● Covered by 1 source · 1 reportMedium impact
Security Flaws Found in Vibe-Coded Applications
Key points
- 434 exploitable security vulnerabilities identified in vibe-coded apps.
- Most common issues include rate limiting and resource exhaustion flaws.
- Insecure direct object reference flaws accounted for 88 security issues.
Rising Use of Vibe Coding
Vibe coding, where AI assists in code generation, is increasingly common in software development. According to Hostinger, about 90% of developers utilized at least one AI tool in their work by January 2026. This trend is driven by the imperative for faster and cheaper app development.
Security Analysis by Xint.io
Xint.io conducted an analysis of vibe-coded applications to assess the security vulnerabilities they introduce. They developed three testing frameworks to study apps created under different coding conditions, including those overseen by experienced developers and those from casual coders.
Findings on Exploitable Security Issues
The analysis uncovered a total of 434 exploitable security issues, with 196 in newly coded apps and 238 in a legacy app that was modernized through migration. The study highlighted the prevalence of security weaknesses in AI-assisted coding, providing insights into flaws introduced during the development process.
Common Vulnerabilities Identified
The report indicated that missing controls for rate limiting and denial-of-service (DOS) protections were the most frequent flaws, accounting for 93 cases of the total vulnerabilities. Authorization and insecure direct object reference flaws were the second most common, with 88 occurrences. These vulnerabilities pose risks beyond data theft, potentially resulting in increased server costs and operational disruptions.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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Reporting from
Xint.io identified 434 exploitable security issues in vibe-coded applications, revealing significant vulnerabilities. This highlights the need for better security practices and oversight in AI-assisted coding efforts as reliance on such technologies increases.