<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Pii on Miguel Lameiro | Cybersecurity Blog &amp; Security Writeups</title><link>https://blog.lameiro0x.com/tags/pii/</link><description>Recent content in Pii on Miguel Lameiro | Cybersecurity Blog &amp; Security Writeups</description><generator>Hugo -- 0.161.1</generator><language>en-us</language><lastBuildDate>Tue, 12 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.lameiro0x.com/tags/pii/index.xml" rel="self" type="application/rss+xml"/><item><title>Practical LLM Guardrails: Hallucination, Topic, PII, and Competitor Controls</title><link>https://blog.lameiro0x.com/notes/ai-security/practical-llm-guardrails-hallucination-topic-pii-competitor-controls/</link><pubDate>Tue, 12 May 2026 00:00:00 +0000</pubDate><guid>https://blog.lameiro0x.com/notes/ai-security/practical-llm-guardrails-hallucination-topic-pii-competitor-controls/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;The guardrails course becomes most useful when it moves from a simple keyword detector to specialized validators. The material covers four practical controls:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;hallucination detection with Natural Language Inference,&lt;/li&gt;
&lt;li&gt;topic restriction with zero-shot classification,&lt;/li&gt;
&lt;li&gt;PII detection with Microsoft Presidio,&lt;/li&gt;
&lt;li&gt;competitor mention detection with exact matching, NER, and vector similarity.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Each control protects a different failure mode. Together they show the right engineering pattern: use small, task-specific models and validators around the LLM instead of expecting the LLM to police itself.&lt;/p&gt;</description></item></channel></rss>