vibecheck
vibecheck
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 / CIWhat 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 | 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.
Related MCP server: Zfuzz
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, JWTnone). These fail--ciand are what the MCPscantool 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--ciand from the agent loop by default, so agents never chase phantom work. Add--allto 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
python3on PATH; Go scanning requires agotoolchain 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 agotoolchain 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, CommonJSrequire/dynamicimport(), 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@staticmethodresolution, intra-file and cross-file via resolvedfrom .mod import/import mod; not resolved:import a.bdotted-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; unaliasedpkg.Funcresolves 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.
Available Tools
1 toolscanA
Scan a project directory for vibe-coding security / ship-readiness issues (offline, no AI). Returns high-confidence (taint-backed) findings as JSON by default; pass includeAll:true for medium/review too. Run before declaring a coding task done.
Inputs: dir, includeAll.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusing it with other tools. Agents will always select the correct tool.
With a single tool, naming consistency is trivially maintained. The name 'scan' is a clear verb that matches its action.
A single tool is on the low end for a server, but it is acceptable for a narrowly focused utility that performs one well-defined task. The tool covers a specific security scanning need without requiring multiple operations.
The one tool handles the primary scanning operation with configurable output levels, but lacks supporting tools for managing scan history, configurations, or results. It covers the core function but leaves gaps for typical workflows.
Maintenance
Related MCP Connectors
Zero-config MCP security scanner for AI-generated apps. 25K+ vulnerability patterns.
Security firewall for AI agents — scans MCP calls for injection, secrets, and risks.
Security scanner for AI agents: prompt injection, leaked secrets, PII, and SSRF-risk URL detection.
Security scanner for AI-written code: SAST, secrets, dependencies, IaC, containers and DAST.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceEnables scanning of AI agent code for security vulnerabilities such as prompt injection, tool abuse, and data exfiltration, directly from MCP-compatible clients like Claude Code.41 PyPI3LGPL 3.0
- AlicenseNot gradedqualityCmaintenanceReal security scanners for AI coding agents — SAST (441 rules), secret detection (419+ patterns), dependency CVEs (OSV.dev), MCP/skill vetting, MITRE ATT&CK. Open-source, Rust, free13 npmApache 2.0
- AlicenseNot gradedqualityCmaintenanceSecurity scanner for MCP servers — vet an MCP before you wire it into an agent. Detects prompt-injection, credential exfiltration (via taint analysis), RCE, and supply-chain risks, and catches cross-server exfil chains no single server reveals. Zero-dependency local CLI, SARIF output, CI-gateable, no account.63 npmMIT
- AlicenseCqualityDmaintenanceSecurity scanner and MCP server that catches dangerous patterns in MCP servers and AI agent projects, such as leaked secrets, shell execution, and prompt-injection text. Runs as both a CLI and MCP server with CI-friendly severity gates.21MIT