We conducted the first analysis of WeChat’s tracking ecosystem. Using reverse engineering methods to intercept WeChat’s network requests, we identified exactly what types of data the WeChat app is sending to its servers, and when. This report is part one of a two-part series on a privacy and security analysis of the WeChat ecosystem.
Posts tagged “WeChat”
As a follow-up to our March 2020 report, we conducted daily tests on WeChat and collected 2,174 censored keywords between January to May 2020. This data provides a view into how narratives and messaging on the pandemic are controlled and molded on social media in China.
WeChat communications conducted entirely among non-China-registered accounts are subject to pervasive content surveillance that was previously thought to be exclusively reserved for China-registered accounts.
The analysis of YY and WeChat indicates broad censorship—blocking sensitive terms as well as general information and neutral references—potentially limiting the public’s ability to access information that may be essential to their health and safety.
This year, Citizen Lab researchers will present on issues ranging from WeChat image filtering to the methodologies used for identifying commercial spyware abuses.
In this work, we study how Tencent implements image filtering on WeChat. We found that Tencent implements realtime, automatic censorship of chat images on WeChat based on what text is in an image and based on an image’s visual similarity to those on a blacklist. Tencent facilitates this realtime filtering by maintaining a hash index of MD5 hashes of sensitive image files.