vibecheck

vibecheck

Agent-native "safe to ship?" security gate for AI-generated code. Uses real parsers and inter-rocedural taint analysis (JS/TS, Python, Go) to flag the classes AI coding agents get wrong — secrets, SQL injection, SS, SSRF, path traversal, command injection, weak JWT/CORS — and ranks findings by confidence. Exposes a scan tool over MCP.

Category
访问服务器

README

vibecheck

ci License: MIT

A fast, agent-native "safe to ship?" gate for vibe-coded apps. It parses your JS/TS/JSX/TSX (@babel/parser), Python (the stdlib ast), and Go (go/parser) with real parsers and uses taint analysis (inter-procedural for JS/TS, Python, and Go — return-taint + param→sink summaries, within a file and across files) to flag the security classes AI coding agents get wrong — committed secrets, SQL injection through abstracted raw-query APIs, XSS, SSRF, path traversal, command injection, insecure deserialization, weak JWT/CORS/cookies — and ranks every finding by confidence so an agent can fix the real ones and ignore the noise.

vibecheck .          # human report (severity + confidence)
vibecheck . --ci     # exit 1 only on high-confidence (taint-backed) issues
vibecheck . --json   # machine-readable findings for agents / CI

What it is — and what it is not (read this)

vibecheck is not a replacement for Semgrep or CodeQL. Those are deeper, broader, multi-language engines and you should run them for full coverage. vibecheck aims to be better on one narrow, measurable axis: a low-false-positive, taint-backed gate for the AI-vibe-coding failure classes that runs inside agent loops and pre-commit in milliseconds, with published precision/recall so you can trust the --ci/MCP signal. Use it alongside the big engines, not instead of them.

vibecheck Semgrep CodeQL
Parsing real AST (Babel JS/TS/JSX + Python ast) real, many langs real, many langs
Data-flow inter-procedural (return-taint + param→sink; intra-file + cross-file by import) taint (Pro) full inter-procedural
Languages JS/TS/JSX/TSX + Python + Go many many
Speed / infra ms, local, no account fast slower, CI-oriented
Agent-native (MCP, confidence gating) yes, first-class partial no
Breadth of rules small, focused 2000+ huge

If you only adopt one general SAST, adopt Semgrep or CodeQL. Adopt vibecheck as the fast agent/CI pre-flight that won't drown an agent in false positives.

Measured quality (not claimed)

Against a labeled benchmark of 91 cases across JS/TS, Python and Go (vulnerable + safe + deliberately tricky-safe), the core detectors score (see METRICS.md, reproduce with bun benchmark/run.ts):

  • Precision 100%, Recall 100%, F1 100% on the corpus.

The tricky-safe cases that produce zero false positives include: parameterized queries, tagged- template SQL, numeric-coerced and schema-validated input, ORM/RegExp .exec(), Supabase anon / Stripe publishable keys, hardened cookies, allow-listed CORS, and pinned JWT algorithms — exactly the patterns a regex linter trips on. This benchmark is curated; for a real-world measurement (9 pinned OSS repos, 1,218 files, manually triaged), see docs/CORPUS.md — which exposed a critical bug (Python/Go files weren't being scanned in real scans) and drove precision fixes (relative redirects, server-source-only SSRF).

Confidence

Every finding has a confidence:

  • high — a user-input source provably flows into the sink (taint-backed), or a deterministic fact (committed secret, JWT none). These fail --ci and are what the MCP scan tool returns by default.
  • medium — a dangerous sink on a non-literal value with no proven source (e.g. eval(x)).
  • review — a structural smell that needs a human (e.g. a route with no visible auth). Excluded from --ci and from the agent loop by default, so agents never chase phantom work. Add --all to include them.

Install & use

npm i -D @arisrhiannon/vibecheck    # or: bun add -d @arisrhiannon/vibecheck (Node >= 20)
vibecheck . --ci
vibecheck explain VC-SQLI
vibecheck mcp           # MCP stdio server exposing a `scan` tool (high-confidence by default)

Agents: see AGENTS.md — run vibecheck . --ci before declaring a task done and fix every high-confidence finding.

JS/TS scanning needs nothing extra. Python scanning requires python3 on PATH; Go scanning requires a go toolchain on PATH (the analyzer is compiled once and cached). If a runtime is absent those files are skipped; if an analyzer fails, a warning is printed to stderr (so a crash never silently drops findings).

Rules (implemented + benchmarked)

Taint-backed: VC-RCE-EVAL, VC-RCE-CHILD-PROCESS, VC-SQLI, VC-XSS-REACT, VC-XSS-DOM, VC-SSRF, VC-PATH-TRAVERSAL, VC-OPEN-REDIRECT. AST config: VC-CORS-WILDCARD, VC-JWT-NONE, VC-JWT-UNPINNED, VC-COOKIE-INSECURE, VC-STACK-EXPOSURE. Provenance/secrets: VC-SECRET-* (8), VC-ENV-COMMITTED/DRIFT/MISSING, VC-NEXT-PUBLIC-SECRET, VC-SUPABASE-SERVICE-ROLE. Advisory: VC-ROUTE-NO-AUTH (review), VC-INPUT-NO-VALIDATION. Python (VC-PY-*): VC-PY-RCE, VC-PY-CMDI, VC-PY-SQLI, VC-PY-DESERIALIZE, VC-PY-YAML, VC-PY-SSTI, VC-PY-OPEN-REDIRECT, VC-PY-PATH. Go (VC-GO-*): VC-GO-CMDI, VC-GO-SQLI, VC-GO-PATH, VC-GO-OPEN-REDIRECT, VC-GO-SSRF. vibecheck explain <id> prints the fix for each.

Limitations

  • JS/TS/JSX/TSX + Python + Go (Python needs python3, Go needs a go toolchain on PATH). More languages are roadmap (each via its own real parser, never hand-rolled).
  • Taint scope: JS/TS taint is inter-procedural with real cross-file module resolution — function summaries carry return-taint and parameter→sink reachability, resolved within a file and across files via resolved relative imports (named, aliased a as b, and namespace * as ns), propagated multi-hop by a fixpoint; sanitizers respected. Not tracked (false negatives): re-exports (export { x } from …), default exports, CommonJS require/dynamic import(), bare/package imports, chains deeper than ~7 hops in worst-case file order, methods, and destructured params. Python is also inter-procedural (return-taint + param→sink and class @staticmethod resolution, intra-file and cross-file via resolved from .mod import/ import mod; not resolved: import a.b dotted-unaliased, */re-exports, decorators). Python request sources span Flask, Django, aiohttp (request.match_info, await request.post()), FastAPI/ Starlette (request.query_params/path_params, await request.json()/form()), Tornado, Bottle, Pyramid. Go is inter-procedural within and across packages (return-taint + param→sink; unaliased pkg.Func resolves by package name). Aliased package imports (import u "…/util") and multi-return assignments (x, _ := f(src)) are not tracked.
  • Config/secret rules are pattern-based where AST adds no value.
  • A high-signal gate and early-warning — not a proof of security. Pair it with Semgrep/CodeQL and review.

Config — .vibecheck.json

{ "ignoreRules": ["VC-INPUT-NO-VALIDATION"], "allowPaths": ["test/**"], "failSeverity": "high" }

License

MIT © 2026 Aris Rhiannon — see LICENSE.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选