Cover Image

Leveraging LLM to Strengthen ML-Based Cross-Site Scripting Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Miczek, Dennis, Gabbireddy, Divyesh, Saha, Suman
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection
by: Gabbireddy, Divyesh, et al.
Published: (2026)

Operationalizing CaMeL: Strengthening LLM Defenses for Enterprise Deployment
by: Tallam, Krti, et al.
Published: (2025)

AttackPilot: Autonomous Inference Attacks Against ML Services With LLM-Based Agents
by: Wu, Yixin, et al.
Published: (2025)

SafePickle: Robust and Generic ML Detection of Malicious Pickle-based ML Models
by: Ohayon, Hillel, et al.
Published: (2026)

BugWhisperer: Fine-Tuning LLMs for SoC Hardware Vulnerability Detection
by: Tarek, Shams, et al.
Published: (2025)

Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning
by: Atitallah, Safa Ben, et al.
Published: (2024)

Leveraging LSTM and GAN for Modern Malware Detection
by: Gupta, Ishita, et al.
Published: (2024)

Democratizing ML for Enterprise Security: A Self-Sustained Attack Detection Framework
by: Momeni, Sadegh, et al.
Published: (2025)

SCORE: Syntactic Code Representations for Static Script Malware Detection
by: Erdemir, Ecenaz, et al.
Published: (2024)

LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution
by: Pohlenz, Christopher G. Pedraza, et al.
Published: (2026)

NegBLEURT Forest: Leveraging Inconsistencies for Detecting Jailbreak Attacks
by: Sleem, Lama, et al.
Published: (2025)

Leveraging Large Language Models to Detect npm Malicious Packages
by: Zahan, Nusrat, et al.
Published: (2024)

SECUREVENT: Hybrid AI/ML Security Monitoring for Distributed Event-Based Systems
by: Liang, Eric
Published: (2026)

A Study of Vulnerability Repair in JavaScript Programs with Large Language Models
by: Le, Tan Khang, et al.
Published: (2024)

A Demonstration of Self-Adaptive Jamming Attack Detection in AI/ML Integrated O-RAN
by: Rahman, Md Habibur, et al.
Published: (2025)

Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)

LAsset: An LLM-assisted Security Asset Identification Framework for System-on-Chip (SoC) Verification
by: Hasan, Md Ajoad, et al.
Published: (2026)

Design and Development of an ML/DL Attack Resistance of RC-Based PUF for IoT Security
by: Acharya, Joy, et al.
Published: (2026)

Good News for Script Kiddies? Evaluating Large Language Models for Automated Exploit Generation
by: Jin, David, et al.
Published: (2025)

SmartLLMSentry: A Comprehensive LLM Based Smart Contract Vulnerability Detection Framework
by: Zaazaa, Oualid, et al.
Published: (2024)

Behavior-Aware and Generalizable Defense Against Black-Box Adversarial Attacks for ML-Based IDS
by: Ennaji, Sabrine, et al.
Published: (2025)

UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks
by: Yu, Tianlong, et al.
Published: (2026)

Leveraging Machine Learning for Botnet Attack Detection in Edge-Computing Assisted IoT Networks
by: Rupanetti, Dulana, et al.
Published: (2025)

Beyond Detection: Leveraging Large Language Models for Cyber Attack Prediction in IoT Networks
by: Diaf, Alaeddine, et al.
Published: (2024)

VulnLLM-R: Specialized Reasoning LLM with Agent Scaffold for Vulnerability Detection
by: Nie, Yuzhou, et al.
Published: (2025)

LProtector: An LLM-driven Vulnerability Detection System
by: Sheng, Ze, et al.
Published: (2024)

STAF: Leveraging LLMs for Automated Attack Tree-Based Security Test Generation
by: Khule, Tanmay, et al.
Published: (2025)

Efficient and Encrypted Inference using Binarized Neural Networks within In-Memory Computing Architectures
by: Rajendran, Gokulnath, et al.
Published: (2025)

Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems
by: Yakubu, Paul Badu, et al.
Published: (2024)

Atlas: A Framework for ML Lifecycle Provenance & Transparency
by: Spoczynski, Marcin, et al.
Published: (2025)

SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents
by: Ouyang, Yipeng, et al.
Published: (2026)

eX-NIDS: A Framework for Explainable Network Intrusion Detection Leveraging Large Language Models
by: Houssel, Paul R. B., et al.
Published: (2025)

Hybrid Machine Learning Models for Intrusion Detection in IoT: Leveraging a Real-World IoT Dataset
by: Akif, Md Ahnaf, et al.
Published: (2025)

NetDeTox: Adversarial and Efficient Evasion of Hardware-Security GNNs via RL-LLM Orchestration
by: Wang, Zeng, et al.
Published: (2025)

Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code
by: Bappy, Md. Azizul Hakim, et al.
Published: (2025)

On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem
by: Pichler, Georg, et al.
Published: (2024)

Modification and Generated-Text Detection: Achieving Dual Detection Capabilities for the Outputs of LLM by Watermark
by: Cai, Yuhang, et al.
Published: (2025)

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection
by: Kulkarni, Prashant
Published: (2026)

Strengthening Human-Centric Chain-of-Thought Reasoning Integrity in LLMs via a Structured Prompt Framework
by: Zhou, Jiling, et al.
Published: (2026)

Enhancing TinyML Security: Study of Adversarial Attack Transferability
by: Shah, Parin, et al.
Published: (2024)