{"id":260,"date":"2026-05-10T23:57:21","date_gmt":"2026-05-10T23:57:21","guid":{"rendered":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/?page_id=260"},"modified":"2026-05-11T04:06:13","modified_gmt":"2026-05-11T04:06:13","slug":"work-samples","status":"publish","type":"page","link":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/leaders\/work-samples\/","title":{"rendered":"Work Samples"},"content":{"rendered":"\n<p><strong>AI Security Research \u2014 Behavioral Detection Methods for MCP Server Vulnerabilities<\/strong><br>This research paper was produced through the Commonwealth Cyber Initiative Coastal Virginia undergraduate research program at Old Dominion University. It addresses a growing security gap in artificial intelligence systems, specifically how to detect vulnerabilities in MCP servers, which are tools that allow AI systems to connect to and interact with external services. Rather than relying on traditional code scanning methods, my research proposed a behavioral detection framework that tests how these servers respond to the same request framed in different ways, exposing inconsistencies that signal security weaknesses. The findings were presented at the COVA CCI research showcase. This work demonstrates my ability to conduct independent research in an emerging area of cybersecurity, analyze complex technical problems, and communicate findings to a broader audience.<\/p>\n\n\n<a href=\"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-content\/uploads\/sites\/41236\/2026\/05\/Behavioral-Detection-Methods-for-Automated-MCP-Servers.pdf\" class=\"pdfemb-viewer\" style=\"\" data-width=\"max\" data-height=\"max\"  data-toolbar=\"bottom\" data-toolbar-fixed=\"off\">Behavioral-Detection-Methods-for-Automated-MCP-Servers<br\/><\/a>\n<p class=\"wp-block-pdfemb-pdf-embedder-viewer\"><\/p>\n\n\n\n<p><br><strong>NIST SP 800-53 Policy Analysis<\/strong><br>This paper was written as part of CYSE 425, a writing-intensive cybersecurity course at Old Dominion University. It analyzes NIST SP 800-53, one of the most widely used federal security frameworks, examining how its controls are applied in real-world environments and the policy decisions behind them. This work sample demonstrates my ability to research complex security frameworks, think critically about their real-world implications, and communicate technical policy concepts in a clear and structured way.<\/p>\n\n\n<a href=\"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-content\/uploads\/sites\/41236\/2026\/05\/Policy-Analysis-Paper-1-Christian-Coleman-1.pdf\" class=\"pdfemb-viewer\" style=\"\" data-width=\"max\" data-height=\"max\"  data-toolbar=\"bottom\" data-toolbar-fixed=\"off\">Policy-Analysis-Paper-1-Christian-Coleman-1<br\/><\/a>\n<p class=\"wp-block-pdfemb-pdf-embedder-viewer\"><\/p>\n\n\n\n<p><br><strong>IT Security Internship Reflection \u2014 CYSE 368<\/strong> <br>This paper was written at the conclusion of my IT Security internship at Old Dominion University&#8217;s Information Security office. It reflects my hands-on experience in security operations, including firewall management, phishing triage, incident response, and security documentation. It demonstrates my ability to apply classroom knowledge in a real professional environment, communicate technical concepts clearly, and grow under pressure. This experience directly shaped who I am as a security professional today.<\/p>\n\n\n<a href=\"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-content\/uploads\/sites\/41236\/2026\/05\/CYSE-368-Internship-Final-Paper-3.pdf\" class=\"pdfemb-viewer\" style=\"\" data-width=\"max\" data-height=\"max\"  data-toolbar=\"bottom\" data-toolbar-fixed=\"off\">CYSE-368-Internship-Final-Paper-3<br\/><\/a>\n<p class=\"wp-block-pdfemb-pdf-embedder-viewer\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI Security Research \u2014 Behavioral Detection Methods for MCP Server VulnerabilitiesThis research paper was produced through the Commonwealth Cyber Initiative Coastal Virginia undergraduate research program at Old Dominion University. It addresses a growing security gap in artificial intelligence systems, specifically how to detect vulnerabilities in MCP servers, which are tools that allow AI systems to&#8230; <\/p>\n<div class=\"link-more\"><a href=\"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/leaders\/work-samples\/\">Read More<\/a><\/div>\n","protected":false},"author":28579,"featured_media":0,"parent":256,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/pages\/260"}],"collection":[{"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/users\/28579"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/comments?post=260"}],"version-history":[{"count":4,"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/pages\/260\/revisions"}],"predecessor-version":[{"id":286,"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/pages\/260\/revisions\/286"}],"up":[{"embeddable":true,"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/pages\/256"}],"wp:attachment":[{"href":"https:\/\/sites.wp.odu.edu\/chriscoleleaders\/wp-json\/wp\/v2\/media?parent=260"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}