Security vulnerabilities exposed in Lovable-showcased EdTech app

A security researcher discovered multiple critical vulnerabilities in an EdTech application showcased as a success story on the Lovable platform. Lovable is a $6.6B "vibe coding" platform that features apps built with their tools.
Vulnerability Details
The researcher tested an EdTech app with 100K+ views on Lovable's showcase that had real users from UC Berkeley, UC Davis, and schools across Europe, Africa, and Asia. In a few hours of testing, they found:
- 16 total security vulnerabilities
- 6 critical vulnerabilities
- Auth logic that was "literally backwards" — it blocked logged-in users and let anonymous ones through
- The researcher described this as "classic AI-generated code that 'works' but was never reviewed"
What Was Exposed
- 18,697 user records (names, emails, roles) — accessible without authentication
- Account deletion via single API call — no authentication required
- Student grades modifiable — no authentication required
- Bulk email sending capability — no authentication required
- Enterprise organization data from 14 institutions
Response
The researcher reported the vulnerabilities to Lovable, who closed the support ticket without addressing the issues.
📖 Read the full source: r/ClaudeAI
👀 See Also

OpenClaw Security: 13 Practical Steps to Lock Down Your AI Agent
A Reddit post outlines 13 security measures for OpenClaw installations, including running on a separate machine, using Tailscale for network isolation, sandboxing subagents in Docker, and configuring allowlists for user access.

KnightClaw: Local Security Extension for OpenClaw Agents
KnightClaw is a drop-in extension that intercepts messages before they reach OpenClaw agents, providing an 8-layer hybrid detection system and egress redaction. It runs entirely local with zero telemetry and is MIT licensed.

Caelguard: Open-source security scanner for OpenClaw skills
Caelguard is an MIT-licensed, locally-run scanner that detects security issues in OpenClaw skills, including prompt injection, credential harvesting, and obfuscated payloads. Research shows approximately 20% of published skills contain concerning patterns.

From Farm to Code: How a Farmer Created an Open-Source Runtime Defense for OpenClaw
Discover how a farmer, with no prior development experience, created an open-source runtime defense for OpenClaw using multiple AI coding agents in just 12 hours.