<?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>Projects on Kyler Nats | Cybersecurity Portfolio</title><link>https://kylernats.github.io/personal-blog/projects/</link><description>Recent content in Projects on Kyler Nats | Cybersecurity Portfolio</description><generator>Hugo -- 0.159.1</generator><language>en-us</language><atom:link href="https://kylernats.github.io/personal-blog/projects/index.xml" rel="self" type="application/rss+xml"/><item><title>Automated AWS Infrastructure with Terraform</title><link>https://kylernats.github.io/personal-blog/projects/aws-terraform-infra/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://kylernats.github.io/personal-blog/projects/aws-terraform-infra/</guid><description>&lt;hr&gt;
&lt;p&gt;Learning how to replace manual cloud configuration with a secure, immutable Infrastructure-as-Code (IaC) pipeline to deploy hardened AWS environments.&lt;/p&gt;
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&lt;h2 id="project-impact--core-functionality"&gt;Project Impact &amp;amp; Core Functionality&lt;/h2&gt;
&lt;p&gt;This project transitioned a manual workflow into a repeatable, version-controlled architecture, ensuring that every security group rule and subnet association is documented as code. By architecting a custom Virtual Private Cloud (VPC), I established a baseline for secure cloud operations that eliminates the risks of manual misconfiguration. The result is a functional, hardened web server environment that serves as the scalable foundation for future security labs.&lt;/p&gt;</description></item><item><title>My Portfolio Infrastructure</title><link>https://kylernats.github.io/personal-blog/projects/portfolio-infrastructure/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://kylernats.github.io/personal-blog/projects/portfolio-infrastructure/</guid><description>&lt;hr&gt;
&lt;p&gt;How I built a containerized, high-performance portfolio using Hugo and Docker to ensure consistent deployments and secure web hosting.&lt;/p&gt;
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&lt;h2 id="project-impact--core-functionality"&gt;Project Impact &amp;amp; Core Functionality&lt;/h2&gt;
&lt;p&gt;This project moved beyond simple web design to focus on the infrastructure required to host a professional cybersecurity brand. By using Docker, I created an isolated environment that ensures the site runs identically on my local machine and the production server, eliminating &amp;ldquo;it works on my machine&amp;rdquo; errors. The final architecture serves as a low-latency, secure platform to showcase my technical labs and research.&lt;/p&gt;</description></item><item><title>Offensive Security &amp; Pentesting Lab</title><link>https://kylernats.github.io/personal-blog/projects/offensive-security-lab/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://kylernats.github.io/personal-blog/projects/offensive-security-lab/</guid><description>&lt;hr&gt;
&lt;p&gt;A segregated virtual lab used to simulate the end-to-end lifecycle of a cyberattack to identify and mitigate defensive gaps.&lt;/p&gt;
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&lt;h2 id="project-impact--core-functionality"&gt;Project Impact &amp;amp; Core Functionality&lt;/h2&gt;
&lt;p&gt;This lab environment allowed for the safe execution of offensive security tactics against a hardened Linux target, bridging the gap between theoretical knowledge and technical application. By utilizing a Kali Linux attack vector, I successfully mapped the target&amp;rsquo;s attack surface and executed a series of exploits to gain unauthorized access. The project concludes with a full post-exploitation analysis, demonstrating how weak service configurations and poor credential management lead to total system compromise.&lt;/p&gt;</description></item><item><title>Scalable RAG Chatbot Architecture</title><link>https://kylernats.github.io/personal-blog/projects/rag-chatbot-architecture/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://kylernats.github.io/personal-blog/projects/rag-chatbot-architecture/</guid><description>&lt;hr&gt;
&lt;p&gt;I built a high-performance Retrieval-Augmented Generation (RAG) pipeline designed to securely query massive datasets using vector embeddings and cloud-native architecture.&lt;/p&gt;
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&lt;h2 id="project-impact--core-functionality"&gt;Project Impact &amp;amp; Core Functionality&lt;/h2&gt;
&lt;p&gt;This project engineered a scalable solution for AI-driven data retrieval, allowing a chatbot to provide accurate, source-backed answers from a sprawling Amazon product dataset. By moving away from local file processing and implementing a DuckDB streaming architecture, I ensured the system could handle enterprise-scale data without crashing under memory constraints. The final architecture is fully isolated within a VPC, ensuring that sensitive data remains invisible to the public internet while remaining highly accessible to the internal API.&lt;/p&gt;</description></item></channel></rss>