<?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>Giskard on Miguel Lameiro | Cybersecurity Blog &amp; Security Writeups</title><link>https://blog.lameiro0x.com/tags/giskard/</link><description>Recent content in Giskard on Miguel Lameiro | Cybersecurity Blog &amp; Security Writeups</description><generator>Hugo -- 0.161.1</generator><language>en-us</language><lastBuildDate>Fri, 08 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.lameiro0x.com/tags/giskard/index.xml" rel="self" type="application/rss+xml"/><item><title>Red Teaming LLM Applications: A Practical Assessment Workflow</title><link>https://blog.lameiro0x.com/notes/ai-security/red-teaming-llm-applications-practical-assessment-workflow/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://blog.lameiro0x.com/notes/ai-security/red-teaming-llm-applications-practical-assessment-workflow/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;Red teaming an LLM application is not the same thing as checking whether the base model passed a benchmark. The deployed application has prompts, retrieval, tools, business rules, memory, hidden context, and user workflows. Those layers create risks that do not exist in the foundation model alone.&lt;/p&gt;
&lt;p&gt;The course uses two demo applications: a banking assistant and an ebook store support bot. The useful pattern is not the specific brand names or prompts. The useful pattern is the assessment workflow: define scope, probe manually, automate repeatable checks, use scanners where they help, and connect successful attacks to real application impact.&lt;/p&gt;</description></item></channel></rss>