Blog · Research · Updated 2026-08-20

Vibe coding security statistics 2026

The numbers that actually describe how AI-generated apps perform on security — sourced, explained, and updated quarterly as new data comes in.

This page is refreshed each quarter as new figures and disclosures emerge. Last reviewed 2026-08-20.

98%

of scanned AI-generated apps had at least one security flaw

Security researchers who scanned over a thousand apps built with tools like Cursor, Bolt, Lovable, and v0 found this in the vast majority of them — not rare edge cases, but the typical outcome of a fast AI-assisted build with no dedicated security pass.

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45%

of AI-generated backends ship an open CORS misconfiguration

Wildcard or reflected-origin CORS is one of the single most common defaults AI coding assistants produce, because it is what makes a demo work immediately without knowing your real list of frontend domains.

Read the CORS breakdown
2.74x

more security flaws in AI-generated code than equivalent human-written code

This comparison shows up consistently across independent code-security research comparing AI-assisted and manually written codebases performing the same task — the gap isn't about AI writing broken code, it's about AI optimizing for working code, and security being a separate, easily skipped step.

~24,000

Android apps found exposing user data through Firebase misconfigurations

A recurring finding across large-scale audits of Firebase-backed mobile apps — nearly always the same root cause: permissive or default-open database security rules, not the public API key itself.

Read the Firebase breakdown
56

AI-related CVEs disclosed in Q1 2026 alone

The volume of documented, disclosed vulnerabilities specifically tied to AI coding tools and AI-generated code accelerated sharply into 2026 — evidence this is a growing category, not a one-time story.

1.5M

API tokens exposed in the Moltbook breach (January 2026)

One of the clearest large-scale examples of what "vibe-coded and shipped without a security review" costs in practice — a widely covered incident where misconfigured, AI-generated infrastructure led to over a million exposed tokens.

45–75

out of 100 — the typical first-scan security score range for AI-built apps

StackSecured's own scan data across the vibe-coding apps we've tested shows most first-time scans land in this range, not because the apps are badly built, but because security hardening is a deliberate step most fast AI-assisted builds skip entirely.

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Where does your app actually land?

Run a free scan and get your real score instead of guessing which end of the 45–75 range you're on.

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Common questions

Are these StackSecured's own numbers?

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Only the 45–75 first-scan score range is from StackSecured's own scan data. The rest are figures reported across independent security research, audits, and disclosed incidents in the AI-generated-code ecosystem — we've cited what each one actually measures rather than presenting them as our own findings.

Why do AI coding tools produce so many more security issues than human developers?

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Not because the underlying code is worse at doing what it's asked — it's because AI coding assistants optimize for a working feature in the fewest steps, and security controls (RLS policies, CORS allowlists, token expiry, rate limits) are almost always an extra, deliberate step beyond 'it works.' Nothing in a typical prompt-to-code loop forces that step to happen.

Does this mean AI-assisted development is unsafe to use?

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No — it means the output needs the same security review any fast-shipped code would need, and currently usually doesn't get one. The fix isn't avoiding AI coding tools, it's adding a scanning or review step before launch that specifically checks for the failure patterns these tools repeat.

More reading: CORS misconfiguration · Firebase security rules · JWT & session security · Exposed source maps · All guides