or edits the manifest, the signature breaks.

The plug-in parses the manifest with the same open-source library used by Adobe’s and Digimarc’s browser extensions, then renders a human-readable report. If the signature chain resolves to a trusted root certificate, you’ll see a green “verified” badge; otherwise you get a warning.

Audio

Hiya Voice-Clone Detector (Locked Feature)

Uses Hiya.ai’s classifier to spot AI text-to-speech or cloned voices in WAV/MP3 uploads, flagging likely synthetic segments. Requires registration; processing happens server-side, and no audio is stored after analysis (see privacy notice in the plug-in).\

Search

X Search

Performs advanced search queries on X (formerly Twitter), including precise time intervals, enhancing the ability to find relevant content. This uses the X's advanced search function.

Fact Check Semantic Search (Locked Feature)

Paste a sentence, paragraph, or whole social-media post, and the tool looks for semantically similar fact-checks in a multilingual database of ≈ 300 000 verified debunks from more than 160 IFCN-signatory organisations. It therefore answers the question “Has anyone already debunked this claim?” even when the input language differs from the fact-check language. Claims are pulled hourly from the Database of Known Fakes (DBKF) back-end, which aggregates RSS, ClaimReview, and custom scrapers.

XNetwork

Provides a customized search engine (CSE) for cross-network queries, simultaneously allowing searches across multiple social media platforms (Twitter, Reddit, 4chan, YouTube, Facebook, 8kun, LinkedIn, VK, Instagram, and TikTok).

Factchecks

This module is a Google Programmable Search Engine (CSE) wired to ~240 trusted fact-checking outlets – chiefly IFCN signatories plus long-standing projects such as Snopes, Full Fact and Africa Check. A single query lets you ask “Has someone published a debunk on this?” and brings back only results that already carry a ClaimReview-style verdict.

Data Analysis

Twitter SNA (Locked Feature)

Performs social network analysis on Twitter, analyzing interactions, trends, and relationships to understand information spread and impact. Deprecated since July 1st, 2023, due to X/Twitter code changes. It is on registration, so it might work again at some point, and this article will reflect that. Access is restricted to registered users.

CSV Analysis

Allows the import and analysis of social network data from CrowdTangle exports, using Social Network Analysis (SNA) to provide in-depth insights into social media activity and trends.

CrowdTangle is permanently gone. We hope that this feature will not disappear but be adapted to perform other ways of SNA instead.

Cost

Free

Level of difficulty

Requirements

Chromium-based browsers and Firefox (via manual .xpi install) are supported; Safari is not. Firefox install instructions remain on the project’s GitHub mirror.

Limitations

External Services: Some tools within the plugin rely on external services that are not open-sourced, which may affect transparency and long-term accessibility.
API Restrictions: Certain features, such as Twitter analysis, have been deprecated due to changes in platform APIs.
Locked Features: Several advanced features are restricted to registered users, such as journalists and researchers, which may limit access for general users.
Processing Time: Analyzing videos with a large number of comments or metadata can be slow, affecting efficiency.
Browser Compatibility: The plugin is primarily designed for Chrome and Opera browsers, with limited support for other browsers, such as Firefox.
Geolocation Accuracy: The Geolocalizer's accuracy depends on the availability and quality of metadata, which may not always be reliable.
AI Detection Limitations: The accuracy of synthetic image and deepfake detection tools can vary, and false positives or negatives may occur.

Ethical Considerations

The InVID Verification Plugin helps researchers and journalists verify online media, but it also raises ethical concerns when used. First, the plugin relies on metadata extraction and reverse searches, which may access personal or private data embedded in media. This raises significant privacy concerns, particularly if personal information is unintentionally disclosed or used without consent.

Tools like deepfake- and AI-generated image detectors may produce false positives or negatives, potentially leading to incorrect conclusions or accusations. It is essential to verify results through multiple sources before making claims. Users should also be mindful of the ethical responsibility of using the tool only for legitimate verification purposes, not for harmful surveillance or invasive investigations.

When using InVID for content verification, there is a risk of misinterpreting results, which could lead to erroneous conclusions. InVID provides tools for analyzing video authenticity by examining metadata, reverse image searching, and extracting keyframes, but the results do not automatically confirm authenticity. Researchers might misinterpret partial metadata or falsely correlate visual matches from reverse image searches, leading to an incorrect verification of content. Without a cautious and critical approach, users could mistake automated analysis for definitive proof, potentially spreading misinformation if content is improperly validated. It's essential to use InVID's findings as part of a broader verification process and corroborate with additional sources before drawing conclusions.

Guide

Guide To Using Reverse Image Search For Investigations

Tool provider

InVID is organized by a consortium of European research groups and businesses, coordinated by The Centre for Research and Technology Hellas (CERTH) in Northern Greece.

The InVID project has received funding from the European Union’s Horizon 2020 research and innovation program.

Page Maintainer

Martin Sona

Last updated 13 days ago

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