<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fingerprinting on CuraSec</title><link>https://curasec.metacog.co.kr/tags/fingerprinting/</link><description>Recent content in Fingerprinting on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 26 Oct 2026 18:39:19 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/fingerprinting/index.xml" rel="self" type="application/rss+xml"/><item><title>AgentTrace: Black-Box LLM Agent Fingerprinting via Execution Traces</title><link>https://curasec.metacog.co.kr/insights/2026-10-26-agenttrace-execution-level-fingerprinting-of-black-box-llm-a/</link><pubDate>Mon, 26 Oct 2026 18:39:19 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-10-26-agenttrace-execution-level-fingerprinting-of-black-box-llm-a/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Novel research showing that the foundation model behind an agent can be identified at 96% accuracy through probe-induced repair behaviors — engineers building or deploying AI agents should factor in that model identity is not concealable, which has implications for AI system design and operational security posture.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Skip&lt;/strong>&lt;/li>
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