GuardCue VS GuardLayer

GuardCue's answer

Most security scanners are written for developers and report in technical terms. GuardCue is written for the person who built the app with an AI tool and cannot read code. Every problem says what it could cost you, how we know, and the exact words to paste into Claude Code, Lovable, Bolt, Cursor or any other AI tool to fix it. Then it checks your live site again to prove the fix worked. It also runs inside those tools, so they can check and fix in one step.

GuardLayer's answer:

GuardLayer scans one stack deeply — Next.js + Supabase — instead of trying to cover everything. That focus lets it catch the specific, high-impact mistakes these apps actually ship: a Supabase servicerole key exposed through NEXTPUBLIC_, tables with Row Level Security disabled or a policy that isn't scoped to the user, webhooks that never verify their signature, and Server Actions with no auth check. It's precision-tuned to stay quiet on safe code (it won't flag a publishable anon key as a leaked secret), so you get real findings with the exact fix — not a wall of noise. The full engine is free on your first repo, no signup or card.

GuardCue's answer

Three reasons. It shows proof, not guesses: when it says a table is open, it read rows from it without signing in. It avoids false alarms: a public product list is called fine, a customer table is called a breach. And it closes the loop: the fix is written for your AI tool, and a second check confirms it on the live site. The first check is free, with no sign up.

GuardLayer's answer:

General scanners like Snyk, Semgrep, and GitGuardian are powerful but broad — they don't know that a Supabase anon key is safe to commit while a service_role key is catastrophic, or that a Next.js Server Action is a public endpoint anyone can call. GuardLayer encodes that stack-specific knowledge, so every finding maps to how Next.js + Supabase apps really break, with the fix inline. It's free to start (full scanner on one repo), runs in seconds as a GitHub Action or a hosted scan, and it's open source (MIT) — no lock-in, nothing to trust blindly.

GuardCue's answer

Founders and small teams who built an app with Claude Code, Lovable, Bolt, Cursor, v0, Replit, Base44 or any other AI tool, often without a developer, and want to know it is safe before they launch or take payments. Agencies that build apps this way for clients can use it too.

GuardLayer's answer:

Solo founders, indie hackers, and small teams shipping SaaS on Next.js + Supabase — especially people building fast with AI tools like Lovable, Cursor, v0, and Claude. That workflow ships working apps quickly but repeatedly leaves the same security gaps: RLS left off, keys exposed to the browser, routes with no auth check. GuardLayer is the safety net for developers who want to ship fast without a dedicated security team.

GuardCue's answer

GuardCue started in September 2026 at Hexspire, a small software studio. People were launching apps built with AI tools in a weekend, and the same mistakes kept showing up: databases anyone could read, secret keys in the page, paid services anyone could run up. The tools that find these problems were written for developers, so the people most at risk could not use them. We built GuardCue to explain each problem in plain English and hand over the fix. Our first study of 50 public AI-built apps found a secret key in the code of 18 of the 47 we could read.

GuardLayer's answer:

GuardLayer grew out of a pattern: AI-built and "vibe-coded" apps kept shipping the same Supabase mistakes — most visibly the 2025 wave of Lovable projects with Row Level Security left off, exposing user data through the public API key (CVE-2025-48757). The tools that catch this tend to be enterprise-priced and stack-agnostic, which doesn't fit a solo builder moving fast on Next.js + Supabase. So GuardLayer was built to encode exactly those failure modes into a free, precision scanner that runs on every push and hands you the fix — putting the checks a security engineer would run in reach of a one-person team.

GuardCue's answer

TypeScript, Node.js and Next.js, with a PostgreSQL database. Claude by Anthropic helps write the plain English explanations, and every finding is confirmed by a fixed, repeatable check before anyone sees it. It also uses open source scanners including Semgrep, Gitleaks, OSV-Scanner and Retire.js.

GuardLayer's answer:

Next.js (App Router) and TypeScript, styled with Tailwind CSS, backed by Supabase (Postgres, Auth, Row Level Security), deployed on Vercel, with Stripe for billing and a GitHub App plus an open-source GitHub Action for CI integration. The scanner engine itself is a dependency-light static-analysis library written in TypeScript.