[2604.02360] Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations

Computer Science > Networking and Internet Architecture arXiv:2604.02360 (cs) [Submitted on 20 Mar 2026] Title:Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations Authors:Yonas Kassa, James Bonacci, Ping Wang View a PDF of the paper titled Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations, by Yonas Kassa and 2 other authors View PDF HTML (experimental) Abstract:The transformative potential of large language models (LLMs) in education, such as improving accessibility and personalized learning, is being eclipsed by significant challenges. These challenges stem from concerns that LLMs undermine academic assessment by enabling bypassing of critical thinking, leading to increased cognitive offloading. This emerging trend stresses the dual imperative of harnessing AI's educational benefits while safeguarding critical thinking and academic rigor in the evolving AI ecosystem. To this end, we introduce AI-Sinkhole, an AI-agent augmented DNS-based framework that dynamically discovers, semantically classifies, and temporarily network-wide blocks emerging LLM chatbot services during proctored exams. AI-Sinkhole offers explainable classification via quantized LLMs (LLama 3, DeepSeek-R1, Qwen-3) and dynamic DNS blocking with Pi-Hole. We also share our observations in using LLMs as explainable classifiers which achieved robust cross-lingual performance (F1-score > 0.83). To support future research a...