Guide

Lovable Security Issues: What Is Documented and How to Fix Them

By Lucas Weber, CyberSec42 · Updated 28 Oct 2026

Lovable ships with its own security checks: a quick scan that runs every time you publish and a deeper scan you start on demand. According to Lovable, though, you are responsible for making sure your app protects its users' data. The most widely documented Lovable security issue is database access rules that let other people's data through. A Lovable app is only secure once you have checked, before launch and with two test accounts plus no account at all, that every user can reach only their own data.

What is publicly documented about Lovable security issues

Search for "lovable security incident" and you will mostly find two kinds of sources: a CVE entry from 2025 and Lovable's own documentation. Both describe the same underlying failure pattern, but they draw different conclusions from it.

The CVE entry: CVE-2025-48757

CVE-2025-48757 was published on 30 May 2025. The record reads in full:

"An insufficient database Row-Level Security policy in Lovable through 2025-04-15 allows remote unauthenticated attackers to read or write to arbitrary database tables of generated sites. NOTE: this is disputed by the Supplier because each individual customer of the Lovable platform accepts a responsibility over protecting the data of their application."

The record maps the issue to CWE-863 (Incorrect Authorization) and carries a CVSS 3.1 base score of 9.3 (critical). The NVD lists the same text, tagged "disputed" and "exclusively-hosted-service". If you run an app, the dispute over who is responsible matters less than what both sides agree on: when an access rule is missing or too broad, the data is exposed, and the rules of your app are yours to get right.

What Lovable says itself

Lovable is open about the topic. In its "Secure Vibe Coding" blog post of 9 June 2025, the company explains that Lovable apps connected to Supabase rely on Row Level Security, and that data can be exposed if policies are missing or overly broad. Lovable says it integrated Supabase's Security Advisor for this, and adds that while the scan catches many issues, incorrect database security setups sometimes slip through.

The current Lovable security documentation (retrieved 28 Oct 2026) is even more explicit:

• Misconfigured RLS rules are described as a common cause of data leaks.
• The tools help identify common issues but cannot guarantee complete security.
• You are responsible for making sure your app meets the security requirements of its use case, especially if it handles sensitive data.
• For apps handling sensitive data or critical functionality, Lovable suggests an additional professional security review.

That is a fair division of labor: the platform provides tooling and flags common mistakes, while deciding who may see what stays with whoever runs the app. How Row Level Security works, which policy mistakes are common and what correct policies look like is covered in depth in our guide to Supabase Row Level Security best practices. This article focuses on everything around it.

Why generated apps tend to fail at access control

There is no reliable statistic we could cite here. The mechanics, however, are easy to explain, and they apply to Lovable just as much as to Bolt, Cursor, v0 or any other tool that turns a description into an app.

You describe what the app should do, not what it must not do

A prompt like "users can upload and view invoices" is a positive requirement. The negative requirement, that user A must never see user B's invoices, is rarely spelled out. The tool builds what was described, and the result works. Whether it allows too much goes unchecked in the normal flow, because when you test with your own account you only ever see your own data.

Errors only appear when rules are too strict

An access rule that is too narrow produces an error: the list stays empty, saving fails. A rule that is too broad produces nothing at all, everything just works. Paste the error back into the chat and you get a change that makes the app work again, which may loosen exactly the rule that was meant to protect your data. The workflow rewards opening things up and never notices when something should have stayed closed.

Security decisions end up in the browser

A hidden admin button, a price calculated in the frontend, a login check that lives only in React code: to the person who built it, this looks like protection. Lovable's security best practices are clear that frontend code runs in the user's browser, where it can be inspected, modified or bypassed, and should never make security decisions. Anyone calling the API directly never sees the button.

Server-side functions bypass the database rules

For payments, emails or AI calls, Lovable generates server-side code such as Edge Functions. According to Lovable's guide, server-side code that uses the privileged service role bypasses Row Level Security, so that code has to check permissions itself: who is calling, and are they allowed to perform this action? These functions can also be called from outside, without going through your app's interface. A function that only checks whether someone is signed in, not whether the record belongs to them, opens a path around the database rules.

The app grows one prompt at a time

Each new feature often brings new tables, columns or storage buckets. Last week's security state says little about the state after twenty more changes. Lovable's own pre-publish checklist explicitly includes making sure new tables are not missing policies. If you checked once, you checked an old version.

AI features bring their own attack surface

Many apps built with AI include AI features themselves: a chat, a summary, an assistant. There, user input or content from documents can steer the model into actions the user would not be allowed to take directly. If the AI feature holds more permissions than the person using it, prompt injection becomes a way around your access rules. More on that in our article on prompt injection and tool poisoning.

What the Lovable security scan does and does not do

Compared with the 2025 blog post, the current documentation describes several layers:

According to the documentation, running the Quick scan and the Deep scan is free. Workspaces can also connect optional integrations from third-party security vendors, including dynamic, AI-driven penetration tests.

The limits, as Lovable describes them

• Static analysis. By Lovable's own description, the built-in scanners read code and configuration and flag patterns that look risky. They do not sign in as two different users and try to reach one account's data from the other.
• No substitute for a thorough review. The documentation says so explicitly, and the overview of the built-in backend describes its automated database checks as "Not a full audit".
• The Deep scan does not run by itself. Publishing triggers the Quick scan only. The review of your application code is something you have to start.
• The scan only knows your business rules from your code. That only members of the same team may see an invoice, or that users must not upgrade their own plan, can only be checked if that rule is recognizable somewhere. If it is missing entirely, there is nothing to find.

Lovable itself recommends an order: run the security scanners first, fix what they surface, then validate with a penetration test before a major release. Scanners and tests with real accounts complement each other; neither replaces the other.

The Trust center that Lovable offers for published apps is, according to the documentation, an informational page and not a certification.

Lovable security checklist before launch

Only test apps you own or have explicit permission to test. None of these items require specialist knowledge, just time and two test accounts.

For internal tools that should not be public, also set the project visibility in Lovable to the workspace and confirm the app has not been published publicly.

When an external security check makes sense

For a prototype with test data, the checklist above is enough. Once real users and real data are involved, the equation changes. An external check is worth it especially if one of these applies:

• The app processes personal or sensitive data, such as health, financial or contract data.
• Several customers, teams or tenants share the app and must not see each other.
• There are payments, credits or unlockable features.
• A launch to paying customers, an investor conversation or a business customer's security questionnaire is coming up.
• Nobody on the team has actually read and understood the access rules.

The difference from a scan is the method. A manual review works against the running app with several test accounts and deliberately tries to break out of one account into another. Every finding is backed by reproducible evidence. That is what our security check for AI-built apps is designed for. If personal data is actually accessed in an incident, this can trigger a notification duty under Article 33 GDPR. Whether it applies in a given case is a legal question. This article is not legal advice.

Frequently asked questions

Further reading

• Vibe coding security checklist
• Supabase Row Level Security Best Practices
• API pentest checklist
• Choosing a pentest provider
• Service: Security check for AI-built apps

Sources

• CVE.org: CVE-2025-48757
• NVD: CVE-2025-48757
• Lovable Docs: Security overview
• Lovable Docs: Security best practices for Lovable apps
• Lovable Docs: Built-in backend
• Lovable Blog: Secure Vibe Coding (9 June 2025)
• Supabase Docs: Understanding API keys
• EUR-Lex: General Data Protection Regulation (EU) 2016/679