<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Network-Policy on CuraSec</title><link>https://curasec.metacog.co.kr/tags/network-policy/</link><description>Recent content in Network-Policy on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 21 Sep 2026 18:11:48 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/network-policy/index.xml" rel="self" type="application/rss+xml"/><item><title>NetInspector: LLM false negatives in network security policy enforcement</title><link>https://curasec.metacog.co.kr/insights/2026-09-21-netinspector-measuring-and-improving-llm-capabilities-for-re/</link><pubDate>Mon, 21 Sep 2026 18:11:48 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-09-21-netinspector-measuring-and-improving-llm-capabilities-for-re/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Research finding that fine-tuned LLMs exhibit false negative rates when validating proposed network intents against security policy — a design-relevant caution for teams evaluating LLM-based network automation or IBN tooling.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Early evidence that LLM agents used for network policy automation can silently miss policy violations; useful context when evaluating AI-assisted infrastructure governance or setting guardrails for agentic tooling adoption.&lt;/li>
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