Cover Image

MALSIGHT: Exploring Malicious Source Code and Benign Pseudocode for Iterative Binary Malware Summarization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lu, Haolang, Peng, Hongrui, Nan, Guoshun, Cui, Jiaoyang, Wang, Cheng, Jin, Weifei, Wang, Songtao, Pan, Shengli, Tao, Xiaofeng
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Artificial Intelligence Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation
by: Hu, Li, et al.
Published: (2026)

PCodeTrans: Translate Decompiled Pseudocode to Compilable and Executable Equivalent
by: Cui, Yuxin, et al.
Published: (2026)

DuET: Dual Execution for Test Output Prediction with Generated Code and Pseudocode
by: Han, Hojae, et al.
Published: (2026)

Can Emulating Semantic Translation Help LLMs with Code Translation? A Study Based on Pseudocode
by: Chen, Songqiang, et al.
Published: (2025)

Distilled GPT for Source Code Summarization
by: Su, Chia-Yi, et al.
Published: (2023)

FlowMalTrans: Unsupervised Binary Code Translation for Malware Detection Using Flow-Adapter Architecture
by: Hu, Minghao, et al.
Published: (2025)

Semantic Similarity Loss for Neural Source Code Summarization
by: Su, Chia-Yi, et al.
Published: (2023)

Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy?
by: Ibiyo, Motunrayo, et al.
Published: (2025)

BinaryAI: Binary Software Composition Analysis via Intelligent Binary Source Code Matching
by: Jiang, Ling, et al.
Published: (2024)

An Analysis of Malicious Packages in Open-Source Software in the Wild
by: Zhou, Xiaoyan, et al.
Published: (2024)

CodeMEM: AST-Guided Adaptive Memory for Repository-Level Iterative Code Generation
by: Wang, Peiding, et al.
Published: (2026)

Identifying Adversary Tactics and Techniques in Malware Binaries with an LLM Agent
by: Xuan, Zhou, et al.
Published: (2026)

Models Are Codes: Towards Measuring Malicious Code Poisoning Attacks on Pre-trained Model Hubs
by: Zhao, Jian, et al.
Published: (2024)

Backdoors in Code Summarizers: How Bad Is It?
by: Wang, Chenyu, et al.
Published: (2025)

MCGMark: An Encodable and Robust Online Watermark for Tracing LLM-Generated Malicious Code
by: Ning, Kaiwen, et al.
Published: (2024)

KGMark: A Diffusion Watermark for Knowledge Graphs
by: Peng, Hongrui, et al.
Published: (2025)

Smoke and Mirrors: Jailbreaking LLM-based Code Generation via Implicit Malicious Prompts
by: Ouyang, Sheng, et al.
Published: (2025)

Resource-Efficient & Effective Code Summarization
by: Afrin, Saima, et al.
Published: (2025)

Exploring the Impact of Source Code Linearity on the Programmers Comprehension of API Code Examples
by: Alharbi, Seham, et al.
Published: (2024)

Do Machines and Humans Focus on Similar Code? Exploring Explainability of Large Language Models in Code Summarization
by: Li, Jiliang, et al.
Published: (2024)

Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough?
by: Vitale, Antonio, et al.
Published: (2025)

RepoSummary: Feature-Oriented Summarization and Documentation Generation for Code Repositories
by: Zhu, Yifeng, et al.
Published: (2025)

SCAFFOLD-CEGIS: Preventing Latent Security Degradation in LLM-Driven Iterative Code Refinement
by: Chen, Yi, et al.
Published: (2026)

SparseCoder: Identifier-Aware Sparse Transformer for File-Level Code Summarization
by: Wang, Yanlin, et al.
Published: (2024)

Zero-Shot Code Representation Learning via Prompt Tuning
by: Cui, Nan, et al.
Published: (2024)

On the Effectiveness of LLM-as-a-judge for Code Generation and Summarization
by: Crupi, Giuseppe, et al.
Published: (2025)

Logic Error Localization in Student Programming Assignments Using Pseudocode and Graph Neural Networks
by: Xu, Zhenyu, et al.
Published: (2024)

Decompile-Bench: Million-Scale Binary-Source Function Pairs for Real-World Binary Decompilation
by: Tan, Hanzhuo, et al.
Published: (2025)

Analysis on LLMs Performance for Code Summarization
by: Akib, Md. Ahnaf, et al.
Published: (2024)

ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization
by: Fang, Chunrong, et al.
Published: (2024)

Source Code Summarization in the Era of Large Language Models
by: Sun, Weisong, et al.
Published: (2024)

Exploring Multi-Lingual Bias of Large Code Models in Code Generation
by: Wang, Chaozheng, et al.
Published: (2024)

Code vs Serialized AST Inputs for LLM-Based Code Summarization: An Empirical Study
by: Dong, Shijia, et al.
Published: (2026)

Exploring Neural Network Structure Code Reuse in the Open‐Source Community for Improving Maintenance
by: Xiaoning Ren, et al.
Published: (2026)

Readability-Robust Code Summarization via Meta Curriculum Learning
by: Zeng, Wenhao, et al.
Published: (2026)

Towards Summarizing Code Snippets Using Pre-Trained Transformers
by: Mastropaolo, Antonio, et al.
Published: (2024)

Can Large Language Models Serve as Evaluators for Code Summarization?
by: Wu, Yang, et al.
Published: (2024)

Programmer Visual Attention During Context-Aware Code Summarization
by: Wallace, Robert, et al.
Published: (2024)

Examining LLMs Ability to Summarize Code Through Mutation-Analysis
by: Khatib, Lara, et al.
Published: (2026)

CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation
by: Wang, Sizhe, et al.
Published: (2025)