<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DevSecOps on The Coders Blog</title><link>https://thecodersblog.com/tag/devsecops/</link><description>Recent content in DevSecOps on The Coders Blog</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 11 May 2026 17:31:00 +0000</lastBuildDate><atom:link href="https://thecodersblog.com/tag/devsecops/index.xml" rel="self" type="application/rss+xml"/><item><title>Beyond the Patch: Rethinking Application Security in the Age of AI</title><link>https://thecodersblog.com/the-patching-treadmill-for-application-security-2026/</link><pubDate>Mon, 11 May 2026 17:31:00 +0000</pubDate><guid>https://thecodersblog.com/the-patching-treadmill-for-application-security-2026/</guid><description>&lt;h2 id="when-patched-means-already-compromised-the-illusion-of-the-quarterly-scan"&gt;When &amp;ldquo;Patched&amp;rdquo; Means &amp;ldquo;Already Compromised&amp;rdquo;: The Illusion of the Quarterly Scan&lt;/h2&gt;
&lt;p&gt;Imagine this: your team deploys a new feature, a carefully crafted piece of code, to production on a Tuesday. By Thursday, a sophisticated attacker, leveraging an exploit discovered mere hours before, has gained a foothold. Your quarterly penetration test, scheduled for next month, will likely miss this novel vulnerability entirely. Even if it surfaced in your logs, your team is drowning in a backlog of 45.4% of enterprise vulnerabilities that remain unpatched after a year, 17.4% of which are high or critical. This isn&amp;rsquo;t a hypothetical horror story; it&amp;rsquo;s the stark reality of the &amp;ldquo;patching treadmill&amp;rdquo; in today&amp;rsquo;s hyper-accelerated development and AI-assisted coding landscape. The traditional &amp;ldquo;find-and-fix&amp;rdquo; model, once the bedrock of application security, has become a Sisyphean task, exacerbated by continuous deployment cycles that push code out faster than security teams can realistically assess and patch it. The rise of AI-generated code, while promising efficiency, introduces a new vector of complexity and potential vulnerabilities at an unprecedented scale. We&amp;rsquo;re not just patching vulnerabilities; we&amp;rsquo;re perpetually chasing shadows, and often, the race is already lost before it begins.&lt;/p&gt;</description></item></channel></rss>