Agent Verify

io.github.AI-Blockchain-Ventures由 GitHub 帳號 AI-Blockchain-Ventures 發布v2.0.0更新於 Nov 7, 2026

面向AI代理和MCP設定的安全檢查:124項已測試的檢查,來自你的AI編碼助理。

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

Security checks for AI agents and MCP configs: 124 tested checks, from your AI coding assistant.

已驗證STDIO僅桌面AI 與機器學習

概覽

Agent Verify 的本機 MCP 服務;無需登入;STDIO;3 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。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Agent Verify,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Agent Verify

Know what your AI agent can do before you deploy it.

Agent Verify inspects an AI agent or agent package — its permissions, tools, MCP connections, execution controls, secrets, runtime configuration, and dependencies — and issues a VERIFIED or NOT VERIFIED result with evidence, before the agent reaches production.

Traditional security tools scan software. Agent Verify also examines what an AI agent is connected to and what those connections may let it actually do — a legitimate credential, valid API access, and an approved tool can still combine into an action the agent should never be able to take.

Agent Verify provides open-source CLI, CI, web integration, and API tooling backed by a proprietary verification engine — see Privacy & proprietary scanner boundary.

Architecture

Dashboard ─┐CLI ───────┼──► Worker API ──► server-side entitlement & scan quota ──► private scanner engineAPI ───────┘         │                      └──► D1 (billing/quota) · Firestore (reports, orgs, audit log)

Every scan — from the dashboard, the CLI, or a direct API call — goes through the same authenticated Worker route and the same server-owned monthly quota; there is no client-only or local-storage-based scan counter anywhere in the product, and no browser code ever runs the detection engine directly. See Web App and Privacy & proprietary scanner boundary for how that boundary is enforced and verified.

What this repo contains — open source vs. proprietary

ComponentLocationLicense
Web app (dashboard, reports, landing page)apps/webOpen source (this repo, MIT)
CLI / SDK (agentverify on npm)packages/cliOpen source (this repo, MIT)
Cloudflare Worker APIworkers/apiOpen source (this repo, MIT)
Detection engine (@agentverify/scanner)packages/scannerProprietary — not in this repository

Quick Start — CLI

bash
npm install -g agentverifyagentverify scan ./agents --key av_your_key

Get an API key from Dashboard → API access after signing in at https://aimodularity.com/agentverify/. Full docs, including the API contract, CI/CD integration, and JSON output shape: https://aimodularity.com/agentverify/docs/

bash
agentverify --helpagentverify --versionagentverify scan ./agents --key av_your_key           # scan a directoryagentverify scan --file agent.json --key av_your_key   # scan a single fileagentverify scan ./agents --key av_your_key --ci        # CI mode, strict exit codesagentverify scan ./agents --key av_your_key --ci --policy standard  # + policy evaluation

CI exit codes distinguish a real security failure from an execution problem:

CodeMeaning
0All scanned files verified
1NOT_VERIFIED — a real security/verification failure
2NOT_ASSESSED — insufficient evidence for a verdict
3Execution error — bad/missing API key, network failure, missing file (not a security finding)

GitHub Action

yaml
- uses: AI-Blockchain-Ventures/[email protected]  with:    path: ./agents    api-key: ${{ secrets.AGENTVERIFY_API_KEY }}

See docs/github-action.md for the full reference — Markdown/JSON output modes, PR comment posting, branch protection, and policy evaluation in CI.

Web App

The dashboard (apps/web) provides scan history, report sharing, a check catalog, policy profiles, and organization/team management (roles: Owner/Admin/Member/Viewer) on top of the same Worker API the CLI uses — every dashboard scan is server-metered exactly like a CLI or API scan, never run or counted client-side.

What Agent Verify analyzes

Permissions and tool access, MCP server connections and what they expose, execution/authorization controls, secrets and credential handling, runtime configuration, and dependencies — static analysis of submitted content, not a live sandbox execution.

Verification output

  • VERIFIED — sufficient execution context was assessed and the required trust controls passed.
  • NOT VERIFIED — sufficient execution context was assessed and one or more security or protocol controls failed.
  • NOT ASSESSED — the submitted content didn't contain enough agent execution context to make a decision. This is not a security failure, and it must never be read as VERIFIED.

Every finding is also labeled by how it was derived: definite (a concrete pattern was matched), heuristic (inferred from context — could be a false positive/negative), or informational (a neutral observation). Agent Verify does static analysis — it never executes submitted code — so it is honest about what it cannot see: see Limitations below.

Artifact fingerprinting / signed attestations

Every scan computes a SHA-256 artifact fingerprint over the exact scanned content — identical content always produces the same fingerprint, independent of when it ran or whether the ruleset changed since. When server-side signing is configured, a scan result can carry a signed attestation (ECDSA P-256 / ES256) over the verdict, score, and fingerprint — independently verifiable by any third party with nothing more than the published public key, with no shared secret and no need to trust Agent Verify's API at verification time.

Policies

Built-in policy profiles (standard, high-security, financial-agent, production-infrastructure) can be evaluated against a scan's evidence in addition to — never instead of — the base verdict: a scan can be VERIFIED and still fail a stricter policy, but a policy can never turn a NOT_VERIFIED scan into a pass. Pass --policy <id> on the CLI or the policy input on the GitHub Action.

Security model

Billing, quota, and authentication are server-authoritative — see docs/billing-setup.md for the full architecture. Webhook payloads are signature-verified and processed idempotently, organization mutations are RBAC-enforced server-side (never trusting a client-supplied role), and Firestore Security Rules enforce per-user access control independently of the UI. Full detail and how to report an issue: SECURITY.md.

Privacy & proprietary scanner boundary

The detection engine — the actual rules that decide what's risky — is Agent Verify's core IP and is intentionally not tracked in this git repository (packages/scanner/ is gitignored). The CLI and Worker call it over HTTPS or via a private build; nothing in this public repo bundles or exposes its source, and no browser-shipped code ever imports it — only Worker-side (server-only) code does. A permanent CI check (npm run check:private-boundary) builds the web app and statically inspects every emitted client bundle for known proprietary markers on every change, so this boundary can't silently regress. Public CI validates the web app, CLI, and Worker against a type-compatible stub of the scanner (see scripts/create-ci-scanner-stub.mjs) so the public build is verifiable without the private engine ever being present.

Plans

Free (10 scans/month, basic findings, private report history), Pro ($19.99/month — full remediation guidance, corrected snippets, A2SPA implementation guidance, PDF export, 100 scans/month), Team (coming soon), Enterprise (contact us). Pricing is defined once in apps/web/src/lib/pricing.ts and mirrored in the Worker's quota table (workers/api/src/billing.ts) — see those files for the current source of truth.

Documentation

Development

bash
npm installnpm run dev              # apps/web dev servernpm run build             # apps/web production buildnpm run build:cli         # packages/clinpm run build:worker      # workers/apinpm run lint               # apps/webnpm run check:web          # apps/web typechecknpm run check:worker       # workers/api typechecknpm run test:worker        # workers/api testsnpm run test --workspace=packages/clinpm run test:rules         # Firestore Security Rules against the real emulatornpm run check:private-boundary  # proprietary-boundary regression check

See CONTRIBUTING.md for the full contributor guide, including what you can and cannot modify and PR expectations.

Limitations

Agent Verify performs static analysis of submitted content. It does not execute your agent and cannot see: runtime-only behavior, permissions/credentials granted dynamically at deploy time, remote policy enforced outside the codebase, production network ACLs, external identity provider policy, or runtime secrets injected outside the source. Every report includes a "What Agent Verify Could Not Determine" section stating this explicitly for that scan. Findings are evidence-based and heuristic, not a formal proof of security — a clean report is not a guarantee of safety, and a finding is not proof of exploitation.

License

MIT — AI Blockchain Ventures LLC — [email protected]

MIT applies to the components in this repository (web app, CLI, Worker API) as listed above. The detection engine is proprietary, is not distributed under this license, and is not included in this repository.

來源:README.md,提交 438180f

工具

3

scan_path

Scan agent files

Scan an AI agent for security risks before it is deployed: dangerous tool permissions, prompt injection paths, exposed secrets, risky MCP servers, missing approval gates, SQL/SSRF/code-execution risks, and framework-specific issues (LangChain, CrewAI, AutoGen, OpenAI Agents SDK, Claude Agent SDK). Give a file or a folder; a folder is scanned as one report using the most important agent files (up to 60 files / 5MB). Returns a verdict, a 0-100 security score (higher is safer) and findings with file and line.

輸入參數path必填

scan_code

Scan agent code

Scan a snippet of agent code, a tool definition, a system prompt or an MCP config for security risks. Use this for code that is not saved to a file yet. Returns a verdict, a security score and findings.

輸入參數content必填fileName

scan_mcp_config

Check my MCP servers

Check the MCP servers configured on this computer (Claude Code, Claude Desktop, Cursor, VS Code, Windsurf) for risks such as broad filesystem access, unpinned packages, remote servers without auth, auto-approved tools and API keys stored in plain text. Only the server definitions are read, and secret values are masked on this computer before anything is sent.

輸入參數path

版本歷史

1
  1. v2.0.0最新Nov 3, 2026

評分

已滿足適用檢查項的 90%

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25 分
  • 已宣告認證方式10 分

    請在註冊中心條目中宣告憑證請求標頭,或保持端點能夠回應探測,以便判定其認證方式。

  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分