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Show XO: Rampart, an open-source tool that masks personal data in the browser before it is sent to a chatbot(ndstudio.gov)

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Writing language: KoreanRead in the original language

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- Rampart is a tool that finds and masks personal information such as names and Social Security numbers (SSN) before a message is sent to a chatbot. According to the source, all processing happens inside the browser and the server is not involved. - Fixed-format information (SSN, card numbers, phone numbers, etc.) is caught by regular expression rules, while information that needs context, such as names and addresses, is found by MiniLM, a small language model. A regular expression is a way of defining character patterns. - According to figures published by the development team, the model size is 14.7MB, the median latency on WebGPU in browsers is 3.9ms, and the personal information recall across seven languages is 98.4%. These figures are results the development team measured on 30,000 rows of the OpenPII held-out data. - It is in alpha and, according to the source, supports only seven languages: English, Spanish, French, German, Italian, Portuguese, and Dutch.
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Editorial opinionstartupxo

The structure that masks SSNs or names in the browser before sending is what catches my eye first. What the source confirms is that the recall of 98.4% was measured by the development team on 30,000 rows of the OpenPII holdout data. Since the list of supported languages does not include Korean, it is hard to know from this article alone how many domestic names and addresses will be caught. Trying a few sample work emails will likely show quickly where things get missed. Would you also like to check how the masked values are restored when they come back in the model's response?
Writing language: Korean

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