<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Learning on Wirez</title><link>https://wirez.top/tags/learning/</link><description>Recent content in Learning on Wirez</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://wirez.top/tags/learning/index.xml" rel="self" type="application/rss+xml"/><item><title>Machine learning misses real BGP security flaws</title><link>https://wirez.top/posts/machine-learning-misses-real-bgp-security-flaws/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://wirez.top/posts/machine-learning-misses-real-bgp-security-flaws/</guid><description>&lt;meta charset="utf-8">
&lt;!-- wp:paragraph {"className":"std-text"} -->
&lt;!-- /wp:paragraph -->
&lt;!-- wp:paragraph {"className":"std-text"} -->
&lt;p class="std-text">Tom Beecher rejected the &lt;a href="https://datatracker.ietf.org/doc/html/rfc4271" target="_blank" rel="noopener noreferrer">BGP&lt;/a> Security Intelligence Platform immediately after reading claims that &lt;strong>as_path length&lt;/strong> dictates routing credibility. This skepticism highlights a critical flaw in current predictive modeling: relying on outdated heuristics rather than verifiable propagation data. The article argues that effective &lt;strong>risk assessment&lt;/strong> demands discarding static path assumptions in favor of dynamic, origin-side vulnerability scoring combined with real-time structural analysis.&lt;/p></description></item></channel></rss>