SST-Guard: Detecting and Characterizing Server-Side Google Analytics in the Wild
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917450401972224 |
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| author | Jazlan, Muhammad Gamero-Garrido, Alexander Shafiq, Zubair Vekaria, Yash |
| author_facet | Jazlan, Muhammad Gamero-Garrido, Alexander Shafiq, Zubair Vekaria, Yash |
| contents | As web browsers increasingly restrict client-side tracking, the web tracking ecosystem is shifting from client-side to server-side tracking (SST). In SST, the browser sends tracking requests to an intermediate endpoint, which then forwards them to the tracker's endpoint, eliminating direct client-to-tracker requests. As a result, existing tracking protections that block requests to known tracker endpoints are rendered ineffective.
In this paper, we investigate server-side implementation of Google Analytics, the most widely deployed third-party tracking service on the web today. We also present SST-Guard, a multi-modal, browser-based system for detecting and blocking server-side Google Analytics (sGA). Our key insight is that even when the tracker's endpoints change, sGA must necessarily still collect and share the same semantic information as client-side Google Analytics (e.g., identifiers, event metadata). Therefore, rather than detecting requests to known Google Analytics endpoints, SST-Guard aims to detect underlying artifacts of collection and sharing of these semantic values to any arbitrary endpoint. Operationalizing this insight is challenging because real-world sGA deployments commonly customize endpoints and obfuscate URLs/payloads. SST-Guard addresses this challenge using a value-template approach that employs regular expressions to match semantic value patterns across multiple modalities: network requests, cookies, and the window object.
We validate SST-Guard on Tranco top-10k websites, detecting 4.02\% (403) sGA domains with over 93\% accuracy across three modalities, with network request classifier demonstrating the highest accuracy (99.8\%). By deploying SST-Guard in the wild, we find 4.21\% (6,314) of Tranco top-150k websites using sGA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_27497 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SST-Guard: Detecting and Characterizing Server-Side Google Analytics in the Wild Jazlan, Muhammad Gamero-Garrido, Alexander Shafiq, Zubair Vekaria, Yash Cryptography and Security Computers and Society As web browsers increasingly restrict client-side tracking, the web tracking ecosystem is shifting from client-side to server-side tracking (SST). In SST, the browser sends tracking requests to an intermediate endpoint, which then forwards them to the tracker's endpoint, eliminating direct client-to-tracker requests. As a result, existing tracking protections that block requests to known tracker endpoints are rendered ineffective. In this paper, we investigate server-side implementation of Google Analytics, the most widely deployed third-party tracking service on the web today. We also present SST-Guard, a multi-modal, browser-based system for detecting and blocking server-side Google Analytics (sGA). Our key insight is that even when the tracker's endpoints change, sGA must necessarily still collect and share the same semantic information as client-side Google Analytics (e.g., identifiers, event metadata). Therefore, rather than detecting requests to known Google Analytics endpoints, SST-Guard aims to detect underlying artifacts of collection and sharing of these semantic values to any arbitrary endpoint. Operationalizing this insight is challenging because real-world sGA deployments commonly customize endpoints and obfuscate URLs/payloads. SST-Guard addresses this challenge using a value-template approach that employs regular expressions to match semantic value patterns across multiple modalities: network requests, cookies, and the window object. We validate SST-Guard on Tranco top-10k websites, detecting 4.02\% (403) sGA domains with over 93\% accuracy across three modalities, with network request classifier demonstrating the highest accuracy (99.8\%). By deploying SST-Guard in the wild, we find 4.21\% (6,314) of Tranco top-150k websites using sGA. |
| title | SST-Guard: Detecting and Characterizing Server-Side Google Analytics in the Wild |
| topic | Cryptography and Security Computers and Society |
| url | https://arxiv.org/abs/2604.27497 |