FinishKitAI Code Security: The 2026 Playbook
AI-built apps share a predictable set of security failures. This is the playbook for finding them in your own repo and fixing them before an attacker or a journalist finds them first.
Why AI-built apps fail security
AI coding tools generate the happy path confidently. They wire up auth, they scaffold routes, they connect a database. What they do not do by default:
- 01Verify the logged-in user owns the row they are requesting
- 02Enable row level security in the database
- 03Rate-limit authentication and OTP endpoints
- 04Separate server secrets from client-exposed variables
- 05Validate input against schemas instead of trusting request bodies
The result is a wave of shipped apps with the same handful of vulnerability classes. Data from scanning 100 vibe-coded apps confirms the pattern.
The core vulnerability classes
Learn these terms. Every serious AI-built app security incident in 2025 and 2026 maps to one of them.
Auth Bypass
A vulnerability class where a user can reach, read, or modify resources they should not have access to, usually because the app checks authentication (who you are) but not authorization (what you can do).
Environment Variable
A named value set outside your code (at build time or runtime) used to configure your app without hardcoding secrets or per-environment settings.
IDOR
Insecure Direct Object Reference, a class of vulnerability where changing a resource id in a URL or request gives access to someone else's data.
Prompt Injection
A class of attack on LLM-powered features where adversarial input to the model causes it to ignore developer instructions and behave maliciously.
Rate Limiting
Restricting how often a single user or IP can call an API endpoint, to prevent abuse, protect downstream systems, and control cost.
Row Level Security
A database feature that restricts which rows a user can read or modify based on per-row policies, enforced by the database itself rather than application code.
Secret Exposure
Any case where a sensitive credential (API key, database password, private key) is visible somewhere it should not be, such as client bundles, git history, or server logs.
By tool
Each AI coding tool has its own set of default behaviors that tend to produce specific security gaps. Pick your tool to see the patterns we typically find.
Lovable security
Prompt to full-stack app, Supabase built in.
Cursor security
AI-first code editor built on VS Code.
Replit security
Cloud IDE with Agent that builds and deploys apps.
Bolt security
In-browser full-stack app builder by StackBlitz.
v0 security
Vercel AI UI generator for React and Next.js.
Windsurf security
Agentic IDE from Codeium with Cascade.
Claude Code security
Anthropic's terminal-native coding agent.
GitHub Copilot security
AI pair programmer built into GitHub and every IDE.
Devin security
Cognition's autonomous software engineer.
Aider security
Open-source AI pair programmer in the terminal.
Cline security
Open-source autonomous coding agent for VS Code.
Zed security
High-performance collaborative editor with AI.
Roo Code security
Autonomous AI coding agent for VS Code.
Codex security
OpenAI's cloud software engineering agent.
Base44 security
Prompt-to-app builder for internal tools and MVPs.
Rork security
AI-first mobile app builder using React Native.
Softgen security
AI software architect for end-to-end web apps.
Databutton security
AI-first builder for data apps and internal tools.
Find your security gaps
FinishKit runs the same checks a penetration tester would, on every AI-built app, in about two minutes.
Run a security scan