<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Threat-Detection on CuraSec</title><link>https://curasec.metacog.co.kr/tags/threat-detection/</link><description>Recent content in Threat-Detection on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 21 Aug 2026 11:38:25 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/threat-detection/index.xml" rel="self" type="application/rss+xml"/><item><title>MS Graph PowerShell: querying Entra risky login detections</title><link>https://curasec.metacog.co.kr/insights/2026-08-21-using-microsoft-graph-and-powershell-risk-detection-commands/</link><pubDate>Fri, 21 Aug 2026 11:38:25 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-08-21-using-microsoft-graph-and-powershell-risk-detection-commands/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Practical walkthrough on using MS Graph and PowerShell to surface Entra ID risk detections — useful reference if you&amp;rsquo;re building automated triage or identity monitoring pipelines.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Plan:&lt;/strong> Walk through the MS Graph risk-detection commands shown here and consider incorporating them into your Entra ID hunting runbooks or SIEM enrichment workflows.&lt;/li>
&lt;li>&lt;strong>Leader — Skip&lt;/strong>&lt;/li>
&lt;/ul></description></item><item><title>Benchmark inconsistencies skew lateral movement detection research</title><link>https://curasec.metacog.co.kr/insights/2026-08-03-on-fair-and-realistic-performance-evaluations-for-graph-base/</link><pubDate>Mon, 03 Aug 2026 15:12:30 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-08-03-on-fair-and-realistic-performance-evaluations-for-graph-base/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>SOC/IR — Learn:&lt;/strong> Research shows that widely-cited lateral movement detectors perform significantly differently under standardized evaluation conditions, suggesting published accuracy claims may be overstated; useful context when selecting or tuning graph-based detection tools.&lt;/li>
&lt;li>&lt;strong>Leader — Skip&lt;/strong>&lt;/li>
&lt;/ul></description></item><item><title>Why Modern SOCs Need Multi-Layered Detections</title><link>https://curasec.metacog.co.kr/insights/2026-07-22-why-modern-socs-need-multi-layered-detections/</link><pubDate>Wed, 22 Jul 2026 12:46:13 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-07-22-why-modern-socs-need-multi-layered-detections/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>SOC/IR — Learn:&lt;/strong> High-level argument that malware-free attacks now dominate (~79% per CrowdStrike data) reinforces the case for behavioral and identity-based detection layers alongside EDR; no specific TTPs or tooling to act on immediately.&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> The framing that AI-equipped attackers are outpacing traditional defenses is useful context for board-level discussions about detection investment, but the piece offers no new data beyond vendor-cited statistics.&lt;/li>
&lt;/ul></description></item></channel></rss>