Abstract
This Undergraduate Thesis Portfolio brings together two complementary projects that reflect my identity as both a computer scientist and artist. The first is a technical Capstone Project detailing my application security internship at GuidePoint Security, where I designed and deployed BurpFlow, a Burp Suite extension that streamlines the workflow of application security consultants. The second is an STS research paper examining how generative AI and artistic communities negotiate the ethical boundaries of creativity, authorship, and intellectual property. Together, these projects explore technology’s dual nature as a practical tool that solves real engineering problems, and as a societal force that reshapes values, labor, and creative ownership. While one project is rooted in applied technical work and the other in sociocultural inquiry, both are rooted in the belief that meaningful technological progress requires understanding the communities they touch.
During application security assessments, consultants generate thousands of HTTP requests and responses, making it difficult to map the traffic back to the business logic flows of a web application when revisiting a project. To address this workflow inefficiency, I developed BurpFlow, a Burp Suite extension built using the Montoya API and Java Swing that enables consultants to organize proxy traffic according to web application business logic. By shadowing senior application security consultants during live assessments at GuidePoint Security, I identified critical pain points in how teams navigate complex project histories and designed a solution that allows users to highlight and categorize HTTP request and response flows directly within Burp Suite’s Proxy interface, then visualize these organized flows through a custom interface. The extension was successfully deployed to GuidePoint’s application security team, improving context retention across assessment sessions and reducing the time consultants spend reconstructing prior work. The Capstone report also documents my broader professional development as an application security consultant, reflecting on the skills and perspectives I gained through hands-on engagement with the field. Future work includes maintaining compatibility with Burp Suite updates, implementing optional highlighting features, and expanding the Montoya API integration to support persistence of additional data types.
My STS research paper investigates the sociotechnical tensions between AI developers and artistic communities as generative image models have become increasingly capable of imitating art styles of human creators. The central argument of the paper is that the conflict between artistic plagiarism and technological innovation is not simply a disagreement about copyright law or technical capability, but a deeper struggle over whose labor, values, and creative norms will shape how transformative technology develops. Drawing on Rogers’ Diffusion of Innovation framework, the paper reframes artists who resist AI image generation not as laggards resistant to change, but as rational actors protecting their economic and expressive interests in the face of technology built without their input and deployed at their expense. The paper further argues that artists and engineers are coproducing new and contested understandings of authorship, consent, and creative ownership in real time. Crucially, the analysis proposes the principal beneficiaries of AI image generation are not artists or individual engineers, but corporations, and any meaningful resolution to this tension will require redistributing power rather than pursuing purely technical compromises. The paper concludes by offering frameworks for consent-based model training and greater collaboration between artistic and engineering communities as pathways toward more equitable AI development.
