Show HN: Auto-identity-remove – Automated data broker opt-out runner for macOS
Auto-identity-remove 是一款开源 macOS 工具，能自动从 500 多个个人搜索网站和数据经纪数据库中删除个人信息。由 Stephen Thorn 开发，它通过 macOS 的 launchd 定期按月运行，自动完成从查找你的列表、填写退出表单到解决 CAPTCHA 的全部流程。完成后会通过 iMessage 发送摘要，并在浏览器中打开需要人工处理的网站。
项目最初覆盖 30 多家主要数据经纪商，并为每家明确映射了退出策略，包含 Spokeo 、 WhitePages 、 Intelius 、 BeenVerified 等。每家经纪商都有定制流程：有的先搜索个人资料、有的直接填写退出表单、有的通过 Mail.app 发邮件。系统采用智能表单检测而非硬编码选择器，对网站变动更具鲁棒性。 state.json 的状态追踪会记录已退出的经纪商，并在 90 天内跳过它们，因为数据经纪商通常会在该时间段内重新添加个人信息。
随着 generic-runner.js 的加入，覆盖范围从 31 家扩展到 500 多家，项目实现了重大扩展。 The Markup 的研究提供了 494 个退出 URL，BADBOOL 贡献了另外 27 个个人搜索站点。对于这些通用经纪商，脚本按顺序尝试四种策略：点击"Do Not Sell My Personal Information"按钮、通过 OneTrust 或 TrustArc 等常见隐私管理器退出、用你的信息填写通用退出表单，或记录 DSAR 链接以便手动跟进。此方法让工具无需为每个站点单独配置也能处理大量网站。
设置通过交互式 setup.js 完成，会收集你的个人信息、 CapSolver API 密钥、 iMessage 通知号码，并创建所需的一次性账户。敏感数据保存在本地，config.json 和 state.json 都被列入 .gitignore 。 CapSolver 集成可以约 $0.001 每次的成本处理带 CAPTCHA 的表单，适合定期运行；不使用 CapSolver 的话，这些带 CAPTCHA 的站点会被加入手动操作列表，而不会直接报错失败。
该工具将自己定位为 Incogni 、 Optery 等付费服务的免费、透明替代方案；这些付费服务按年订阅并覆盖更多经纪商、由专业团队维护流程。 auto-identity-remove 让用户能完全掌控并查看整个过程。作者建议两者结合使用：让付费服务处理大部分经纪商，本脚本补位处理 Acxiom 、 LexisNexis 、 ZoomInfo 、 Clearbit 等可能未被全面覆盖的网站。项目采用 MIT 许可证，欢迎贡献，尤其是添加带有已验证可用选择器的新经纪商。
Auto-identity-remove is an open-source macOS tool that automates the process of removing personal information from over 500 people-search sites and data broker databases. Created by Stephen Thorn, it runs on a monthly schedule using macOS's launchd system and handles everything from searching for your listings to filling out opt-out forms and solving CAPTCHAs. The tool sends an iMessage summary when complete and opens any sites requiring manual action directly in your browser.
The project started by covering 30+ major data brokers with explicitly mapped opt-out strategies, including sites like Spokeo, WhitePages, Intelius, BeenVerified, and others. Each broker has a tailored approach, whether that involves searching for your profile first, filling a direct opt-out form, or sending an email through Mail.app. The system uses smart form detection rather than hardcoded selectors, making it more resilient to site changes. A state tracking system in state.json remembers which brokers you've been removed from and skips them for 90 days, since data brokers typically re-add personal information within that timeframe.
A major expansion came with the addition of generic-runner.js, which brought coverage from 31 to over 500 brokers by incorporating two public datasets. The Markup's research provided 494 opt-out URLs, while BADBOOL contributed 27 additional people-search sites. For each of these generic brokers, the script tries four strategies in sequence: clicking a "Do Not Sell My Personal Information" button, opting out through common privacy managers like OneTrust or TrustArc, filling any generic opt-out form with your details, or recording a DSAR link for manual follow-up. This approach allows the tool to handle a vast number of sites without needing individual configuration for each one.
The setup process is handled through an interactive setup.js script that collects your personal information, CapSolver API key, iMessage notification number, and creates any required one-time accounts. Your sensitive data stays local, as both config.json and state.json are gitignored. CapSolver integration handles CAPTCHA-protected forms at roughly $0.001 per solve, making it affordable for regular use. Without CapSolver, those CAPTCHA-protected sites simply get added to your manual action list instead of failing with errors.
The tool positions itself as a free, transparent alternative to paid services like Incogni or Optery, which charge annual subscriptions. While paid services cover more brokers with professionally maintained flows, auto-identity-remove gives users full control and visibility into the process. The author actually recommends using both approaches together, with a paid service handling the bulk of brokers and this script filling in the gaps for sites like Acxiom, LexisNexis, ZoomInfo, and Clearbit that might not be fully covered elsewhere. The project is MIT licensed and welcomes contributions, particularly for adding new brokers with verified working selectors.
132 comments • Comments Link
• 这款自动化数据经纪人退出工具有潜力，但可用性问题严重——链接失效、强制要求与 Apple Mail 集成，以及对非美国地址处理不当——表明要被更广泛采用还需大幅改进。
• 对 macOS 及 Apple 服务（如 Messages 和 launchd）的依赖限制了可及性，尽管其他系统可以通过 cron 或任务计划程序做变通。
• 使用 CapSolver 等 AI 服务绕过 CAPTCHA 引发了对自动化与反机器人措施之间军备竞赛的担忧；有些 CAPTCHA 难到连正常用户都受影响。
• 关于 Yellow Pages 退出方式的轶事既暴露了实体数据分发的荒诞与环境浪费，也展示了早期大规模数字抵抗的尝试。
• 数据经纪人的退出流程往往被刻意设得繁琐，需要手动操作、邮件验证或注册账户，因此有人怀疑这些机制更像是在确认活跃用户而非真正删除数据。
• 普遍存在对数据经纪人是否真的遵守退出请求的质疑，很多人认为这只是表面合规，难以称得上真正的隐私保护。
• 更严格的隐私法规（如 GDPR）被视为最有效的解决办法，加州即将推出的 DROP 表格为美国消费者带来一线希望，尽管执法仍是难题。
• 该工具需要向数百个网站提交个人信息，构成一种悖论：用户必须信任工具不会滥用数据，这凸显了透明性和开源审计的必要性。
• 有人认为，向数据经纪人提供虚假信息比提交退出请求更有效，因为这能削弱其数据集的可靠性。
• 开发者承认项目仍处于测试阶段，欢迎社区贡献以提高成功率、补充经纪人定义并扩展对 macOS 以外平台的支持。
讨论反映出人们对数据经纪人行业及现有退出机制的深切沮丧，参与者既提出技术层面的批评，也探讨了数字时代更广泛的隐私伦理问题。尽管自动化工具是一种创造性的应对之道，但对其有效性与安全性的怀疑，折射出对那些以收集个人数据为前提来"保护"隐私的系统的普遍不信任。对话强调了个人行动与系统性解决方案之间的张力，很多人认为有意义的改变需要监管介入，而非仅靠技术变通。尽管挑战重重，社区仍真诚希望通过协作改进此类工具，并在防范 AI 生成内容的风险与保障隐私敏感场景中的人工监督之间取得平衡。 • The tool automating data broker opt-outs shows promise but has significant usability issues, including broken links, mandatory Apple Mail integration, and problems handling non-US addresses, suggesting it needs substantial refinement for broader adoption.
• The requirement for macOS and Apple services like Messages and launchd limits accessibility, though workarounds exist for other operating systems using cron or task scheduler.
• CAPTCHA solving via AI services like CapSolver raises concerns about perpetuating the arms race between automation and anti-bot measures, with some CAPTCHAs becoming so difficult they frustrate legitimate users.
• Historical anecdotes about Yellow Pages opt-out schemes highlight both the absurdity of physical data distribution and the environmental waste, while also illustrating early attempts at mass digital resistance.
• Data broker opt-out processes are often intentionally cumbersome, requiring manual steps, email verifications, or account creation, leading many to suspect these mechanisms serve more to confirm active user data than to genuinely remove it.
• There's widespread skepticism about whether data brokers actually honor opt-out requests, with some viewing the entire process as performative compliance rather than real privacy protection.
• Stronger privacy regulations like GDPR are seen as the most effective solution, with California's upcoming DROP form offering hope for US consumers, though enforcement remains a challenge.
• The tool's reliance on submitting personal information to hundreds of sites creates a paradox where users must trust the tool not to misuse their data, emphasizing the need for transparency and open-source verification.
• Some suggest that flooding data brokers with false information might be more effective than opt-out requests, as it undermines the reliability of their datasets.
• The developer acknowledges the project is in beta and welcomes community contributions to improve success rates, add broker definitions, and expand platform support beyond macOS.
The discussion reveals deep frustration with the data broker industry and the inadequacy of current opt-out mechanisms, with participants sharing both technical critiques and broader philosophical concerns about privacy in the digital age. While the automated tool represents a creative approach to a widespread problem, skepticism about its effectiveness and safety reflects a broader distrust of systems that demand personal data to protect personal data. The conversation underscores the tension between individual action and systemic solutions, with many concluding that meaningful change will require regulatory intervention rather than technological workarounds. Despite the challenges, there's genuine interest in collaborative improvement of such tools, balanced against concerns about AI-generated content and the need for human oversight in privacy-sensitive applications.