PixelConfig: Longitudinal Measurement and Reverse-Engineering of Meta Pixel Configurations

TL;DR

This paper introduces PixelConfig, a framework for reverse-engineering Meta Pixel configurations across websites, revealing widespread activity and identity tracking, especially on health-related sites, with limited effectiveness of restrictions.

Contribution

PixelConfig provides a novel differential analysis method to analyze and compare Meta Pixel configurations across thousands of websites, uncovering their usage patterns and limitations.

Findings

High adoption of activity and identity tracking features, up to 98.4%.

Detection of sensitive information being tracked on health websites.

Limited effectiveness of tracking restrictions, with partial adoption and circumvention.

Abstract

Tracking pixels are used to optimize online ad campaigns through personalization, re-targeting, and conversion tracking. Past research has primarily focused on detecting the prevalence of tracking pixels on the web, with limited attention to how they are configured across websites. A tracking pixel may be configured differently on different websites. In this paper, we present a differential analysis framework: PixelConfig, to reverse-engineer the configurations of Meta Pixel deployments across the web. Using this framework, we investigate three types of Meta Pixel configurations: activity tracking (i.e., what a user is doing on a website), identity tracking (i.e., who a user is or who the device is associated with), and tracking restrictions (i.e., mechanisms to limit the sharing of potentially sensitive information). Using data from the Internet Archive's Wayback Machine, we analyze and compare Meta Pixel configurations on 18K health-related websites with a control group of the top 10K websites from 2017 to 2024. We find that activity tracking features, such as automatic events that collect button clicks and page metadata, and identity tracking features, such as first-party cookies that are unaffected by third-party cookie blocking, reached adoption rates of up to 98.4%, largely driven by the Pixel's default settings. We also find that the Pixel is being used to track potentially sensitive information, such as user interactions related to booking medical appointments and button clicks associated with specific medical conditions (e.g., erectile dysfunction) on health-related websites. Tracking restriction features, such as Core Setup, are configured on up to 34.3% of health websites and 8.7% of control websites. However, even when enabled, these tracking restriction features provide limited protection and can be circumvented in practice.