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AI编码 dev.to · @Daniel Ehrhardt

开源 AI 同事 Godmode Bot:2FA 登录时模型看不到密码

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作者发布开源(MIT)AI 同事 Godmode Bot,基于 Tauri 2,支持 macOS/Windows/Linux 桌面及服务器、NAS、树莓派无头运行,以 Claude Code 为大脑、browser-use 驱动受管 Chromium。登录与 TOTP 密钥存于本地 vault(scrypt→KEK→随机 256 位数据密钥→AES-256-GCM),agent 通过 vault_fill_login、vault_fill_totp 等工具经 CDP 将值填入页面,密码不进入模型上下文;填充仅限对应 https 站点与真实密码字段,密钥在记录、日志和 UI 中脱敏并写入审计日志。支持从 Chrome、1Password、Bitwarden、Apple Passwords、Firefox 导入密码,以及从 Google Authenticator 导出二维码截图导入 2FA。每个 agent 是一个 git 仓库,含 CLAUDE.md、MEMORY.md、会话记录、运行日志与工作区,每次运行提交可回滚;另提供 cron 例程、agent 间委派、缺失登录收件箱、Chrome 会话导入、Composio/MCP 集成与语音模式。

AI推荐理由 作者自述的开源项目(MIT)Godmode Bot,用 Tauri 2 构建桌面/无头应用,以 Claude Code 为大脑、browser-use 驱动 Chromium。核心新信息是凭据隔离设计:登录与 TOTP 密钥存本地 vault(scrypt→KEK→256 位数据密钥→AES-256-GCM),agent 通过 vault_fill_login/vault_fill_totp 经 CDP 直接填入页面,密码不进入模型上下文;填充绑定站点与真实密码字段以降低钓鱼/提示注入风险,密钥在日志与 UI 中脱敏并记录审计日志。还支持从 Chrome、1Password、Bitwarden 等导入密码,agent 以 git 仓库形式保存指令、记忆、会话与运行日志并可回滚。局限:均为作者自述,无第三方验证或实测数据,安装量、星数、安全扫描等未提供,实际安全性与效果需独立评估。

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Every AI agent I tried had the same weak spot: it was great until it reached a login screen. Then it needed a password, a 2FA code, or me. So I built Godmode Bot, an open-source (MIT) AI coworker that has a real browser plus your logins and 2FA codes. The model never sees any of those secrets. What it is Godmode Bot is a desktop app for macOS, Windows and Linux built with Tauri 2. It can also run headless on a server, NAS or Raspberry Pi with a web dashboard. It uses Claude Code as the brain and browser-use to drive a managed Chromium. You can start with a single chat ("log into our billing portal and download September's invoice"), or build a team of persistent agents that each have their own instructions, memory, schedules and history. Fill, don't reveal This is the part I spent the most time on. Logins and TOTP secrets live in a local vault: scrypt → key-encryption key → random 256-bit data key → AES-256-GCM per secret. When an agent reaches a login form, it calls a tool like vault_fill_login or vault_fill_totp. Godmode types the value into the page over CDP. The password never enters the model's context. Fills are site-bound. A login is only typed into its own https site and into real password fields, so a phishing or prompt-injected lookalike page gets nothing. Known secrets are redacted from transcripts, logs and the UI, and every secret access is written to an audit log. Getting secrets in is easy too. You can import passwords from Chrome, 1Password, Bitwarden, Apple Passwords or Firefox, and 2FA from a screenshot of a Google Authenticator export QR code (multi-account codes work). Agents are git repos Every agent gets its own repository: ~/.godmode/agents/invoice-collector/ ├── CLAUDE.md # identity & instructions ├── MEMORY.md # long-term memory the agent maintains ├── conversations/.md # transcripts ├── runs/2026-09-27/.jsonl# raw event logs (secrets redacted) └── workspace/ # files the agent produced Enter fullscreen mode Exit fullscreen mode Every run is committed, so you can see exactly what an agent learned and did, and roll it back. Other features Routines: cron schedules with a friendly builder ("weekdays at 08:00") Delegation: agents hand tasks to peer agents or spawn short-lived subagents Missing-login inbox: when an agent can't sign in, it tells you exactly what's missing instead of stalling Chrome session import: continue where your Chrome profile left off Integrations: Composio toolkits and custom MCP servers, globally, per workspace or per agent Voice mode, encrypted backup & restore, and all Claude Code slash commands in the composer How it works Each turn runs claude -p --output-format stream-json inside the agent's git repo and streams every thought, tool call and screenshot to the UI. A local MCP gateway gives the agent vault tools, delegation tools and report_missing_login. You can watch the browser live next to the chat and take control at any point, for example to solve a CAPTCHA. The honest caveat Agents run Claude Code with bypass permissions, so there are no permission prompts. Treat it like a trusted coworker with access to your machine. For sensitive setups, run it in a VM or container. SECURITY.md covers the threat model. Try it Desktop app: Releases Headless: docker compose up -d and open http://localhost:7777 Code, issues and PRs: https://github.com/codextde/godmode-bot I'd love feedback, especially on the vault design and what you'd want agents to do next. A full computer-use VM mode is on the roadmap.

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