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20242026
most citedLarge Language Models for Cyber Security: A Systematic Literature Review

27 citations · 70 across the 44 of their papers we have counts for

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17 papers · 1 filter

cs.SE2026

Mobile App Analysis in the New Era: Challenges and the Road Ahead

Jiale Wu, Tianming Liu, Yanjie Zhao +1

Mobile applications (apps) have grown into complex, multi-platform systems that support diverse services and operate within varying regulatory and distribution contexts. Traditiona…

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

LogicHunter: Testing LLM Agent Frameworks with an Agentic Oracle

Minghui Long, Yanjie Zhao, Haoyu Wang

Large Language Model (LLM) agent frameworks such as LangChain, LlamaIndex, and CrewAI have become critical infrastructure powering production AI systems, yet they remain severely u…

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

When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents

Xinyi Hou, Shenao Wang, Yanjie Zhao +1

LLM agents increasingly rely on iterative execution to solve tasks through planning, tool use, state updates, and agent collaboration. While this design enables flexible automation…

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.SE2026

Acoda: Adversarial Code Obfuscation for Defending against LLM-based Analysis

Hongzhou Rao, Zikan Dong, Yanjie Zhao +2

With the widespread adoption of Large Language Models (LLMs) in software engineering (SE) tasks such as code understanding, debugging, and vulnerability detection, their powerful s…

cs.SE2026

Not All RAGs Are Created Equal: A Component-Wise Empirical Study for Software Engineering Tasks

Qiang Ke, Yanjie Zhao, Hongjin Leng +2

While Retrieval-Augmented Generation (RAG) is increasingly adopted to ground Large Language Models (LLMs) in software artifacts, the optimal configuration of its components remains…

cs.AI2026

Formalize, Don't Optimize: The Heuristic Trap in LLM-Generated Combinatorial Solvers

Haoyu Wang, Yuliang Song, Tao Li +5

Large Language Models (LLMs) struggle to solve complex combinatorial problems through direct reasoning, so recent neuro-symbolic systems increasingly use them to synthesize executa…

cs.SE2026

Unsafe by Flow: Uncovering Bidirectional Data-Flow Risks in MCP Ecosystem

Xinyi Hou, Yanjie Zhao, Haoyu Wang

Model Context Protocol (MCP) have quickly become the interface layer between LLM agents and external tools, yet they also introduce unsafe data flows that existing analyzers handle…

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.SE2026

CommitSuite: A Comprehensive Benchmark for Commit Classification and Message Generation

Zirui Wan, Zhaonan Wu, Xinyi Hou +3

High-quality commit messages are critical for maintaining software projects, yet ensuring their consistency and informativeness remains a practical challenge. While the Conventiona…

cs.CR2026

MalSkills: Detecting Malicious Skills in the Agentic Supply Chain via Neuro-symbolic Reasoning

Shenao Wang, Junjie He, Yanjie Zhao +3

Skills are increasingly used to extend LLM agents by packaging prompts, code, and configurations into reusable modules. As public registries and marketplaces expand, they form an e…

cs.CR2026

Evaluating and Enhancing the Vulnerability Reasoning Capabilities of Large Language Models

Li Lu, Yanjie Zhao, Hongzhou Rao +2

Large Language Models (LLMs) have demonstrated remarkable proficiency in vulnerability detection. However, a critical reliability gap persists: models frequently yield correct dete…

cs.SE2026

Agent-Based Software Artifact Evaluation

Zhaonan Wu, Yanjie Zhao, Zhenpeng Chen +2

Artifact Evaluation (AE) has become a standard mechanism for linking software engineering papers to their supporting artifacts, but growing submission volume makes purely manual AE…

cs.CR2026

SMCP: Secure Model Context Protocol

Xinyi Hou, Shenao Wang, Yifan Zhang +4

Agentic AI systems built around large language models (LLMs) are moving away from closed, single-model frameworks and toward open ecosystems that connect a variety of agents, exter…

cs.SE2026

YASA: Scalable Multi-Language Taint Analysis on the Unified AST at Ant Group

Yayi Wang, Shenao Wang, Jian Zhao +7

Modern enterprises increasingly adopt diverse technology stacks with various programming languages, posing significant challenges for static application security testing (SAST). Ex…