> For the complete documentation index, see [llms.txt](https://bellingcat.gitbook.io/toolkit/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://bellingcat.gitbook.io/toolkit/more/all-tools/facecheck.id.md). # FaceCheck.ID A facial recognition search engine that tries to find photos of people that look similar to a person of interest. ## URL ## Description Reverse image searching for people is not a reliable research method on its own but it can be used as one of several steps during an open source investigation. Save photographs of the individual you are researching, ideally high-resolution images that clearly show their face, and run these through tools like FaceCheck.ID to potentially find more photographs of the same individual. It is important to keep in mind that you should never solely rely on facial recognition tools to identify the same person across several photos (since two people might just look very similar). You also need other pieces of evidence to be able to draw correct conclusions. ### Step-by-step guide Simply drag and drop the image in the search engine. Once the search is complete, FaceCheck.ID will generate a report. Each photograph it has identified has a certainty score between 0 and 100. The higher the score the higher the likelihood that the two faces might be the same according to FaceCheck.ID. The search report is [deleted ](https://facecheck.id/Face-Search/FAQ)after 24 hours, according to the FAQ page of FaceCheck.ID. That said, you can create a permanent link for future reference by clicking on the link below the report.

Screenshot 1. Drag and drop an image on the website's home page to search.

## Cost * [ ] Free * [ ] Partially Free * [x] Paid FaceCheck.ID will allow you to search for free, but you will have to [buy ](https://facecheck.id/buy)credits to view the results. It is important to note you can only pay with cryptocurrencies. ## Level of difficulty
1
## Requirements You need to buy credits via cryptocurrency. ## Limitations Like other reverse facial recognition search engines, FaceCheck.ID will not provide you with a full name, email address and other confirmed pieces of personal identification data. You will need to comb through the results to determine whether a) the images identified by FaceCheck.ID are of your subject, and b) analyse the information on each web page that features the photos to determine information like usernames, possible location etc. ## Ethical Considerations FaceCheck.ID does not clearly list its sources, [its website only states](https://facecheck.id/Face-Search/Privacy) that the tool compares uploaded photos with photos "from public, readily available web pages only." Ethical considerations include privacy concerns, copyright infringement, and possible proliferation of misinformation. Make sure you analyse the search results critically and cross-reference these with other sources of information to ensure your findings are accurate. Do not use copyright images without permission. Josephine Lulamae reflects on ethical questions around the use of facial recognition tools in the AlgorithmWatch article: [War Crimes OSINT, Harassment, Doxxing Police and Protesters: Face Recognition for Everyone](https://algorithmwatch.org/en/face-recognition-for-everyone/) (2022). ## Guides and articles Read the guide on the FaceCheck.ID [website](https://facecheck.id/Face-Search-Effective-Face-Lookup). ## Tool provider The FaceCheck.ID website states that it was created by Tech Solutions - Belize. ## Advertising Trackers * [x] This tool has not been checked for advertising trackers yet. * [ ] This tool uses tracking cookies. Use with caution. * [ ] This tool does not appear to use tracking cookies. | Page maintainer | | --------------- | | Ana. | | | --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://bellingcat.gitbook.io/toolkit/more/all-tools/facecheck.id.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.