What 434 AI-Generated Vulnerabilities Reveal About Secure Software Development

New research finds that modern AI coding models frequently generate insecure code that exposes AI-generated applications to denial-of-service attacks, hardcoded secrets and authorization failures. The rapid adoption of AI coding assistants has transformed software development, enabling developers to generate production-ready applications in minutes rather than days. But as organizations increasingly rely on AI-generated code, a new question has emerged: what kinds of security flaws are these systems introducing? A new study from our research team at Xint.io analyzed 28 AI-coded applications spanning multiple development workflows, AI models and programming environments to identify which vulnerability classes appear most frequently—and how those vulnerabilities change as applications become more complex. After validating findings through source-code verification and runtime testing, researchers identified 434 verified…