OWASP Top 10 for Vibe Coding: How AI-Generated Apps Get Pwned

OWASP Top 10 for Vibe Coding: How AI-Generated Apps Get Pwned

The OWASP Top 10 has been the canonical "what goes wrong in web applications" list for over twenty years. It is still useful in 2026 — but if you are shipping with AI coding tools like Lovable, Bolt, Replit, Cursor, or v0, you need to read it through a different lens.

These tools are extraordinary at generating working code. They are not, by default, generating secure code. The same prompt that gives you a full-stack app with auth, dashboards, and Stripe integration in a single afternoon will quietly ship most of the OWASP Top 10 along with it, unless you actively check.

This post walks the OWASP Top 10 from a vibe coder's perspective: what each category looks like in AI-generated apps, the specific patterns we see most often, and how to detect them before someone else does.

Important note: OWASP versions and category names evolve. We use the current Top 10 categorization as of 2026. The names matter less than the underlying classes of bug — they have been the same for decades.

A1 — Broken access control

This is the single most common class of vulnerability in vibe-coded apps, and it is not close.

The pattern looks like this:

• The frontend hides admin routes behind a "user.role === 'admin'" check.
• The backend forgets to do the same check.
• Anyone with a normal account can call admin endpoints directly.

AI coding tools are particularly good at hiding this. They generate beautiful UI with role-based rendering, but the backend Supabase RPC, Express route, or Next.js API handler often does not re-check authorization. We see this in Lovable apps, in Replit apps, in Cursor-generated code, and in v0-generated code — it is a category problem, not a tool problem.

What to do: every endpoint must independently verify (a) the user is authenticated and (b) the user is authorized for this specific resource. Row-Level Security (RLS) in Supabase only helps if it is actually enabled and tested.

A2 — Cryptographic failures

In AI-generated apps, cryptographic failures usually look like:

• Plaintext passwords in a database (rare, but it still happens with some tools).
• Tokens stored in localStorage instead of httpOnly cookies.
• Sensitive PII (email, phone, address) sent over plain HTTP in a webhook handler.
• API keys hardcoded in frontend code or committed to Git.

The last one is the most common single mistake: an AI coding tool helpfully writes const STRIPE_KEY = 'sk_live_...' directly in a React component because you mentioned Stripe in your prompt.

What to do: never put secret keys in client code. Use environment variables. If a key has been exposed, rotate it immediately — assume it has already been scraped.

A3 — Injection

Classic SQLi is rarer than it used to be because most AI tools default to ORMs (Prisma, Drizzle, Supabase client). It is not gone, though. We still see:

• Raw SQL string interpolation when the AI gets clever ("just use a raw query for performance").
• NoSQL injection in Mongo queries that pass user input straight into $where.
• LDAP, OS command, and XPath injection in any code that shells out.
• Prompt injection in apps that pipe user input into LLM calls (a 2026-specific case worth its own post).

What to do: parameterized queries everywhere, no exceptions. Treat any user-controlled string as hostile. For LLM-backed apps, treat user prompts as untrusted input even more carefully than form input.

A4 — Insecure design

This is the category that AI tools struggle with the most, because it is not about a single line of code — it is about whether the architecture has any security thinking at all.

Examples we see in vibe-coded apps:

• Multi-tenant SaaS with no tenant isolation at the database level.
• Password reset flows that do not invalidate the token after use.
• "Forgot password" reveals whether an email is registered.
• Account creation with no rate limiting, allowing enumeration and abuse.
• Direct object references in URLs (/invoice/4521) with no ownership check.

AI tools do not design — they translate prompts into code. If your prompt did not say "make sure tenant A cannot see tenant B's data," it almost certainly is not enforced.

What to do: before shipping, ask yourself "what is the worst thing a malicious authenticated user could do here?" and walk through the answers manually. A pentest — human or Sentinel-driven — surfaces these design flaws faster than code review.

A5 — Security misconfiguration

This is everything from default credentials still being shipped, to verbose error pages exposing stack traces, to permissive CORS policies (Access-Control-Allow-Origin: * with credentials), to debug endpoints left in production.

In vibe coding specifically, watch for:

• NODE_ENV=development in production deploys.
• Source maps shipped to the public.
• Default Supabase anon keys with no RLS, effectively making the database public.
• Permissive CORS that any malicious site can use to read your API responses.
• Open admin dashboards reachable without authentication because the frontend route was the only protection.

What to do: harden the deployment, not just the code. Headers, CORS, env vars, and source maps all matter. A DAST scanner like Vuln0x catches most of this in minutes.

A6 — Vulnerable and outdated components

AI tools love to pin to specific package versions, often pinning to versions with known CVEs because that is what showed up in their training data. We routinely see vibe-coded apps shipping with vulnerable versions of axios, lodash, next, express, image-processing libraries, and various Supabase or auth dependencies.

What to do: run npm audit (or your equivalent) regularly, integrate SCA into CI, and update dependencies on a schedule. Dependabot is free and effective.

A7 — Identification and authentication failures

Authentication is hard. AI tools tend to either:

• Use a managed provider (Clerk, Supabase Auth, Auth.js) — usually fine.
• Roll something custom — usually broken.

Custom auth in vibe-coded apps tends to have:

• No rate limiting on login.
• No protection against credential stuffing.
• Weak or no session expiry.
• Password reset tokens that do not expire.
• 2FA bolted on as a UI checkbox without backend enforcement.

What to do: prefer a managed auth provider. If you must roll your own, use a vetted library and test it. Account-takeover bugs are catastrophic and trivially scriptable.

A8 — Software and data integrity failures

This category covers things like deserialization vulnerabilities, untrusted CDN scripts, and unsigned or unverified updates. In vibe-coded apps, the most common failure is loading random CDN scripts (analytics, fonts, "useful" libraries) without subresource integrity hashes — a single CDN compromise lets an attacker run code in your app.

What to do: prefer first-party hosting for critical scripts. Use SRI hashes for any third-party CDN. Pin and audit your supply chain.

A9 — Security logging and monitoring failures

This is the category vibe coders skip entirely. The app has no logs, or logs go to stdout and disappear when the container restarts. There is no alerting on suspicious behavior — no spike in failed logins, no unusual data access, no reaction to a sudden flood of 500 errors.

What to do: even minimal logging is dramatically better than none. Send auth events, admin actions, and sensitive data access to a real log store. Wire alerts to Slack or email. You do not need a SIEM on day one — you need something.

A10 — Server-side request forgery (SSRF)

SSRF is when your server makes outbound HTTP requests based on user input — fetching a user-supplied avatar URL, a webhook URL, an "import from URL" feature. Without strict allowlisting, attackers point that fetch at internal IPs (169.254.169.254 for cloud metadata, localhost for internal services, RFC1918 addresses for your VPC).

In vibe-coded apps, anywhere the AI generated a "fetch this URL the user provided and do something with it" feature is a likely SSRF candidate.

What to do: validate the URL host against an explicit allowlist. Block private IP ranges. Disable HTTP redirects, or follow them with the same allowlist applied at every hop.

How Vuln0x maps to this list

Vuln0x is an AI-powered DAST platform with an autonomous AI pentest agent (Sentinel). Most of the OWASP Top 10 is exactly what a competent DAST + pentest run is designed to find:

| OWASP category | Detection approach |
| --- | --- |
| Broken access control | Sentinel walks your app like an authenticated user, then tries authorized and unauthorized requests across roles |
| Cryptographic failures | Header checks, TLS configuration, secret-leak scanning |
| Injection | DAST payload coverage across SQL, NoSQL, OS command, header injection |
| Insecure design | Sentinel's 7-phase methodology surfaces logic flaws via exploitation pivots |
| Security misconfiguration | Header checks, CORS analysis, debug endpoint detection |
| Vulnerable components | Fingerprinting of frameworks and libraries with known CVEs |
| Authentication failures | Brute-force, password reset, session management testing |
| Integrity failures | SRI checks, mixed content detection |
| Logging failures | Surfaced via reporting that flags absence of expected security headers |
| SSRF | Active probing of fetch-from-URL features |

Sign up at vuln0x.com, get 20 free scan credits, and run a real OWASP-aligned scan on your vibe-coded app.

TL;DR

The OWASP Top 10 has not gone away — it just moved into the era of AI-generated code, where every category is now ten times easier to ship by accident. Read it as a checklist for what not to assume your AI coding tool got right, and verify with a scanner before someone else does.