01 / THE SIGNAL

我们发现了什么

enjoy global connections at the team level, like shared LLM keys or service accounts Here’s a demo: https://www.youtube.com/watch?v=dlW-44ntpbE We started working on this by accident, even t

  • 来源:Hacker News首次 2026-07-24 · 最近 2026-08-20
  • 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
  • 商业模式:API / Usage-based
  • 主题:AI Agent
  • 初筛评分:27.9/100 · 收录 2
#工作流自动化#待验证#产品发现
02 / SOURCE & EVIDENCE

证据,比故事更重要。

发现产品或需求信号,暂未获得可核验的商业证据。

规则清洗与初筛,未经人工商业核验。原文语境、实际客户和付费情况仍需自行验证。

引用与数字披露

来源类型(原作者自述/第三方测算/媒体转引)需采集端标注,本版尚未落字段。

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中文辅助译文(全文)

嗨,HN,我是 Jonathan 和 Guy,OneCLI ( https://onecli.sh/ ) 的创建者。OneCLI 是面向 AI 智能体(Agent)的开源保险库。传统的保险库用于存储你的密钥,并在需要时以安全的方式将它们提供给你,依赖于使用者来确保密钥的安全。我们认为,在智能体的世界里,情况并非如此,因为你不知道密钥被传递给智能体之后会发生什么,也不知道它被保存在哪里。或者甚至有人可能篡改了它们以使其交出……基于这样的理解,我们决定构建一个网络网关,部署在你的 AI 智能体与其调用的服务之间。OneCLI 通过 host/path 匹配请求,验证该智能体是否应拥有访问权限,将占位符替换为真实凭证,然后转发请求。密钥存储在 OneCLI 保险库内并在静态时加密,也可以从你的 bitwarden / 1password 钱包实时获取。演示 - https://www.youtube.com/watch?v=5e5pbPEzZfY 。我们最初是偶然开始做这个项目的,尽管我们的职业生涯都深耕于安全领域。我们当时在做一款名为 ChartDB 的开发工具,一款开源的数据库工具。今年一月 OpenClaw 走红之后,我们开始用它来在 ChartDB 之上编排智能体。我们很快意识到身份验证方面存在一个重大问题。智能体需要凭证才能完成实际工作,但把这些密钥交给它们并不是一个好主意。它们会把密钥保存在内存中,还会以明文形式写入本地文件和会话记录。而且我们知道,智能体很容易被欺骗而交出自己的 API key 或密钥。

因此我们需要某种方式来控制智能体,并阻止提示词注入(prompt injection)诱导它利用其服务来为攻击者谋利。具体做法是不向智能体提供密钥,并针对敏感操作增加告警或人工审批(human-in-the-loop),以防有人操纵智能体,同时对访问日志进行审计。我们自己每天都在使用它。我的 OpenClaw 跨 Attio、Gmail 和我的日历管理我的一天,并对敏感操作执行人工审批。审批在网络层强制执行,因此无论智能体是通过 MCP、CLI、curl 还是它即时生成的代码发起请求,审批都有效。Guy 用它来审查 PR,但没有他的审批就不能合并。公司目前主要将其用于编码类智能体,因为这些智能体总会想方设法提升自身权限以达成目标。使用 OneCLI,无论智能体找到什么方法都没用:如果请求不符合策略,它就无法通过。代理(proxy)使用 Rust 编写,仪表盘使用 Next.js,密钥在静态时使用 AES-256-GCM 加密。所有组件都运行在 Docker 容器中。它兼容任何智能体框架(Claude Code、Codex、Cursor、OpenClaw、Hermes 或任何可以设置 HTTPS_PROXY 的东西)。它无法阻止智能体滥用其合法拥有的访问权限,所以请务必严格收紧作用域策略!很乐意回答任何问题。我们认为不能信赖模型自身的行为,必须设定确定性规则才能保持控制。欢迎评论!

译文由上游机器翻译生成,可能有误;判断请以英文原文为准。

英文原文(来源本站未改写)

Hi HN, Jonathan & Guy here from OneCLI, an agent harness built for teams, giving every employee a secured, sandboxed personal agent.Here’s what you can do with it: 1. get a sandboxed agent, with all the OneCLI capabilities in place like connect your GitHub account, Gmail, Notion, or Dropbox simply from the chat. 2. deterministic human in the loop approval in the chat itself for things that you need 100% control like sending an email or deleting the Linear ticket. 3. manage team policy in one place, enforced across every agent in the workspace 4. enjoy global connections at the team level, like shared LLM keys or service accounts Here’s a demo: https://www.youtube.com/watch?

v=dlW-44ntpbE We started working on this by accident, even though our careers were in the security space.We were working on a devtool called ChartDB, an open-source DB tool.When OpenClaw took off back in January, we started using it to orchestrate agents on top of ChartDB.We quickly understood there is a big issue around auth.Agents need credentials to do real work, but to give them those secrets would not be the best idea.They keep them in their memory and also write them down to local files and their sessions as plain text.And we knew that agents can easily be fooled into giving up those API keys/secrets.

So we needed some way to control the agent and stop prompt injections from tricking it into using its services for an attacker's benefit.We created OneCLI that started as a vault for AI Agents built in Rust.We found out that most of our demand for OneCLI came from autonomous agents like Hermes, OpenClaw and NanoClaw for individuals and teams.Users looked for useful agents that do things for the person who runs them with two missing parts: 1) managing secrets and permissions. 2) and for teams - multiplayer management.We decided to pivot and provide the agent itself as a harness for teams, to give each employee an agent.

We saw that teams had to deal with setting up their own harness again and again, and basically as we already had the vault as a gateway.We got the idea to provide the missing piece of the agent management out of the box and open source it (Apache-2.0, with a small enterprise exception).We're open source first - the entire platform, not just a small portion of it like other agents, so companies can actually see the code, evaluate it, and trust it instead of taking our word for it.They run it isolated, in their own environment, fully under their control, at production quality, not a locked black box hosted somewhere else.

That means the safety isn't just a promise, it's something they can verify themselves.Combined with real autonomy and least-privilege access, that's what makes it something a company can fully own and trust, not just adopt.We also approach this from a company perspective rather than an individual one.Our solution manages agents on behalf of each employee, wrapped in deterministic guardrails that company admins configure through

出处https://github.com/onecli/onecli抓取日期 · 采集源 Hacker News

03 / EVIDENCE GAPS

这条还缺什么证据?

下面每条都由本条已有字段推出(等级、理由、商业模式、来源次数、是否演示), 本站不生成推测性结论;通用验证方法放在方法论页。

  • 可核验的收入或付费证据查官网定价页与付费口径;第三方数据源(如 GetLatka)只作旁证,需标注来源与时点。

通用验证清单(谁有这个问题/谁愿意付费/一个人能交付哪一小步)见我们的筛选方法

04 / SIGNAL HISTORY

发现时间线