降温信号未识别中风险权限组合

Redact

Privacy guard for LLM chats. Catches credentials and PII - On-device and Open source.

用户数2当前公开安装规模

评分5.0商店平均评分

评论数1公开评论体量

Manifest 版本V3插件平台版本

7日增长-1近 7 天净增用户

7日增长率-33.3%相对周增长速度

视觉预览

Redact 媒体预览

2 项素材

趋势

用户增长趋势

按已采集快照查看用户数变化。

用户增长趋势

评分趋势

30 日评分变化

按时间查看评分波动，辅助判断近期口碑是否稳定。

30 日评分变化

起始值

5.00

日/周/月增长表现

同口径展示 1 天、7 天、30 天的绝对增长与增长率。

1日增长增长

+2--

7日增长减少

-1-33.3%

30日增长持平

00%

技术摘要

版本、语言与抓取信息

查看发布时间、版本、支持语言、最近更新和抓取时间。

版本1.0.0

ManifestV3

大小27.04MiB

语言数1English (United States)

发布时间--

插件简介

查看插件说明、主要功能和适用场景。

Redact catches credentials and personally identifying information before it reaches LLM chat boxes. Detection runs locally inside the user's browser using a small neural network bundled in the extension package.

HOW IT WORKS

When the user pastes into a supported chat box, Redact intercepts the paste event and scans the text in a Web Worker. Inference completes in about 150 milliseconds on a modern laptop after the model has loaded. The model recognizes credentials, social security numbers, credit card numbers, email addresses, and phone numbers. A regex safety net adds high-precision detection for canonical credential formats including AWS access keys, GitHub personal access tokens, Anthropic API keys, JWTs, database connection URLs, and private key blocks.

INTERACTION

Each entity type has a Block / Warn segmented toggle in the popup's "Sensitivity per type" section. When a blocked item is detected the user can choose one of four flows: a quick prompt, a full-screen block, a cooldown after the first prompt, or silent auto-redaction.

WHERE IT RUNS

评价