12 papers
Poster: Rethinking Security in LLM Code Generation through Real-World Risk Scenarios
Lixun Ma, Ruolong Ma, Bei Wang +4
Large Language Models (LLMs) are widely used for code generation, yet their security behavior in realistic development workflows remains underexplored. Existing benchmarks often re…
Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning
Xingzhi Qian, Xinran Zheng, Yiling He +1
Recent LLM-based systems have shown promising capabilities for security-focused code analysis. Malware understanding, however, poses a distinct challenge: analysts must reconstruct…
Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries
Xinran Zheng, Alfredo Pesoli, Marco Valleri +2
Frontier LLM agents are increasingly capable of localizing suspicious code, but vulnerability reasoning requires more than access to program artifacts. An agent must carry forward…
Antaeus: Hunting Repository-Level Logic Vulnerabilities via Context-Grounded LLM Reasoning
Michele Armillotta, Nicolò Romandini, Rebecca Montanari +1
LLM-based vulnerability detectors have shown promising results in identifying memory-safety bugs and vulnerability classes whose violations can often be expressed through establish…
TIF: Learning Temporal Invariance in Android Malware Detectors
Xinran Zheng, Shuo Yang, Edith C. H. Ngai +2
Learning-based Android malware detectors degrade over time due to natural distribution drift caused by malware variants and new families. This paper systematically investigates the…
Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput
Alfredo Pesoli, Herman Errico, Lorenzo Cavallaro
Recent demonstrations of large language models producing candidate and confirmed vulnerabilities in production software have renewed the narrative that AI will reshape offensive an…