原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Offense

作者:offense-research版本 0.7.0i★ –i在云端运行
注册名称io.github.offense-research/offense

安装

概览

作者提供的说明(英文原文)

Security tools for coding agents: dependency advisory audits and evidence for remediation.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://offense.sh/mcp

在终端中运行这条命令

claude mcp add --transport http offense https://offense.sh/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "offense": {
      "url": "https://offense.sh/mcp"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "offense": {
      "type": "http",
      "url": "https://offense.sh/mcp"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://offense.sh/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 offense-research 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32433 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32433 个服务器的 84% 更新
  • 基础检查结果等于或优于此分类中其他 32433 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Offense 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.7.0)于6天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

Symantec Cloud DLP AIops

作者:AIops-tools

Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Offense

Security tools your AI agent can discover, call and verify.

Offense is a product by [Offense Research, Inc.](https://offenseresearch.com). Open-source software, optional paid hosting.

Give Pi, OMP, Hermes, Codex, Claude Code, Crush or another coding agent the tools to audit dependencies, inspect source and workflows, and test a proposed fix. Offense returns structured security evidence through CLI, MCP and HTTP. Your agent reads that evidence, investigates your code, makes authorized changes and runs your tests—with its existing model, repository access and permissions.

Open-source repository · Discord · Hosted service · Self-hosting · Contributing · Report a vulnerability

Start here: Give this to your agent · Add with a PR · Recipes · Install the CLI · Agent installation · Choose a mode · Local quick start · MCP setup · Self-hosted platform · Documentation · Troubleshooting · Community

Add Offense to your repository with a PR

Add Offense to your repo →

Enter your GitHub repository and base branch. The installer opens GitHub's prefilled workflow editor; review the file, choose Create a new branch, then open a pull request. No Offense account, API key or GitHub token is required. Offense prepares the link; you create and approve the PR on GitHub.

The starter adds free npm/pnpm dependency audits on pull requests using pinned, read-only GitHub Actions. It never installs or runs your app, edits code or calls paid Offense tools. Dependency metadata goes to OSV/npm; reports are retained as GitHub artifacts for seven days. Advisories are report-only; coverage warnings and scan errors fail the check. GitHub Actions usage limits and charges still apply. This is a dependency check, not the full tool catalog.

Review the template · Manual installation, privacy and updates

Give this to your agent

Paste this into your coding agent in the project you want to check:

Set up Offense for this project. Read the installation instructions at

https://github.com/offense-research/offense#install-the-offensesh-agent-skill and review the skill at https://raw.githubusercontent.com/offense-research/offense/main/.agents/skills/scanning-with-offense/SKILL.md

Reuse an existing reviewed Offense checkout or connection if available. Otherwise inspect the public source before using its helpers. Install the skill in this agent's project-local skill directory, preserving custom files and other agent settings. Tell me if a new session or project trust is needed.

Run only the offline dependency-input preview. Show the selected lockfiles, unsupported inputs and which execution mode would perform the real audit. Do not upload data, run a paid scan, install the target project's dependencies, edit application code, commit or push.

The first success is a real preview and an explicit scope, not “installed” without a command result. The agent needs terminal/filesystem access and Node; copying a skill does not give a chat-only client those capabilities. If it cannot read GitHub pages, use the raw skill URL or a reviewed local checkout.

Already configured? Ask: “Use Offense to check my app for security problems, explain the findings and consequences, and help me decide what to fix.” Offense infers relevant checks from the project, reports missing coverage, and asks only for the inputs or authorization those checks need. Assessment alone does not authorize application edits or paid calls. Narrow dependency and local-only requests keep their scope.

Start with one of the task prompts below. Prefer manual setup? Use the per-agent instructions.

Recipes from the landing page

Codex plugin

The native plugin is built from the same maintained skill and CLI in this repo. To try a local checkout with Codex:

codex plugin marketplace add /absolute/path/to/offense

codex plugin add offense@offense

Start a new Codex session, then ask $offense:offense to check your app and explain the findings. Installing does not log in, scan, buy credit or register MCP. The plugin reuses existing connections or its bundled CLI. Codex owns updates; credentials stay in the CLI's private configuration. If you already installed a manual Offense skill, choose which entry point to keep; customized skills and project instructions are never removed automatically.

Once these files are published on the repository's default branch, the intended remote registration is codex plugin marketplace add offense-research/offense, followed by codex plugin add offense@offense. The local path has been smoke tested; the remote command requires verification against that published ref. Public OpenAI directory listing is a separate submission, not part of this build.

Put the examples on offense.sh to work. Each recipe includes an agent prompt, prerequisites, commands, approval boundaries and the evidence to return. Start with a single reviewed run before adding recurring automation.

Build or runRecipe
Your dependency bot / a pre-release auditAudit dependencies and verify reviewed upgrades
Your first reviewerReview a PR with source evidence
Your secrets guardCheck staged or tracked contents without confusing the snapshots
A SQL-injection reviewTrace request input, parameterize and test
Your CI reviewerReview Actions YAML without executing workflows
Your API testerExercise a disposable local API with bounded requests

These are recipes for your agent, not installed schedules, hooks or bots. Local scanners need their pinned engines; hosted Gitleaks needs availability, upload approval and a spending ceiling. See the shared setup and limits.

What you can do

  • Find vulnerable dependencies. Inventory npm/pnpm lockfiles, query OSV advisories and inspect upgrade options with the independent local engine.
  • Give your agent actionable context. Produce structured findings and a repository-specific remediation prompt; use explicit triage and rehearsal commands when you need deeper evidence.
  • Check source and GitHub Actions workflows. Run pinned Opengrep and Zizmor engines through the self-hosted API/MCP profile in isolated Docker containers.
  • Discover tools before running them. Inspect coverage, supported inputs, availability and price quotes. A directory listing is not a promise that a tool is enabled on your deployment.
  • Use the same job workflow across clients. Submit bounded jobs, retrieve results and preserve partial/failed outcomes through the CLI, MCP or HTTP API.

Offense is not an autonomous permission grant. A finding is not a confirmed exploit, an advisory match is not proof of reachability, and a partial scan is not a clean bill of health. Your agent remains responsible for reviewing changes and obtaining authorization before active testing, paid calls or publication.

From a finding to a reviewed fix

See From a finding to a reviewed fix.

Ask for the outcome you want

See Ask for the outcome you want.

What your agent should read and return

See What your agent should read and return.

Export a PDF report locally

See Export a PDF report locally.

Choose how to run it

ModeBest forRequirementsExecution and cost
Local dependency engineAuditing a project from your terminal or coding agentNode.js 24+, npm; no Docker or Offense account for dependency analysisRuns on your machine; queries public OSV/npm metadata; no Offense usage charge
Self-hosted platformRunning your own API, MCP endpoint and isolated source scannersLinux amd64, Node.js 24+, npm, Git and Docker EngineYour infrastructure; dependency audits, Opengrep and Zizmor enabled; Offense billing disabled
Hosted serviceUsing managed tool execution without operating the scanner infrastructureAn Offense account for authenticated toolsRuns on the service; enabled paid tools use quoted prepaid credit

The local engine and self-hosted profile do not require an Offense subscription or model-provider key. Advisory lookup still needs network access; “local” does not mean an offline advisory database. You pay your own infrastructure costs when self-hosting.

Install the CLI

See Install the CLI.

Homebrew — macOS and Linux

See Homebrew — macOS and Linux.

Stable GitHub release — Node.js 20+

See Stable GitHub release — Node.js 20+.

Ubuntu and Arch Linux

See Ubuntu and Arch Linux.

npx / npm exec — run without a global install

See npx / npm exec — run without a global install.

npm — install the command globally

See npm — install the command globally.

pnpm or Bun — one-off execution

See pnpm or Bun — one-off execution.

From a reviewed checkout — no package manager install

See From a reviewed checkout — no package manager install.

After installation

See After installation.

Quick start: local dependency analysis

Use Node.js 24 or newer, npm and Git. This path does not start a server, install Docker scanners or require an account.

git clone https://github.com/offense-research/offense.git

cd offense npm --prefix offense ci --ignore-scripts

Inspect the runtime and preview supported dependency inputs without network calls.

node offense/bin/offense.mjs doctor /absolute/path/to/your-project node offense/bin/off

只显示了开头部分;其余内容请在仓库中阅读

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