<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Adversarial-Ai on CuraSec</title><link>https://curasec.metacog.co.kr/tags/adversarial-ai/</link><description>Recent content in Adversarial-Ai on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 01 Sep 2026 15:28:52 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/adversarial-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>UAC-0099 embeds LLM-disrupting prompts in malware to blind AI analysis</title><link>https://curasec.metacog.co.kr/insights/2026-09-01-russia-aligned-uac-0099-plants-nuclear-weapon-prompt-in-malw/</link><pubDate>Tue, 01 Sep 2026 15:28:52 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-09-01-russia-aligned-uac-0099-plants-nuclear-weapon-prompt-in-malw/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> GuardBreaker shows that AI-assisted malware scanning can be manipulated at the artifact level; no patch or config change is needed today, but engineers building AI-augmented security pipelines should understand this evasion class.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Plan:&lt;/strong> Review any AI/LLM-assisted triage or malware-analysis workflows and add a mandatory human-review layer for suspected APT samples — do not treat LLM output as authoritative when analyzing artifacts from sophisticated actors.&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Adversaries are now actively engineering around AI-assisted defenses; file this as context for future AI-tool procurement and policy decisions around over-reliance on LLM-based analysis in SOC operations.&lt;/li>
&lt;/ul></description></item></channel></rss>