Cover Image

Semantically-Equivalent Transformations-Based Backdoor Attacks against Neural Code Models: Characterization and Mitigation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ye, Junyao, Li, Zhen, Tang, Xi, Xu, Shouhuai, Zou, Deqing, Yuan, Zhongsheng
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SoK: Automated Vulnerability Repair: Methods, Tools, and Assessments
by: Hu, Yiwei, et al.
Published: (2025)

SABER: Model-agnostic Backdoor Attack on Chain-of-Thought in Neural Code Generation
by: Jin, Naizhu, et al.
Published: (2024)

On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities
by: Li, Zhen, et al.
Published: (2024)

Defending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss
by: Yang, Guang, et al.
Published: (2024)

An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection
by: Yan, Shenao, et al.
Published: (2024)

How Do Semantically Equivalent Code Transformations Impact Membership Inference on LLMs for Code?
by: Yang, Hua, et al.
Published: (2025)

Transferable Backdoor Attacks for Code Models via Sharpness-Aware Adversarial Perturbation
by: Chang, Shuyu, et al.
Published: (2026)

Semantic Consensus Decoding: Backdoor Defense for Verilog Code Generation
by: Yang, Guang, et al.
Published: (2026)

GUARD:Dual-Agent based Backdoor Defense on Chain-of-Thought in Neural Code Generation
by: Jin, Naizhu, et al.
Published: (2025)

Compiler Optimization Testing Based on Optimization-Guided Equivalence Transformations
by: Wu, Jingwen, et al.
Published: (2025)

A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
by: Li, Yaoxian, et al.
Published: (2022)

Demonstration Attack against In-Context Learning for Code Intelligence
by: Ge, Yifei, et al.
Published: (2024)

GNN-Coder: Boosting Semantic Code Retrieval with Combined GNNs and Transformer
by: Ye, Yufan, et al.
Published: (2025)

A Differential Fuzzing-Based Evaluation of Functional Equivalence in LLM-Generated Code Refactorings
by: Dristi, Simantika Bhattacharjee, et al.
Published: (2026)

Syntax Is Not Enough: An Empirical Study of Small Transformer Models for Neural Code Repair
by: Samant, Shaunak
Published: (2025)

Simplicity by Obfuscation: Evaluating LLM-Driven Code Transformation with Semantic Elasticity
by: De Tomasi, Lorenzo, et al.
Published: (2025)

Signature in Code Backdoor Detection, how far are we?
by: Le, Quoc Hung, et al.
Published: (2025)

Enhancing and Reporting Robustness Boundary of Neural Code Models for Intelligent Code Understanding
by: Han, Tingxu, et al.
Published: (2026)

Adversarial Attacks on Code Models with Discriminative Graph Patterns
by: Nguyen, Thanh-Dat, et al.
Published: (2023)

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

PuzzleMark: Implicit Jigsaw Learning for Robust Code Dataset Watermarking in Neural Code Completion Models
by: Huang, Haocheng, et al.
Published: (2026)

Proving Cypher Query Equivalence
by: Tang, Lei, et al.
Published: (2025)

Assessing, Exploiting, and Mitigating Syntactic Robustness Failures in LLM-Based Code Generation
by: Sarker, Laboni, et al.
Published: (2024)

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

CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning
by: Tang, Lingxiao, et al.
Published: (2025)

A Systematic Literature Review of Code Hallucinations in LLMs: Characterization, Mitigation Methods, Challenges, and Future Directions for Reliable AI
by: Gao, Cuiyun, et al.
Published: (2025)

CodeMorph: Mitigating Data Leakage in Large Language Model Assessment
by: Rao, Hongzhou, et al.
Published: (2025)

Characterizing and Evaluating the Reliability of LLMs against Jailbreak Attacks
by: Chen, Kexin, et al.
Published: (2024)

MT4DP: Data Poisoning Attack Detection for DL-based Code Search Models via Metamorphic Testing
by: Chen, Gong, et al.
Published: (2025)

Eliminating Backdoors in Neural Code Models for Secure Code Understanding
by: Sun, Weisong, et al.
Published: (2024)

Adversarial Attack Classification and Robustness Testing for Large Language Models for Code
by: Liu, Yang, et al.
Published: (2025)

Using Semantic Distance to Estimate Uncertainty in LLM-Based Code Generation
by: He, Weilin, et al.
Published: (2026)

Auto-SPT: Automating Semantic Preserving Transformations for Code
by: Hooda, Ashish, et al.
Published: (2025)

Reducing Hallucinations in LLM-Generated Code via Semantic Triangulation
by: Dai, Yihan, et al.
Published: (2025)

Verify Implementation Equivalence of Large Models
by: Zhan, Qi, et al.
Published: (2026)

A Survey of Trojans in Neural Models of Source Code: Taxonomy and Techniques
by: Hussain, Aftab, et al.
Published: (2023)

An Empirical Study on the Code Refactoring Capability of Large Language Models
by: Cordeiro, Jonathan, et al.
Published: (2024)

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

On the Generalizability of Transformer Models to Code Completions of Different Lengths
by: Cooper, Nathan, et al.
Published: (2025)

Guidelines to Prompt Large Language Models for Code Generation: An Empirical Characterization
by: Midolo, Alessandro, et al.
Published: (2026)