Wenbo Guo

The paper introduces SynthChain, a comprehensive, multi-source synthetic testbed and dataset that demonstrates that detecting advanced software supply chain attacks requires fusing evidence from multiple, disparate telemetry sources.

SAILOR automates the construction of symbolic execution harnesses by combining static analysis and LLM-based synthesis, significantly improving the scalability and effectiveness of vulnerability discovery in large codebases.

The paper introduces ExploitGym, a large-scale benchmark, demonstrating that advanced AI agents can successfully turn theoretical software vulnerabilities into working exploits, highlighting growing cybersecurity risks.

MalwarePT introduces a novel binary-level foundation model, pretrained on Windows PE code-section bytes using a ModernBERT-style encoder, demonstrating superior transfer learning capabilities across various malware analysis tasks.

The paper introduces CyberGym-E2E, a large-scale, end-to-end benchmark designed to comprehensively evaluate AI agents' capabilities across the entire lifecycle of real-world software vulnerability discovery, proof-of-concept generation, and patch creation.