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The AI code vulnerabilities that grow with your app

Feeds2.Feedburner •Mirko Zorz • July 23, 2026

Theori built 28 apps with AI coding agents and scanned each one through its pentesting platform. Five models did the building, split between Anthropic and OpenAI, across apps written from a spec, thrown together from a casual prompt, and rewritten from an aging PHP codebase. The team went in expecting injection everywhere. SQL injection, cross-site scripting, the bugs that fill security tutorials. Those barely showed up. The models reached for prepared statements and ORMs on … More →

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This article is one source in a clustered incident — the cluster page carries the summary, timeline and every other outlet covering it.

AI Coding Models Generate Vulnerabilities in Software Development Recent research reveals that AI coding models, including those from Anthropic and OpenAI, frequently produce insecure code, leading to vulnerabilities such as denial-of-service attacks, hardcoded secrets, and authorization failures. The study involved scanning 28 applications built with AI coding agents, which showed unexpected resilience against traditional vulnerabilities like SQL injection. However, the findings indicate a significant risk as organizations increasingly rely on AI-generated code for rapid application development. The vulnerabilities identified could potentially expose numerous applications to exploitation if not addressed. Current security practices may need to adapt to the unique challenges posed by AI-generated code. 2 sources 52

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The AI code vulnerabilities that grow with your app

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Attack Types (2)

CWE Weaknesses (2)

Platforms (1)