FixVibe
Covered by FixVibehigh

Securing the MVP: Preventing Data Leaks in AI-Generated SaaS Apps

Rapidly developed SaaS applications often suffer from critical security oversights. This research explores how leaked secrets and broken access controls, such as missing Row Level Security (RLS), create high-impact vulnerabilities in modern web stacks.

CWE-284CWE-798CWE-668

Attacker Impact

An attacker can gain unauthorized access to sensitive user data, modify database records, or hijack infrastructure by exploiting common oversights in MVP deployments. This includes accessing cross-tenant data due to missing access controls [S4] or using leaked API keys to incur costs and exfiltrate data from integrated services [S2].

Root Cause

In the rush to launch an MVP, developers—especially those using AI-assisted "vibe coding"—frequently overlook foundational security configurations. The primary drivers of these vulnerabilities are:

  • Secret Leakage: Credentials, such as database strings or AI provider keys, are accidentally committed to version control [S2].
  • Broken Access Control: Applications fail to enforce strict authorization boundaries, allowing users to access resources belonging to others [S4].
  • Permissive Database Policies: In modern BaaS (Backend-as-a-Service) setups like Supabase, failing to enable and correctly configure Row Level Security (RLS) leaves the database open to direct exploitation via client-side libraries [S5].
  • Weak Token Management: Improper handling of authentication tokens can lead to session hijacking or unauthorized API access [S3].

Concrete Fixes

Implement Row Level Security (RLS)

For applications using Postgres-based backends like Supabase, RLS must be enabled on every table. RLS ensures that the database engine itself enforces access constraints, preventing a user from querying another user's data even if they have a valid authentication token [S5].

Automate Secret Scanning

Integrate secret scanning into the development workflow to detect and block the push of sensitive credentials like API keys or certificates [S2]. If a secret is leaked, it must be revoked and rotated immediately, as it should be considered compromised [S2].

Enforce Strict Token Practices

Follow industry standards for token security, including using secure, HTTP-only cookies for session management and ensuring tokens are sender-constrained where possible to prevent reuse by attackers [S3].

Apply General Web Security Headers

Ensure the application implements standard web security measures, such as Content Security Policy (CSP) and secure transport protocols, to mitigate common browser-based attacks [S1].

How FixVibe tests for it

FixVibe already covers this data-leak class across multiple live scan surfaces:

  • Supabase RLS exposure: baas.supabase-rls extracts public Supabase URL/anon-key pairs from same-origin bundles, enumerates exposed PostgREST tables, and performs read-only anonymous SELECT checks to confirm whether table data is exposed.
  • Repo RLS gaps: repo.supabase.missing-rls reviews authorized GitHub repository SQL migrations for public tables that are created without a matching ALTER TABLE ... ENABLE ROW LEVEL SECURITY migration.
  • Supabase storage posture: baas.supabase-security-checklist-backfill reviews public Storage bucket metadata and anonymous listing exposure without uploading or mutating customer data.
  • Secrets and browser posture: secrets.js-bundle-sweep, headers.security-headers, and headers.cookie-attributes flag leaked client-side credentials, missing browser hardening headers, and weak auth-cookie flags.
  • Gated access-control probes: when the customer enables active scans and domain ownership is verified, active.idor-walking and active.tenant-isolation test discovered routes for IDOR/BOLA-style cross-resource and cross-tenant data exposure.