You already know AI writes more bugs than it should. What you don't know yet is exactly which flaws to look for and why AI keeps making the same mistakes, codebase after codebase.
Your team is shipping AI-generated code faster than any human review process can keep up with. That gap is where vulnerabilities live.
Xint's autonomous source-code pentesting technology analyzed 28 codebases across three real-world scenarios: "Vibe coded" apps, enterprise-supervised AI code, and AI-hardened legacy code.
Testing spanned coding agents from the top two frontier labs, Anthropic and OpenAI, across multiple languages and application sizes — giving us a genuinely representative view of how AI code fails, regardless of vendor or model.