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    <title>Waap on ShieldedBytes</title>
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      <title>The WAF Is Learning: How ML and Behavioral Analysis Are Reshaping Application Protection</title>
      <link>https://linuxeries.org/post/2026-10-31-the-waf-is-learning-ml-and-behavioral-analysis/</link>
      <pubDate>Sat, 31 Oct 2026 10:15:00 +0100</pubDate>
      <guid>https://linuxeries.org/post/2026-10-31-the-waf-is-learning-ml-and-behavioral-analysis/</guid>
      <description>&lt;p&gt;For years, a web application firewall was mostly a large list of known-bad patterns. It was useful, but brittle. A new attack vector slipped through until someone wrote a signature, and legitimate traffic that happened to look like an old attack got blocked. The usual fix was more rules, more tuning, and more full-time WAF administration.&lt;/p&gt;&#xA;&lt;p&gt;A different model is now in production at several major vendors. Instead of asking &lt;em&gt;&amp;ldquo;does this request match a known attack?&amp;rdquo;&lt;/em&gt;, these systems ask &lt;em&gt;&amp;ldquo;does this request look like it belongs here?&amp;rdquo;&lt;/em&gt; The answer comes from models that learn what normal traffic looks like for a specific application and flag deviations from that baseline.&lt;/p&gt;</description>
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