This presentation provides a status update on our investigation into how anonymization technologies impact web accessibility. We employ a mixed-methodology, combining large-scale automated analysis with qualitative manual testing. 

The primary technical contribution is a configurable crawler that systematically measures how websites respond to traffic from various anonymization services like Tor and commercial VPNs compared against direct connections. 

To ensure reproducibility, the crawler utilizes specific exit nodes and captures comprehensive artifacts for each test case. This includes page load times, full HTML documents and screenshots. 

This quantitative data is supplemented by manual account registration attempts on popular web platforms. This approach is designed to capture the nuanced user-experience hurdles and blocking mechanisms that are difficult to detect via automation which provides a more holistic view of the challenges faced by privacy-conscious users.