Your AI Tool Scored 40/100

100/100

health score

We formally verified real applications built with the tools you use every day.

Bolt

0/100

3 criticals

Lovable (App 1)

0/100

2 criticals

Lovable (App 2)

0/100

1 critical

Replit

0/100

2 criticals

21 bugs found4 platforms0 passed verification

What we found

One critical finding per platform. Selected from 21 total.

criticalBolt

38/100

Authentication bypass on protected routes

Any user can access admin panels without login

criticalLovable (App 1)

42/100

Payment webhook handler returns 200 without processing

Payments are acknowledged but never recorded in database

criticalLovable (App 2)

45/100

Dashboard metrics computed from hardcoded seed data

"Live" charts show fabricated numbers disconnected from actual usage

criticalReplit

35/100

Analytics page displays entirely hardcoded mock data

"Real-time insights" is fabricated. Zero connection to actual data sources.

See all 21 findings →

This is real AI-generated code. Watch what happens when we verify it.

api/subscribe/route.ts

1export async function POST(req: Request) {

2 const { email, plan } = await req.json()

4 // Verify user authentication

5 const user = getCurrentUser()

Returns { id: "demo" } — no actual auth checkNO-OP

7 if (user) {

8 const subscription = await createSubscription({

9 userId: user.id,

10 plan,

11 status: 'active'

Status set to "active" without checking paymentHARDCODED

12 })

14 await sendConfirmation(email)

Function body is empty — email never sentEMPTY

15 return Response.json({ success: true })

16 }

18 return Response.json({ error: 'Unauthorized' }, { status: 401 })

19}

100/100

health score

Every tool checks if AI code compiles.
None check if it's correct.

We built the tool that does. Formal verification — mathematical proof that code does what it claims. Not vibes. Not another LLM checking another LLM's homework.

100%

pass@3 on HumanEval

+36%

vs baseline on SWE-bench

Other approaches actually get worse with more iterations. LLM-as-judge drops from 99.4% to 97.2% at k=5 — false positives cause regression. LUCID is the only method that converges monotonically to 100%.

See the full report