Mitigant

io.github.mitigant由 GitHub 帳號 mitigant 發布v0.1.0更新於 Oct 25, 2026

在AWS、Azure和GCP上執行真實的、可自動恢復的雲攻擊,以測試你的防禦能力。

AI 翻譯由 AI 模型根據下方的原文描述翻譯,可能有誤。

原文描述

Run real, auto-recovered cloud attacks on AWS, Azure and GCP to test your defenses.

已驗證Streamable HTTP可網頁執行雲端與基礎設施

概覽

Mitigant 的託管 MCP 服務(mcp.mitigant.io);需要 API 金鑰;Streamable HTTP;10 個工具。

暫無 AI 概覽:以下資訊來自註冊中心條目和服務本身。

端點
mcp.mitigant.io
最近檢查

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Mitigant,將其新增到工作區。
  2. 連接 apiToken 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 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.mitigant%2Fmitigant-mcp/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。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "mitigant": {
      "type": "http",
      "url": "https://mcp.mitigant.io/mcp",
      "headers": {
        "apiToken": "<YOUR_API_KEY>"
      }
    }
  }
}

README

該儲存庫沒有 README。

工具

10

list_attacks

Browse Mitigant's attack actions -- atomic tests that each emulate one attacker technique -- that you can launch on their own against AWS, Azure or GCP. Currently 111 attack actions (AWS 49, Azure 36, GCP 26). Returns each action's attackName (show this to the user) and attackType (an opaque id -- pass this, not attackName, to get_attack_details or launch_attack), what it does, its impact, the MITRE ATT&CK technique it maps to, and its orchestration type (PROVISIONED or INLINE -- see orchestration_filter for what these mean). Optionally filter by cloud service (S3, IAM, ...), category, or orchestration type. Some attack actions run only as steps inside a scenario and appear via list_scenarios / get_scenario_details, not here. Start here to find an attack action to run.

輸入參數cloud_service必填service_filtercategory_filterorchestration_filter

get_attack_details

Full description, impact, MITRE mapping, and orchestration type (PROVISIONED or INLINE -- PROVISIONED attacks create and destroy their own target rather than targeting your existing infrastructure (they may still read or use existing resources along the way), so they're the lower-risk, production-viable choice; INLINE attacks find and attack an existing resource in the account) for one attack, by the action key from list_attacks. Result includes attackName (show this to the user) alongside the attackType you passed in (an opaque id, not for display).

輸入參數action_key必填cloud_service必填

launch_attack

Run an attack against a cloud account connected to Mitigant and return the result once it finishes. This performs real actions on real cloud infrastructure -- it is not a simulation. Confirm with the user before calling: if their request could match more than one attack in list_attacks (similar names, or an underspecified description like "the security group attack"), show them the matching candidates with their names and descriptions and have them pick one -- don't guess which attack they meant.

輸入參數regionaccount_no必填action_key必填cloud_service必填

list_cloud_accounts

List the cloud accounts available for attack emulation -- any account not listed here cannot be attacked, so check this before guessing an account_no for launch_attack. An empty result means no accounts are onboarded for attack emulation (for that cloud, or at all), not a failure -- the account may still exist in Mitigant for other purposes (e.g. posture scanning) without being eligible here. Each result's accountNo is already the value launch_attack expects; accountName is for display to the user. defaultRegion is the region attacks against that account run in by default (and where their evidence is collected); it can be overridden per attack request, but unless you do, actions target that region. State it when telling the user where an attack will run.

輸入參數cloud_service

list_scenarios

List Mitigant's attack scenarios -- multi-step chains that combine several attack actions run in sequence, so treat a scenario as having the combined blast radius of every step. Currently 45 scenarios (AWS 26, Azure 12, GCP 7). Returns each scenario's scenarioName (show this to the user) and scenarioKey (an opaque id -- pass this, not scenarioName, to get_scenario_details or launch_scenario), plus description, impact, and the step-by-step composition (each attack action's name, service, MITRE mapping, and impact). Use this to find a multi-step chain to run; use list_attacks instead for a single attack action.

輸入參數cloud_service必填

get_scenario_details

Full details for one attack scenario -- description, impact, and the step-by-step composition, by the scenario key from list_scenarios. A scenario runs several attacks in sequence; this returns every step, not just the first. Result includes scenarioName (show this to the user) alongside the scenarioKey you passed in (an opaque id, not for display).

輸入參數scenario_key必填cloud_service必填

launch_scenario

Run a multi-step attack chain against a cloud account connected to Mitigant and return the result once every step finishes. This performs real actions on real cloud infrastructure, as several attacks in sequence -- it is not a simulation, and its blast radius is the combined blast radius of every step. Confirm with the user before calling: if their request could match more than one scenario in list_scenarios, show them the matching candidates with their names and descriptions and have them pick one -- don't guess which scenario they meant.

輸入參數regionaccount_no必填scenario_key必填cloud_service必填

get_attack_status

Get the current report for a previously launched attack, including its clean-up state. Returns the attack report plus a 'cleanup' summary with cleanUpComplete and a plain-language statement. Only tell the user the account is back to its pre-attack state when cleanup.cleanUpComplete is true -- while anything is pending or failed, clean-up is not done, so report it as in progress and check again rather than implying all-clear. A pending clean-up is usually the DELIBERATE inspection window, not a stall: read cleanup.statement and relay it, and poll no faster than that -- a few minutes -- rather than reporting a fault.

輸入參數attack_id必填

clean_up_attack

Clean up a previously launched attack, restoring the cloud resources it changed back to their pre-attack state. Clean-up is normally AUTOMATIC after a short, deliberate inspection window (so the team can verify the attack and collect evidence first); calling this kicks it off immediately rather than waiting out that window. It is NOT a fix for a stall, and it ends that window early -- removing the attack's artifacts before the team may have finished inspecting them -- so only use it when the user explicitly wants the account restored now. This triggers clean-up and returns immediately -- clean-up runs in the background, so a success here means the request was accepted, not that clean-up is done. Confirm the account is actually restored by polling get_attack_status until cleanup.cleanUpComplete is true; do not tell the user it is restored based on this call alone.

輸入參數attack_id必填cloud_service必填

get_attack_evidence

Get the evidence Mitigant collected for a previously launched attack -- what the account's own logging (CloudTrail, GuardDuty) recorded about it. Returns an 'evidence' summary (counts, sources, and a plain-language statement) plus the raw records, each with an evidenceUrl that opens the matching console entry. Use it to show the user what their defenses saw, especially during the clean-up inspection window. Important: an empty result shortly after an attack is normal -- logging delivery lags by minutes -- and an attack whose purpose is to disable logging is expected to leave none, so never report an empty result as the attack leaving no trace; re-check instead. Read evidence.statement and relay it.

輸入參數attack_id必填

版本歷史

1
  1. v0.1.0最新Oct 25, 2026

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