collaborators

8 papers

cs.CR2026

BenchShield: Formal Model-Backed Instrumentation for Reward Integrity in LLM-Agent Evaluation Infrastructure

Shenghan Zheng, Zonglin Di, Yimin Liu +19

LM-agent benchmarks increasingly function as interactive evaluation infrastructure. Agents observe state, call tools, modify workspaces, submit artifacts, and receive rewards from…

cs.CR2026

MalTotal: Cost-Effective and Language-Agnostic Malicious Code Poisoning Detection for Millions of Repositories

Jian Zhao, Shenao Wang, Qingyang Wu +3

The widespread adoption of open source software (OSS) has introduced significant security risks, with malicious code poisoning attacks increasingly targeting public package registr…

cs.SE2026

Neuro-Symbolic Reasoning for Vulnerability Detection

Yanjie Zhao, Hongjie Chen, Li Lu +3

Ask a large language model (LLM) whether a pointer dereference is safe, and it can often produce a plausible justification for ``yes''. The difficulty is that a fluent justificatio…

cs.SE2026

AgentFlow: Building Agent Dependency Graphs for Static Analysis of Agent Programs

Shenao Wang, Xinyi Hou, Yanjie Zhao +2

LLM agents are increasingly developed as source-code applications built on agent frameworks. These agent programs combine conventional host-language code with framework-defined sem…

cs.CR2026

Demystifying and Detecting Agentic Workflow Injection Vulnerabilities in GitHub Actions

Shenao Wang, Xinyi Hou, Zhao Liu +5

GitHub Actions is increasingly used to deploy LLM-based agents for repository-centric tasks such as issue triage, pull-request review, code modification, and release assistance. Th…

cs.AI2025

As If We've Met Before: LLMs Exhibit Certainty in Recognizing Seen Files

Haodong Li, Jingqi Zhang, Xiao Cheng +3

The remarkable language ability of Large Language Models (LLMs) stems from extensive training on vast datasets, often including copyrighted material, which raises serious concerns…

cs.SE2025

Flow Sensitivity without Control Flow Graph: An Efficient Andersen-Style Flow-Sensitive Pointer Analysis

Jiahao Zhang, Xiao Cheng, Yuxiang Lei

Flow-sensitive pointer analysis constitutes an essential component of precise program analysis for accurately modeling pointer behaviors by incorporating control flows. Flow-sensit…

cs.SE2025

Tracing Errors, Constructing Fixes: Repository-Level Memory Error Repair via Typestate-Guided Context Retrieval

Xiao Cheng, Zhihao Guo, Huan Huo +1

Memory-related errors in C programming continue to pose significant challenges in software development, primarily due to the complexities of manual memory management inherent in th…