
Aribot
io.github.aristiun由 GitHub 帳號 aristiun 發布v1.0.0更新於 Oct 24, 2026
Threat modeling, code/cloud/pipeline scanning, shadow-AI discovery, compliance checks and fixes.
概覽
Aribot 是託管的安全 MCP 伺服器,讓助理建立威脅模型、掃描程式碼、流水線與雲端帳戶、檢查合規並提出修復建議。
- 可以做什麼
- 依系統圖或文字描述產生並重新建立威脅模型,涵蓋 STRIDE 與 LINDDUN,並可從威脅追溯到需求、控制與修復;在程式碼中驗證威脅,檢查 NIST、ISO 27001、SOC 2 等框架的涵蓋情況並回報合規狀態,也可評估第三方供應商。執行程式碼、CI/CD 流水線、雲端組態與 SBOM 掃描,並找出環境中擴散的影子 AI 使用與 API 端點。以程式碼、雲端組態或基礎設施即程式碼形式取得修復方案,並檢視計費與用量資訊。
- 適用情境
- 適合在現有助理中完成安全工作:把設計轉成威脅模型,檢查程式碼儲存庫、流水線或 AWS、Azure、GCP 帳戶,追蹤合規缺口,或為某個發現取得修復建議而不必切換工具。
- 執行需求
- 遠端 streamable HTTP 端點,需 OAuth 2.1 登入(授權碼加 PKCE,動態用戶端註冊);不需本機套件或環境變數。存取受公司授權、授予的 OAuth 範圍與團隊角色限制,因此需要已授權的帳戶與租戶。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Aribot,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.aristiun%2Faribot/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"mcpServers": {
"aribot": {
"type": "http",
"url": "https://mcp.aribot.ayurak.com/mcp"
}
}
}README
Aribot — MCP server for security work
Live page: https://aristiun.github.io/aribot-mcp/ · Product: https://aribot.ayurak.com · Registry: io.github.aristiun/aribot
Aribot is a security tool from Ayurak / Aristiun, available as a remote Model Context Protocol (MCP) server. Connect it to any MCP client — ChatGPT, Gemini, Claude, or your own — and run real security work from the assistant you already use, without switching tools.
This repository is a public manifest for the hosted server. It contains no product code — only the connection details. The server requires OAuth, so listing its address exposes nothing without an authorized login.
Unified threat modeling — one model, not five tools
Aribot builds one threat model per system and layers every discipline onto it — security (STRIDE + LINDDUN), cloud posture (AWS · Azure · GCP), compliance (NIST · ISO 27001 · SOC 2), and the economics of each risk (value at risk, cost to fix, dollars saved once healed) — all kept traceable end to end:
Threat → Requirement → Control → Framework → Code → Fix
Ask for any link in that chain, in either direction, with evidence behind every finding and every fix.
What you can do with it
Threat modeling
- Turn a diagram or a written description of a system into a full threat model
- STRIDE and LINDDUN coverage, generated per component and per data flow
- Threats mapped to the security controls, requirements, and compliance frameworks that address them
- A traceability view from each threat → finding → control → requirement → remediation
- Re-model as the design changes; link related diagrams and reuse component threat libraries
Scanning
- Code security — static analysis of a connected repository
- Pipeline security — CI/CD configuration and supply-chain checks
- Cloud & compliance — posture checks across AWS, Azure, and GCP accounts
- SBOM — generate a software bill of materials
- Shadow AI & API discovery — find where AI/LLM use and API endpoints have spread across your estate
Compliance
- Coverage and control status against NIST, ISO 27001, SOC 2, and other frameworks
- See which controls a threat model or scan already satisfies, and where the gaps are
Vendors
- Assess a third party's posture and fold it into your own risk view
Remediation
- Get a fix for a finding — as code, cloud configuration, or infrastructure-as-code
- Keep it advisory, or apply it (e.g. open a pull request or push a cloud change) under approval
Connect
Point any MCP client at the server and complete the OAuth prompt:
OAuth is discovered automatically at https://mcp.aribot.ayurak.com/.well-known/oauth-authorization-server.
Example (Claude Code):
Access controls
Each call is checked against your company's licence, the OAuth scopes you granted (read:findings, read:threatmodel, read:insights, run:scan, run:codereview, write:threatmodel, run:remediation), your team's roles, and your tenant boundary. Usage is metered, and every action is logged. So you can run security work from an assistant without losing track of who can do what, or which company's data is which.
Tools
generate_threat_model · verify_threats_in_code · get_traceability · get_framework_coverage · compliance_status · discover_shadow_ai · get_api_security · get_cloud_compliance · get_remediation · get_billing
See the full tool list and pricing at https://ayurak.com/pricing.
© Ayurak / Aristiun. "Aribot" and "Ayurak" are trademarks of their owner. This manifest is provided for MCP discovery under the MIT License (see LICENSE).
來源:README.md,提交 429a244
工具
0版本歷史
1- v1.0.0最新Sep 16, 2026
評分
已滿足適用檢查項的 85%
該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。
- 近 30 天內可連通必需25 分
- 已宣告認證方式必需10 分
- 已列出工具15 分
請讓伺服器在無憑證時回應 tools/list,或發布可在沙箱中無憑證啟動的軟體包。
- 描述必需15 分
- 圖示10 分
- 文件15 分
- 授權條款10 分