Cover Image

Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gabbireddy, Divyesh, Saha, Suman
Format:	Preprint
Published:	2026
Subjects:	Cryptography and Security Machine Learning Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging LLM to Strengthen ML-Based Cross-Site Scripting Detection
by: Miczek, Dennis, et al.
Published: (2025)

To Err is Machine: Vulnerability Detection Challenges LLM Reasoning
by: Steenhoek, Benjamin, et al.
Published: (2024)

From Lab to Reality: A Practical Evaluation of Deep Learning Models and LLMs for Vulnerability Detection
by: Lu, Chaomeng, et al.
Published: (2025)

On the Difficulty of Selecting Few-Shot Examples for Effective LLM-based Vulnerability Detection
by: Hannan, Md Abdul, et al.
Published: (2025)

Rethinking the Evaluation of Secure Code Generation
by: Dai, Shih-Chieh, et al.
Published: (2025)

deepSURF: Detecting Memory Safety Vulnerabilities in Rust Through Fuzzing LLM-Augmented Harnesses
by: Androutsopoulos, Georgios, et al.
Published: (2025)

Security and Quality in LLM-Generated Code: A Multi-Language, Multi-Model Analysis
by: Kharma, Mohammed, et al.
Published: (2025)

Evaluating and Improving the Robustness of Security Attack Detectors Generated by LLMs
by: Pasini, Samuele, et al.
Published: (2024)

Learning-based Models for Vulnerability Detection: An Extensive Study
by: Ni, Chao, et al.
Published: (2024)

A New Framework of Software Obfuscation Evaluation Criteria
by: De Sutter, Bjorn
Published: (2025)

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants
by: Štorek, Adam, et al.
Published: (2025)

Exploiting LLM Agent Supply Chains via Payload-less Skills
by: Liu, Xinyu, et al.
Published: (2026)

Protecting Deep Learning Model Copyrights with Adversarial Example-Free Reuse Detection
by: Luan, Xiaokun, et al.
Published: (2024)

BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer
by: Jha, Piyush, et al.
Published: (2023)

How Safe Are AI-Generated Patches? A Large-scale Study on Security Risks in LLM and Agentic Automated Program Repair on SWE-bench
by: Sajadi, Amirali, et al.
Published: (2025)

"You still have to study" -- On the Security of LLM generated code
by: Goetz, Stefan, et al.
Published: (2024)

LLM-based Vulnerability Discovery through the Lens of Code Metrics
by: Weissberg, Felix, et al.
Published: (2025)

From Trace to Line: LLM Agent for Real-World OSS Vulnerability Localization
by: Xi, Haoran, et al.
Published: (2025)

Towards Causal Deep Learning for Vulnerability Detection
by: Rahman, Md Mahbubur, et al.
Published: (2023)

Efficient Software Vulnerability Detection Using Transformer-based Models
by: Shaik, Sameer, et al.
Published: (2026)

MARGIN: Margin-Aware Regularized Geometry for Imbalanced Vulnerability Detection
by: Zhang, Yuteng, et al.
Published: (2026)

MVD: A Multi-Lingual Software Vulnerability Detection Framework
by: Zhang, Boyu, et al.
Published: (2024)

UniASM: Binary Code Similarity Detection without Fine-tuning
by: Gu, Yeming, et al.
Published: (2022)

A Study on Mixup-Inspired Augmentation Methods for Software Vulnerability Detection
by: Daneshvar, Seyed Shayan, et al.
Published: (2025)

Strategic Heterogeneous Multi-Agent Architecture for Cost-Effective Code Vulnerability Detection
by: Wang, Zhaohui Geoffrey
Published: (2026)

Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
by: Bostani, Hamid, et al.
Published: (2024)

Who Audits the Auditor? Tamper-Proof Fraud Detection with Blockchain-Anchored Explainable ML
by: Wang, Zhaohui
Published: (2026)

Code-Centric Detection of Vulnerability-Fixing Commits: A Unified Benchmark and Empirical Study
by: Loose, Nils, et al.
Published: (2026)

Security Vulnerability Detection with Multitask Self-Instructed Fine-Tuning of Large Language Models
by: Yang, Aidan Z. H., et al.
Published: (2024)

RESCUE: Retrieval Augmented Secure Code Generation
by: Shi, Jiahao, et al.
Published: (2025)

Dissecting Payload-based Transaction Phishing on Ethereum
by: Chen, Zhuo, et al.
Published: (2024)

Closing the Gap: A User Study on the Real-world Usefulness of AI-powered Vulnerability Detection & Repair in the IDE
by: Steenhoek, Benjamin, et al.
Published: (2024)

Deep Learning Model Security: Threats and Defenses
by: Wang, Tianyang, et al.
Published: (2024)

EditLord: Learning Code Transformation Rules for Code Editing
by: Li, Weichen, et al.
Published: (2025)

Beyond Fidelity: Explaining Vulnerability Localization of Learning-based Detectors
by: Cheng, Baijun, et al.
Published: (2024)

Learning to Triage Taint Flows Reported by Dynamic Program Analysis in Node.js Packages
by: Ni, Ronghao, et al.
Published: (2025)

THEMIS: Towards Practical Intellectual Property Protection for Post-Deployment On-Device Deep Learning Models
by: Huang, Yujin, et al.
Published: (2025)

SCoPE: Evaluating LLMs for Software Vulnerability Detection
by: Gonçalves, José, et al.
Published: (2024)

Black-Box Adversarial Attacks on LLM-Based Code Completion
by: Jenko, Slobodan, et al.
Published: (2024)

Evaluating LLaMA 3.2 for Software Vulnerability Detection
by: Gonçalves, José, et al.
Published: (2025)