Base44: Built-In Security Scan with Automatic Fixes for App Vulnerabilities

Overview

Base44 introduced a built-in Security Scan feature designed to surface common but critical misconfigurations in AI-generated apps before they reach production. The tool addresses a systemic challenge in rapid, AI-assisted development: security issues that experienced developers typically catch through code review tend to be invisible to builders who are moving fast with natural language prompts.

What the Security Scan Checks

The scanner analyzes apps across three distinct vulnerability categories:

Missing or Overly Permissive Row-Level Security

Database tables without row-level security (RLS) rules -- or with rules that are effectively open to all -- represent one of the most common data exposure risks in AI-generated apps. Base44's scan identifies these gaps and flags which tables are potentially accessible to unauthorized users. For each finding, the tool provides a plain-language explanation of what the misconfiguration means and what data could be at risk.

Exposed API Keys and Credentials in Frontend Code

Secrets embedded in client-side JavaScript are a pervasive problem in apps built quickly without a backend secrets management layer. The scan inspects frontend code for API keys, tokens, and credentials that could be extracted by anyone who inspects the page source or network requests. Findings include the specific location of the exposure and guidance on how to move the secret server-side.

Backend Functions Without User Authentication

Backend functions that perform sensitive operations -- reading user data, triggering actions, modifying records -- without verifying the caller's identity are a common source of privilege escalation and unauthorized data access. The scan flags each unprotected function and explains what an attacker could do by calling it directly.

How Automatic Fixes Work

For each finding, Base44 provides a one-click fix option that applies a safe default remediation. Importantly, fixes are not applied automatically -- developers review the proposed change before it takes effect. This design keeps the developer in control while eliminating the friction of manually researching and implementing the correct security configuration.

For RLS issues specifically, the suggested fixes apply standard permission rules that restrict access to authenticated users or the record's owner, depending on the table's apparent purpose. Developers can accept the suggestion as-is or adjust it before applying.

AI-Assisted Permission Configuration

Beyond the one-click defaults, Base44 also offers AI-driven permission setup for cases where the correct access rules are more nuanced. Builders can describe their access requirements in plain language -- for example, "only the app owner and their invited collaborators should be able to read this table" -- and the AI translates that description into the appropriate RLS rules. This lowers the barrier for builders who understand their app's security requirements conceptually but are unfamiliar with the syntax of database permission systems.

Context: Security in AI-Generated Apps

The release comes on the heels of significant scrutiny around the security posture of apps built with AI coding tools. Research from security firm Wiz found a critical vulnerability in Base44's own platform -- demonstrating that even the tools themselves are not immune. Separately, Imperva documented critical flaws in Base44 that exposed sensitive user data and enabled account takeovers. Studies examining AI-generated codebases broadly have found that a substantial share of apps leak data or expose credentials in ways that traditional development workflows typically catch during review.

By embedding security analysis directly into the build experience, Base44 aims to make secure-by-default the path of least resistance, even for builders who may not have a security background.