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Agentic Security
Building and evaluating autonomous agents for realistic, long-horizon security engineering workflows.
Research Ledger · 2026
Hwiwon Lee
PhD Student in Computer Science · UIUC
I build and evaluate AI agents for cybersecurity.
01 / Inquiry
Research focus
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Software Systems
Designing reproducible systems that connect models, program analysis, and dynamic execution evidence.
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Applied Vulnerability Research
Discovering and validating vulnerabilities in production software, from services to operating-system kernels.
02 / Notes
Recent news
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SEC-bench Pro, our benchmark for long-horizon software security tasks, is now available on arXiv.
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Agentic Vulnerability Reasoning on COTS Binaries is now available on arXiv.
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Recognized as a Microsoft Most Valuable Security Researcher for 2026 Q1.
03 / Record
Selected publications
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SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks?
A benchmark of 344 validated vulnerabilities across browser engines and the Linux kernel, designed to measure realistic agent bug hunting.
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Agentic Vulnerability Reasoning on COTS Binaries
An end-to-end study of autonomous vulnerability discovery and debugger-verified validation on commercial Windows binaries.
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SEC-bench: Automated Benchmarking of LLM Agents on Real-World Software Security Tasks
A fully automated framework for constructing and evaluating authentic proof-of-concept generation and vulnerability patching tasks.
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BENZENE: A Practical Root Cause Analysis System with an Under-Constrained State Mutation
A practical, automated crash-diagnosis system that uses under-constrained state mutation to rank root causes efficiently.