PolyDefender Research Blog
Security guides for every module and every vulnerability
Browse our pillar content, cluster playbooks, and original research for AI platform modules and vulnerability classes, with practical remediation and internal pathways to scan and harden your app.
How to Secure a Lovable App (Step-by-Step, Non-Technical)
A practical checklist founders can follow to lock down a Lovable app before launch, even without a security team.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
How to Fix Supabase RLS Fast: Founder-Friendly Playbook
The exact workflow to identify missing Row Level Security, patch policies safely, and validate fixes in production.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
My API Key Got Leaked — What Do I Do? 30-Minute Incident Plan
A calm, practical response plan for leaked OpenAI, Stripe, Supabase, and other production secrets.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Is My Lovable, Replit, or Claude App Secure? A Non-Technical Check
A plain-English way to estimate security risk in AI-built apps before users or investors see your product.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
How to Check If Your AI Website Is Hacked
A quick triage process for suspicious behavior, unauthorized changes, and hidden data exfiltration in AI websites.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
I Audited 10 Lovable Apps. Here's What I Found
Cross-app findings from ten Lovable production audits, including recurring exploit paths and the fastest fixes.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
State of AI App Security Q2 2026
Original PolyDefender research on 18,200 production scans, including the most common exploitable gaps, median fix times, and platform-level risk distribution.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
AI Security Posture for Startups in 2026: The Fast Path to Baseline Coverage
A practical operating model for teams shipping AI features weekly without introducing critical security debt.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Lovable + Vercel Vulnerability Chains in 2026: How Real Exploits Unfold
A deep incident-style breakdown of common Lovable and Vercel misconfiguration chains, from initial leak to privilege expansion and containment.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Lovable Security Module: Detection, Exploit Paths, and Fixes
How to harden Lovable apps against leaked secrets, weak RLS, and authorization drift — the three recurring critical finding categories in every Lovable audit.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Bolt.new Security Module: Detection, Exploit Paths, and Fixes
Production hardening steps for Bolt.new projects — covering credential safety, CORS misconfigurations, broken auth in generated handlers, and the unique risks of WebContainer-based development.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Cursor Security Module: Detection, Exploit Paths, and Fixes
Detection and remediation playbook for the security patterns that appear most often in Cursor-generated code — auth gaps, injection vulnerabilities, and credential handling anti-patterns.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Replit Security Module: Detection, Exploit Paths, and Fixes
Stop Replit production misconfigurations before they lead to account takeover or data exposure — covering environment variables, public-by-default behavior, and database access control.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
v0 + Next.js Security Module: Detection, Exploit Paths, and Fixes
Guardrails for v0-generated Next.js deployments — covering Server Actions security, source map leaks, broken access control in API routes, and the specific risks of Vercel-hosted AI apps.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Claude App Builder Security Module: Detection, Exploit Paths, and Fixes
Reduce prompt injection, tool abuse, and data exfiltration in Claude-built applications and AI-powered workflows — the security issues that do not appear in traditional web app scanners.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
API Key Exposure: Detection and Remediation Guide
Leaked API credentials in client bundles, logs, source maps, and misconfigured environment variables — how to find them, rotate them, and prevent recurrence.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Missing Supabase RLS: Detection and Remediation Guide
Tables without Row Level Security policies expose your entire database to unauthorized reads and writes. Here is the exact detection, patching, and validation workflow.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Prompt Injection: Detection and Remediation Guide
Untrusted input manipulates model behavior, triggering unauthorized actions or data disclosure. How to detect, test for, and defend against prompt injection in AI-powered applications.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
IDOR and Auth Bypass: Detection and Remediation Guide
Endpoints that trust client-supplied IDs without server-side ownership checks allow any authenticated user to access any other user's data. How to find and fix every instance.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
Hallucinated Dependencies: Detection and Remediation Guide
AI coding tools sometimes invent package names that do not exist. Attackers register those names to deliver malware. Here is how to detect, prevent, and respond to hallucinated dependency attacks.
Includes: concise overview, exploit path, and remediation checklist for AI-assisted teams.
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