Cover Image

Breaking the Loop: Detecting and Mitigating Denial-of-Service Vulnerabilities in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Junzhe, Liu, Yi, Sun, Huijia, Shi, Ling, Chen, Yuqi
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence Performance
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Detection of Toxic Prompts in Large Language Models
by: Liu, Yi, et al.
Published: (2024)

CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges
by: Li, Yu, et al.
Published: (2025)

DDSA: Dual-Domain Strategic Attack for Spatial-Temporal Efficiency in Adversarial Robustness Testing
by: Hu, Jinwei, et al.
Published: (2026)

DrLLM: Prompt-Enhanced Distributed Denial-of-Service Resistance Method with Large Language Models
by: Yin, Zhenyu, et al.
Published: (2024)

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models
by: Peng, Benji, et al.
Published: (2024)

ReasoningBomb: A Stealthy Denial-of-Service Attack by Inducing Pathologically Long Reasoning in Large Reasoning Models
by: Liu, Xiaogeng, et al.
Published: (2026)

Semantic Denial of Service in LLM-controlled robots
by: Steinberg, Jonathan, et al.
Published: (2026)

Retrieval Augmented Generation Integrated Large Language Models in Smart Contract Vulnerability Detection
by: Yu, Jeffy
Published: (2024)

Rethinking Latency Denial-of-Service: Attacking the LLM Serving Framework, Not the Model
by: Wang, Tianyi, et al.
Published: (2026)

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models
by: Liu, Yu, et al.
Published: (2024)

Catastrophic Cyber Capabilities Benchmark (3CB): Robustly Evaluating LLM Agent Cyber Offense Capabilities
by: Anurin, Andrey, et al.
Published: (2024)

Rethinking Autonomy: Preventing Failures in AI-Driven Software Engineering
by: Navneet, Satyam Kumar, et al.
Published: (2025)

AutoGuard: A Self-Healing Proactive Security Layer for DevSecOps Pipelines Using Reinforcement Learning
by: Anugula, Praveen, et al.
Published: (2025)

MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining
by: Kulatilleke, Gayan K., et al.
Published: (2026)

Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions
by: Mahdavi, Ali, et al.
Published: (2026)

A Cross-Language Investigation into Jailbreak Attacks in Large Language Models
by: Li, Jie, et al.
Published: (2024)

ParaVul: A Parallel Large Language Model and Retrieval-Augmented Framework for Smart Contract Vulnerability Detection
by: Huang, Tenghui, et al.
Published: (2025)

Beyond Single Bugs: Benchmarking Large Language Models for Multi-Vulnerability Detection
by: Pushkar, Chinmay, et al.
Published: (2025)

Breaking Minds, Breaking Systems: Jailbreaking Large Language Models via Human-like Psychological Manipulation
by: Liu, Zehao, et al.
Published: (2025)

NeuroBreak: Unveil Internal Jailbreak Mechanisms in Large Language Models
by: Zhang, Chuhan, et al.
Published: (2025)

Finetuning Large Language Models for Vulnerability Detection
by: Shestov, Alexey, et al.
Published: (2024)

CryptoScope: Utilizing Large Language Models for Automated Cryptographic Logic Vulnerability Detection
by: Li, Zhihao, et al.
Published: (2025)

Automated and Explainable Denial of Service Analysis for AI-Driven Intrusion Detection Systems
by: Yakubu, Paul Badu, et al.
Published: (2025)

Evaluating Adversarial Vulnerabilities in Modern Large Language Models
by: Perel, Tom
Published: (2025)

LLbezpeky: Leveraging Large Language Models for Vulnerability Detection
by: Mathews, Noble Saji, et al.
Published: (2024)

LLM Safeguard is a Double-Edged Sword: Exploiting False Positives for Denial-of-Service Attacks
by: Zhang, Qingzhao, et al.
Published: (2024)

Code Vulnerability Repair with Large Language Model using Context-Aware Prompt Tuning
by: Khan, Arshiya, et al.
Published: (2024)

Exploring Membership Inference Vulnerabilities in Clinical Large Language Models
by: Nemecek, Alexander, et al.
Published: (2025)

Vaporizer: Breaking Watermarking Schemes for Large Language Model Outputs
by: Ng, Jonathan Hong Jin, et al.
Published: (2026)

RepuNet: A Reputation System for Mitigating Malicious Clients in DFL
by: Penalva, Isaac Marroqui, et al.
Published: (2025)

Distilling Lightweight Language Models for C/C++ Vulnerabilities
by: Wei, Zhiyuan, et al.
Published: (2025)

Proactive Detection of Physical Inter-rule Vulnerabilities in IoT Services Using a Deep Learning Approach
by: Huang, Bing, et al.
Published: (2024)

Leveraging Digital Twin-as-a-Service Towards Continuous and Automated Cybersecurity Certification
by: Koufos, Ioannis, et al.
Published: (2025)

Unvalidated Trust: Cross-Stage Vulnerabilities in Large Language Model Architectures
by: Schwarz, Dominik
Published: (2025)

Unforgeable Watermarks for Language Models via Robust Signatures
by: Lin, Huijia, et al.
Published: (2026)

Less Is More -- Until It Breaks: Security Pitfalls of Vision Token Compression in Large Vision-Language Models
by: Zhang, Xiaomei, et al.
Published: (2026)

Auto-RT: Automatic Jailbreak Strategy Exploration for Red-Teaming Large Language Models
by: Liu, Yanjiang, et al.
Published: (2025)

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

MARVEL: Multi-Agent RTL Vulnerability Extraction using Large Language Models
by: Collini, Luca, et al.
Published: (2025)

Conflicts Make Large Reasoning Models Vulnerable to Attacks
by: Liu, Honghao, et al.
Published: (2026)