12 papers
How Do LLM Agents Actually Get the Flag? Trace-Level Provenance for Agentic Offensive Security Evaluation
Kimberly Milner, Minghao Shao, Nanda Rani +8
Capture-the-Flag (CTF) benchmarks are widely used to assess the offensive security capabilities of autonomous language-model agents. Evaluations rely on shallow binary judgments or…
AI In Cybersecurity Education -- Scalable Agentic CTF Design Principles and Educational Outcomes
Haoran Xi, Minghao Shao, Kimberly Milner +11
Large language models are rapidly changing how learners acquire and demonstrate cybersecurity skills. However, when human--AI collaboration is allowed, educators still lack validat…
Safeguarding LLMs Against Misuse and AI-Driven Malware Using Steganographic Canaries
Md Raz, Venkata Sai Charan Putrevu, Meet Udeshi +3
AI-powered malware increasingly exploits cloud-hosted generative-AI services and large language models (LLMs) as analysis engines for reconnaissance and code generation. Simultaneo…
CTFExplorer: Evaluating LLM Offensive Agents Through Multi-Target Web CTF Benchmarking
Nanda Rani, Kimberly Milner, Minghao Shao +9
Existing benchmarks for LLM-based offensive security agents use isolated, single-target setups with a known vulnerable service and fixed objective. They measure exploitation effect…
Binary Diff Summarization using Large Language Models
Meet Udeshi, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy +4
Security of software supply chains is necessary to ensure that software updates do not contain maliciously injected code or introduce vulnerabilities that may compromise the integr…
SaMOSA: Sandbox for Malware Orchestration and Side-Channel Analysis
Meet Udeshi, Venkata Sai Charan Putrevu, Prashanth Krishnamurthy +2
Cyber-attacks on operational technology (OT) and cyber-physical systems (CPS) have increased tremendously in recent years with the proliferation of malware targeting Linux-based em…