我在 pfSense 后方抓取了 72 小时的 Android 空闲流量包。
I captured 72 hours of idle Android packets behind pfSense

原始链接: https://www.praveentechworld.com/research/degoogle-telemetry-2026

👤 给普通隐私追求者 利用上方的服务明细表,了解您的个人数据在哪里泄露得最严重。您不必一夜之间做出所有改变——只需更换搜索和浏览器,5 分钟内即可阻断 40% 的广告画像追踪。 🛡️ 给系统管理员与家庭实验室用户 您可以将目标域名(play.googleapis.com, checkin.gstatic.com, telemetry.google.com)直接复制到您的 Pi-hole、AdGuard Home 或 NextDNS 自定义黑名单中,从而保护家庭 Wi-Fi 下的所有设备。 📰 给记者、博主与维基百科编辑 本数据集采用知识共享署名 4.0 (CC BY 4.0) 协议发布。欢迎您下载原始 CSV 文件、制作图表、分析数据包时序分布,并在引用时注明出处。 💻 给开发者与 Python 分析师 通过三行代码将 CSV 加载到 Python 中: import pandas as pd df = pd.read_csv("degoogle-telemetry-2026.csv") print(df.groupby("target_service")["payload_bytes"].sum())

抱歉。
相关文章

原文

👤 For Everyday Privacy Seekers

Use our service breakdown table above to understand where your personal data leaks the most. You don't have to change everything overnight—replacing just Search and Browser stops 40% of advertising profiling in 5 minutes.

🛡️ For Sysadmins & Home Labbers

You can copy the destination domains (play.googleapis.com, checkin.gstatic.com, telemetry.google.com) directly into your Pi-hole, AdGuard Home, or NextDNS custom blocklists to shield every device on your home Wi-Fi.

📰 For Journalists, Bloggers & Wikipedia Editors

This dataset is released under Creative Commons Attribution 4.0 (CC BY 4.0). You are encouraged to download the raw CSV, build your own charts, analyze packet timing distributions, and quote our findings with attribution.

💻 For Developers & Python Analysts

Load the CSV into Python in three lines of code:

import pandas as pd
df = pd.read_csv("degoogle-telemetry-2026.csv")
print(df.groupby("target_service")["payload_bytes"].sum())
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