<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Secure AI on carney.wiki</title><link>https://carney.wiki/tags/secure-ai/</link><description>Recent content in Secure AI on carney.wiki</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Thu, 02 Oct 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://carney.wiki/tags/secure-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>Why Most AI Security Failures Start With Data</title><link>https://carney.wiki/blog/why-most-ai-security-failures-start-with-data/</link><pubDate>Thu, 02 Oct 2025 00:00:00 +0000</pubDate><guid>https://carney.wiki/blog/why-most-ai-security-failures-start-with-data/</guid><description>Most AI security failures do not start with the model.
They start with the data.
That is not as exciting as a story about a rogue algorithm or a clever jailbreak, but it is usually closer to the truth.
If the data feeding an AI system is unclassified, unverified, poorly governed, over-permissioned, or impossible to trace, the model inherits the problem. Then it scales it.
AI does not make weak data practices disappear.</description></item></channel></rss>