6 papers
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark
Jeremy Spence, Nicholas Assaderaghi, Jinhao Zhu +5
AI agents are rapidly improving in cybersecurity capabilities when the source code is available for analysis, yet much of the software most consequential to cybersecurity, includin…
OpenSage: Self-programming Agent Generation Engine
Hongwei Li, Zhun Wang, Qinrun Dai +11
Agent development kits (ADKs) provide effective platforms and tooling for constructing agents, and their designs are critical to the constructed agents' performance, especially the…
To Defend Against Cyber Attacks, We Must Teach AI Agents to Hack
Terry Yue Zhuo, Yangruibo Ding, Wenbo Guo +1
For over a decade, cybersecurity has relied on human labor scarcity to limit attackers to high-value targets manually or generic automated attacks at scale. Building sophisticated…
DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle
Yuheng Tang, Kaijie Zhu, Bonan Ruan +14
Even though demonstrating extraordinary capabilities in code generation and software issue resolving, AI agents' capabilities in the full software DevOps cycle are still unknown. D…
Co-PatcheR: Collaborative Software Patching with Component(s)-specific Small Reasoning Models
Yuheng Tang, Hongwei Li, Kaijie Zhu +3
Motivated by the success of general-purpose large language models (LLMs) in software patching, recent works started to train specialized patching models. Most works trained one mod…
Rethinking Kernel Program Repair: Benchmarking and Enhancing LLMs with RGym
Kareem Shehada, Yifan Wu, Wyatt D. Feng +4
Large Language Models (LLMs) have revolutionized automated program repair (APR) but current benchmarks like SWE-Bench predominantly focus on userspace applications and overlook the…