<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Attack-Graphs on CuraSec</title><link>https://curasec.metacog.co.kr/tags/attack-graphs/</link><description>Recent content in Attack-Graphs on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 27 Jul 2026 15:10:27 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/attack-graphs/index.xml" rel="self" type="application/rss+xml"/><item><title>Graph Optimisation and AI Models for Active Directory Hardening</title><link>https://curasec.metacog.co.kr/insights/2026-07-27-practical-graph-optimisation-and-ai-driven-models-for-active/</link><pubDate>Mon, 27 Jul 2026 15:10:27 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-07-27-practical-graph-optimisation-and-ai-driven-models-for-active/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Academic thesis proposing game-theoretic models for AD attack-path hardening, including dynamic graph defense and honeypot placement. No patch or configuration change needed today, but the prioritization framework could inform future AD remediation planning.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Learn:&lt;/strong> The decoy/honeypot placement model—designed to maximize worst-case incident response time in dynamic AD environments—is worth reading for analysts building deception layers, though no actionable detection content or IOCs are included.&lt;/li>
&lt;li>&lt;strong>Leader — Skip&lt;/strong>&lt;/li>
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