tensorlakeai/dsh-tensorlake-sandbox

Name: tensorlakeai/dsh-tensorlake-sandbox
Author: tensorlakeai

Plugin插件 Native原生 ⭐ 6 MIT Approval & Security审批与安全

用于tensorlake沙箱的deepseek框架插件

Project Overview项目介绍

Edited by Zhiwei Agent (zhiwei)由知微Agent(zhiwei)编辑

This is a native DeepSeek Harness (DSH) plugin that offloads all of DSH’s file operations, subprocess calls, Bash terminal sessions, and LSP operations into a short-lived microVM sandbox managed by Tensorlake. Distributed as an installable DSH bundle, it does not require any modifications to your existing DSH installation to work. After installing DSH globally via npm, you can add this plugin directly to your headless DSH profile with a single CLI command, and it automatically replaces DSH's default host sandbox providers after installation.

This plugin is designed for DSH users who need an extra layer of isolated sandbox security for their AI agent operations. After configuring the required API keys for Tensorlake and DeepSeek as environment variables, you can run any DSH task in headless mode with the sandbox fully enabled. All file and terminal operations are handled by the isolated Tensorlake microVM, so no untrusted code executed by the agent can directly access your host machine’s filesystem or core processes.

The plugin is released under the open source MIT license, and requires Node.js version 22.19.0 or newer, or Node 24 and above, plus DSH version 0.1.0-rc.6 or a newer compatible release. Currently, the Tensorlake SDK dependency used by this plugin has transitive dependencies with unpatched high-severity security vulnerabilities. If you plan to use this plugin in a production environment, you should review the upstream security advisories before deploying, and wait for a patched SDK release from Tensorlake if you are concerned about the risk.

这是一款专为 DeepSeek Harness 开发的原生插件，可将 DSH 中的文件操作、子进程调用、Bash 终端和 LSP 操作全部迁移到 Tensorlake 的短效微 VM 沙箱中运行。它以可安装的 DSH 包形式分发，无需修改现有 DSH 安装，用户可直接通过 DSH CLI 命令将其添加到现有 DSH 配置文件中使用。

它面向需要增强操作隔离安全性的 DSH 用户，典型工作流程是用户预先在环境变量中配置好 Tensorlake API 密钥和 DeepSeek API 密钥，安装插件后即可通过无头模式运行各类 DSH 任务，所有文件、终端操作都会在隔离微 VM 中执行，不会影响宿主机环境。

该插件遵循 MIT 许可协议，依赖 Node.js 22.19.0 以上版本以及 0.1.0-rc.6 及以上版本的 DSH，目前依赖的 Tensorlake SDK 存在依赖项高危漏洞，暂未有官方修复版本，用户使用前需要查阅上游安全公告，生产环境使用需谨慎。

View on GitHub在 GitHub 查看

Send to your DSH发给你的 DSH 安装

请帮我安装这个 DSH 插件。安装前先完成【兼容性检查 + 安全性检查】，检查通过再动手。

插件：dsh-tensorlake-sandbox（tensorlakeai/dsh-tensorlake-sandbox）
仓库：https://github.com/tensorlakeai/dsh-tensorlake-sandbox
本站详情页：https://www.yhbd.top/plugins/tensorlakeai-dsh-tensorlake-sandbox/
本站登记：类型 plugin · 归类 原生 DSH 插件 · 许可证 MIT · ⭐ 6 · 最近提交 2026-08-14 · 主语言 TypeScript

按下面顺序执行，每步先把结论告诉我，再进入下一步：

【1 兼容性检查】
① 我这边：DSH 版本、Node 版本、操作系统、当前 profile（web / desktop）。
② 读它的 README、package.json、插件 manifest，列出它要求的 DSH 版本 / Node 版本 / 操作系统 / 外部依赖 / 需要另外先装的运行时。
③ 逐条比对，结论只写「满足 / 不满足 / 未知」三种；不满足的给出可行替代方案。
④ 检查是否和我已装的插件冲突：命令名重复、skill / tool 重名、端口占用、重复注册的 MCP server。

【2 安全性检查】
① 仓库可信度：和上面「本站登记」是否一致；star / fork 数、创建时间、最近提交，是否归档或长期停更。
② 安装脚本：逐行看 package.json 的 preinstall / install / postinstall，以及 install.sh、setup.ps1 之类脚本。出现 curl|bash、下载后直接执行、混淆代码、访问与插件功能无关的域名，立刻停下来告诉我，不要继续装。
③ 依赖：列出新增依赖，标出无人维护、或与知名包拼写近似的可疑包（typosquatting）。
④ 权限与副作用：它会读写哪些目录、访问哪些域名、需要哪些 DSH 权限（filesystem / network / shell / clipboard 等），以及怎么卸载和回滚。
⑤ 如果它要求 sudo / 管理员权限，或权限明显超出功能所需，先停下来问我。

【3 安装】
上面两步没有「不满足」和「高危项」时才执行；用官方推荐方式安装，不要自行提权。

【4 汇报】
用表格输出：检查项 / 结论 / 依据 / 是否需要我决策。拿不准的一律写「未知」并说明要我怎么确认——不要猜，也不要替我决定。

Send this message to DSH in your current session: it verifies compatibility and security first (answering met / not met / unknown item by item) and only installs once everything checks out — it will stop and ask you if it finds a high-risk item. The box scrolls; the copy is the full prompt. CLI install commands may not be accurate across systems, so DSH is the safer route.把上面这条消息直接发给当前会话里的 DSH：它会先核对兼容性与安全性（逐条给「满足 / 不满足 / 未知」），确认没问题再安装，有高危项会停下来问你。框内可滚动，复制到的是完整提示词；安装命令不一定准确，发给 DSH 更稳。

Pre-install check安装前体检Compatibility · Security兼容性 · 安全性 1 warning1 项注意

Only 6 stars - very few users, little community feedback星标只有 6，几乎没人在用，遇到问题缺少社区反馈

DSH walks through these 9 checksDSH 会逐条核对这 9 项

Compatibility兼容性

DSH, Node, OS and profile requirementsDSH 版本 / Node 版本 / 操作系统 / profile 是否满足要求
External dependencies and runtimes (Electron / Python / Docker, ...)外部依赖与运行时（Electron / Python / Docker 等）是否齐备
Conflicts with installed plugins: command names, skill / tool names, ports, duplicate MCP registration与已装插件是否冲突：命令名、skill / tool 重名、端口占用、重复 MCP 注册

Security安全性

Repo matches the facts registered here; archived or abandoned?仓库是否与页面登记一致，是否归档或长期停更
Safety of preinstall / install / postinstall and install.sh / setup.ps1preinstall / install / postinstall 与 install.sh、setup.ps1 是否安全
curl|bash, download-then-execute, obfuscation, unrelated domains → stop immediatelycurl|bash、下载即执行、混淆代码、无关域名 → 立刻停止
Typosquatting or unmaintained packages among the new dependencies新增依赖里有没有 typosquatting 或无人维护的包
Requested permissions vs. what the feature actually needs申请了哪些权限、是否超出功能所需（filesystem / network / shell / clipboard）
Any sudo / admin requirement, plus uninstall and rollback是否要求 sudo / 管理员权限，以及卸载与回滚方式

Anything uncertain must be marked unknown with a note on how to confirm it. This site's signal screen is a static snapshot, not a security audit.拿不准的必须标「未知」并说明要我怎么确认。本站的信号筛查是静态快照，不能替代安全审计。

Or use CLI install (for developers)或使用命令行安装（适合开发者）

CLI Install命令行安装

dsh plugin --profile headless add @tensorlakeai/dsh-sandbox

把 tensorlakeai/dsh-tensorlake-sandbox 加入你的 DSH 配置（web profile）即可启用。

READMEREADME

5.4 KB · 缓存于 2026-08-23 03:41:31 · 5.4 KB

Tensorlake sandbox for DeepSeek Harness

@tensorlakeai/dsh-sandbox moves DeepSeek Harness file, subprocess, Bash, terminal, and LSP operations into one short-lived Tensorlake microVM. It is an installable dsh bundle and does not require changes to the Harness installation.

Prerequisites

Node.js ^22.19.0 or >=24.0.0
@deepseek-ai/dsh 0.1.0-rc.6 or a later compatible release
A Tensorlake project with TENSORLAKE_API_KEY set in the host environment
DEEPSEEK_API_KEY set in the host environment for the default DeepSeek model provider

Keep credentials in environment variables or a secret manager; do not commit them to the profile or repository.

Install

Install dsh and add this bundle to the profile you run:

npm install --global @deepseek-ai/dsh
dsh plugin --profile headless add @tensorlakeai/dsh-sandbox
TENSORLAKE_API_KEY=... DEEPSEEK_API_KEY=... dsh --profile headless "build and test this repo"

During development, install a local checkout from its directory:

npm install
npm run build
dsh plugin --profile headless add .

Use dsh --profile headless --dump-config to verify that the @tensorlakeai/dsh-sandbox layer disables the host subprocess and fs-sandbox providers, inserts the Tensorlake runtime, subprocess, and filesystem rows, and keeps bash-sandbox mounted in danger-full-access mode. In that mode Harness's sandbox-aware Bash executor delegates directly to the Tensorlake subprocess provider while still satisfying the permission-preset capability contract.

Smoke test

Run one headless task that exercises both the subprocess and filesystem providers:

dsh --profile headless \
  "Use Bash to run pwd and id. Create smoke-test.txt containing hello, read it back, and report the results."

A successful run reports /home/tl-user/workspace from pwd, the tl-user identity from id, and reads hello back from the file. The model-facing working directory is the same remote Linux path, so the response should not mention or fall back from a host-machine path.

Configuration

The bundle starts an ephemeral sandbox on profile boot and terminates it when dsh exits. The runtime module accepts these Cordis config fields:

Showing the opening section of the README — the full document lives in the repository以上为 README 开头摘要，完整文档在仓库内 · View the full README on GitHub →在 GitHub 查看完整 README →

渲染基于仓库 tensorlakeai/dsh-tensorlake-sandbox 的 README.md。在 GitHub 查看原文 →