▍ Compare
vibecheck vs Wiz vs Snyk vs Lovable's scan.
Honest comparison of four scanners that overlap with vibecheck. We don't badmouth competitors — every tool here is built for a specific audience, and the differences explain why all four exist.
The short version
Capability matrix.
All four detect security issues. The differences are in audience, scope, depth, and price.
| vibecheck | Wiz | Snyk | Lovable's scan | |
|---|---|---|---|---|
| Built for | Solo devs, small teams | Enterprise security teams | Mid–large dev teams | Lovable users |
| Price | Free / $29 / $99 | Quote (~$10k+ ARR start) | Free tier limited; teams $$$ | Free with Lovable |
| Read-only | ✓ | partial (full visibility) | partial | ✓ |
| Cross-platform (any deployed URL) | ✓ | ✓ | source code only | Lovable apps only |
| AI-stack tokens (HF, Replicate, Pinecone…) | ✓ | — | — | — |
| RLS policy SQL generation | ✓ | — | — | partial |
| Free for solo devs forever | ✓ | — | free tier limited | ✓ |
| Agent-friendly (MCP server) | ✓ | — | — | — |
| Source-code SAST (static analysis) | — | ✓ | ✓ | partial |
| Cloud infrastructure visibility | — | ✓ | — | — |
| Compliance reports (SOC 2, ISO) | — | ✓ | ✓ | — |
The long version
One paragraph per tool. Use-when callout each.
vibecheck
What we built. Inspects deployed URLs from outside — same vantage as an attacker. Detects exposed credentials, open Row-Level Security, leaked secrets across 52 patterns including the AI inference stack (HF, Replicate, Pinecone, Cohere, Together, Groq, Anyscale, Modal, fal.ai, ElevenLabs, Perplexity). Generates Row-Level Security policy SQL for any open Supabase tables found. MCP server lets agents call it pre-merge.
Wiz
Cloud-native security platform. Sees your whole AWS/GCP/Azure footprint via cloud-API integrations, identifies misconfigured assets, traces attack paths through your infrastructure. Heavy lift to set up; designed for security teams that own a budget. Their research on vibe-coded apps is what surfaced the 20% misconfig stat we cite.
Snyk
Static analysis of your source code: dependency CVEs, code patterns, container images, IaC. Strong on supply-chain risk; the dependency CVE database is best-in-class. Doesn't see what your deployed bundle exposes — if a regex matches a leaked key in your .env, Snyk catches it; if it ships into your bundle and is reachable at runtime, Snyk doesn't have visibility.
Lovable's built-in scan
Lovable shipped a security check after the March 2026 incident. Catches the most common Lovable-specific issues during build (missing RLS scaffolding, env var prefix mistakes, default-permissions bugs). Only covers Lovable-built apps. Stops at the platform boundary.
Honest takes
How we actually fit alongside.
vibecheck is not a Wiz replacement. If you have multi-cloud infrastructure with attack-path complexity, Wiz earns its price. We compete on price for solo devs, not capability for enterprises.
vibecheck and Snyk are complementary. Snyk reads your source; we read your deploy. A leaked secret committed to your repo + then deleted may live forever in git history (Snyk catches it) but never ship to production (vibecheck doesn't see it). A secret pasted into a Vite env var with the wrong prefix ships to production every time (vibecheck catches it) but may never appear in source review (Snyk misses it). Run both.
vibecheck and Lovable's scan are stacked. Lovable scans during build; vibecheck scans after deploy. Each catches issues the other doesn't. If you're a Lovable user, run both.
What vibecheck doesn't do:
- Source-code static analysis (Snyk territory)
- Dependency CVE matching (Snyk, Dependabot, Renovate)
- Cloud infrastructure visibility (Wiz, Lacework, Aqua)
- SOC 2 / ISO 27001 evidence collection (Drata, Vanta, Tugboat Logic)
- Application-layer DAST against authenticated routes (Burp Suite Pro, Acunetix)
- Active credential validation against the issuing service (we never use a key we find)
If you need any of those, use the right tool for the job. We're narrow on purpose.
What stays unique
Three differentiators that compound.
Three things vibecheck does that we expect to remain unique for a while:
- AI-stack token coverage. Every week another AI inference startup ships an API. We add the regex within a day. By the time an enterprise scanner adds Pinecone or fal.ai support (if they ever do), we'll be five providers ahead. The catalogue of 52 secret patterns is at /llms-full.txt § Family 3.
- RLS policy SQL generation. Detection is becoming a commodity. The actionable output is the differentiator. Six pattern templates today; LLM-driven for edge cases coming in v0.5.
- Agent-friendly JSON API + MCP server. Most security tools optimize for human security engineers. We optimize for AI agents that pull JSON, parse it, decide. Stable rule names, severity enum, structured evidence. /agents for the integration shapes.