<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Authentication on No Semicolons</title><link>https://nosemicolons.com/tags/authentication/</link><description>Recent content in Authentication on No Semicolons</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 14 Aug 2026 09:00:00 +0000</lastBuildDate><atom:link href="https://nosemicolons.com/tags/authentication/index.xml" rel="self" type="application/rss+xml"/><item><title>The AI Code Generation Authentication Crisis: How Generated Login Systems Expose 90% of Apps to Security Breaches</title><link>https://nosemicolons.com/posts/ai-code-generation-authentication-security-crisis/</link><pubDate>Fri, 14 Aug 2026 09:00:00 +0000</pubDate><guid>https://nosemicolons.com/posts/ai-code-generation-authentication-security-crisis/</guid><description>&lt;p>Ever asked Claude or ChatGPT to &amp;ldquo;build me a login system&amp;rdquo; and gotten back what looks like perfectly reasonable authentication code? I hate to break it to you, but there&amp;rsquo;s a good chance that shiny new login flow is riddled with security holes that could expose your entire application.&lt;/p>
&lt;p>After reviewing hundreds of AI-generated authentication implementations across different models and prompts, I&amp;rsquo;ve found a disturbing pattern: roughly 90% of AI-generated login systems contain at least one critical security vulnerability. The scary part? Most of these flaws aren&amp;rsquo;t obvious at first glance.&lt;/p></description></item></channel></rss>