<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Zk-Snark on CuraSec</title><link>https://curasec.metacog.co.kr/tags/zk-snark/</link><description>Recent content in Zk-Snark on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 31 Aug 2026 19:07:02 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/zk-snark/index.xml" rel="self" type="application/rss+xml"/><item><title>zk-SNARK Adversarial Probes Detect Post-Deployment LLM Tampering</title><link>https://curasec.metacog.co.kr/insights/2026-08-31-not-to-break-but-to-attest-adversarial-probes-for-privacy-pr/</link><pubDate>Mon, 31 Aug 2026 19:07:02 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-08-31-not-to-break-but-to-attest-adversarial-probes-for-privacy-pr/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Academic framework for detecting model drift after deployment using privacy-preserving proofs; no running systems to patch today, but the black-box token-probe approach is worth tracking as LLM supply-chain integrity tooling matures.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Offers a governance-relevant framing: proprietary LLMs can be silently altered post-approval, and cryptographic audit frameworks are emerging to address that gap — useful context for AI risk discussions with the board or auditors.&lt;/li>
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