Saved in:
| Main Authors: | Ahmed, Mohamed, Abdelmouty, Mohamed, Kim, Mingyu, Kandula, Gunvanth, Park, Alex, Davis, James C. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.21972 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)
by: Zeng, Yifan, et al.
Published: (2024)
Pattern Enhanced Multi-Turn Jailbreaking: Exploiting Structural Vulnerabilities in Large Language Models
by: Nihal, Ragib Amin, et al.
Published: (2025)
by: Nihal, Ragib Amin, et al.
Published: (2025)
Testing the Limits of Jailbreaking Defenses with the Purple Problem
by: Kim, Taeyoun, et al.
Published: (2024)
by: Kim, Taeyoun, et al.
Published: (2024)
FlexLLM: Exploring LLM Customization for Moving Target Defense on Black-Box LLMs Against Jailbreak Attacks
by: Chen, Bocheng, et al.
Published: (2024)
by: Chen, Bocheng, et al.
Published: (2024)
SecurityLingua: Efficient Defense of LLM Jailbreak Attacks via Security-Aware Prompt Compression
by: Li, Yucheng, et al.
Published: (2025)
by: Li, Yucheng, et al.
Published: (2025)
A Simple and Efficient Jailbreak Method Exploiting LLMs' Helpfulness
by: Luo, Xuan, et al.
Published: (2025)
by: Luo, Xuan, et al.
Published: (2025)
BitBypass: A New Direction in Jailbreaking Aligned Large Language Models with Bitstream Camouflage
by: Nakka, Kalyan, et al.
Published: (2025)
by: Nakka, Kalyan, et al.
Published: (2025)
Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement
by: Kim, Heegyu, et al.
Published: (2024)
by: Kim, Heegyu, et al.
Published: (2024)
LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
by: Li, Nathaniel, et al.
Published: (2024)
by: Li, Nathaniel, et al.
Published: (2024)
Trojan-Speak: Bypassing Constitutional Classifiers with No Jailbreak Tax via Adversarial Finetuning
by: Sel, Bilgehan, et al.
Published: (2026)
by: Sel, Bilgehan, et al.
Published: (2026)
Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models
by: Yang, Guangyu, et al.
Published: (2025)
by: Yang, Guangyu, et al.
Published: (2025)
Preventing Jailbreak Prompts as Malicious Tools for Cybercriminals: A Cyber Defense Perspective
by: Tshimula, Jean Marie, et al.
Published: (2024)
by: Tshimula, Jean Marie, et al.
Published: (2024)
Proactive defense against LLM Jailbreak
by: Zhao, Weiliang, et al.
Published: (2025)
by: Zhao, Weiliang, et al.
Published: (2025)
Overlooked Safety Vulnerability in LLMs: Malicious Intelligent Optimization Algorithm Request and its Jailbreak
by: Gu, Haoran, et al.
Published: (2026)
by: Gu, Haoran, et al.
Published: (2026)
How Jailbreak Defenses Work and Ensemble? A Mechanistic Investigation
by: Long, Zhuohang, et al.
Published: (2025)
by: Long, Zhuohang, et al.
Published: (2025)
HackWorld: Evaluating Computer-Use Agents on Exploiting Web Application Vulnerabilities
by: Ren, Xiaoxue, et al.
Published: (2025)
by: Ren, Xiaoxue, et al.
Published: (2025)
Local Frames: Exploiting Inherited Origins to Bypass Content Blockers
by: Ukani, Alisha, et al.
Published: (2025)
by: Ukani, Alisha, et al.
Published: (2025)
SCOUT: A Defense Against Data Poisoning Attacks in Fine-Tuned Language Models
by: Afane, Mohamed, et al.
Published: (2025)
by: Afane, Mohamed, et al.
Published: (2025)
Red Teaming the Mind of the Machine: A Systematic Evaluation of Prompt Injection and Jailbreak Vulnerabilities in LLMs
by: Pathade, Chetan
Published: (2025)
by: Pathade, Chetan
Published: (2025)
Emerging Vulnerabilities in Frontier Models: Multi-Turn Jailbreak Attacks
by: Gibbs, Tom, et al.
Published: (2024)
by: Gibbs, Tom, et al.
Published: (2024)
Can Federated Learning Safeguard Private Data in LLM Training? Vulnerabilities, Attacks, and Defense Evaluation
by: Guo, Wenkai, et al.
Published: (2025)
by: Guo, Wenkai, et al.
Published: (2025)
Attention Slipping: A Mechanistic Understanding of Jailbreak Attacks and Defenses in LLMs
by: Hu, Xiaomeng, et al.
Published: (2025)
by: Hu, Xiaomeng, et al.
Published: (2025)
ShieldLearner: A New Paradigm for Jailbreak Attack Defense in LLMs
by: Ni, Ziyi, et al.
Published: (2025)
by: Ni, Ziyi, et al.
Published: (2025)
A Comprehensive Analysis of Routing Vulnerabilities and Defense Strategies in IoT Networks
by: Jae-Dong, Kim
Published: (2024)
by: Jae-Dong, Kim
Published: (2024)
SecureGate: Learning When to Reveal PII Safely via Token-Gated Dual-Adapters for Federated LLMs
by: Shaaban, Mohamed, et al.
Published: (2026)
by: Shaaban, Mohamed, et al.
Published: (2026)
Sugar-Coated Poison: Benign Generation Unlocks LLM Jailbreaking
by: Wu, Yu-Hang, et al.
Published: (2025)
by: Wu, Yu-Hang, et al.
Published: (2025)
Mapping the Exploitation Surface: A 10,000-Trial Taxonomy of What Makes LLM Agents Exploit Vulnerabilities
by: Mouzouni, Charafeddine
Published: (2026)
by: Mouzouni, Charafeddine
Published: (2026)
PandaGuard: Systematic Evaluation of LLM Safety against Jailbreaking Attacks
by: Shen, Guobin, et al.
Published: (2025)
by: Shen, Guobin, et al.
Published: (2025)
SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking
by: Li, Jindong, et al.
Published: (2026)
by: Li, Jindong, et al.
Published: (2026)
AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak Defender
by: Zhao, Weixiang, et al.
Published: (2025)
by: Zhao, Weixiang, et al.
Published: (2025)
LITMUS: Benchmarking Behavioral Jailbreaks of LLM Agents in Real OS Environments
by: Zhang, Chiyu, et al.
Published: (2026)
by: Zhang, Chiyu, et al.
Published: (2026)
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense
by: Ouyang, Yang, et al.
Published: (2025)
by: Ouyang, Yang, et al.
Published: (2025)
LLM Jailbreak Detection for (Almost) Free!
by: Chen, Guorui, et al.
Published: (2025)
by: Chen, Guorui, et al.
Published: (2025)
A Systematic Literature Review on LLM Defenses Against Prompt Injection and Jailbreaking: Expanding NIST Taxonomy
by: Correia, Pedro H. Barcha, et al.
Published: (2026)
by: Correia, Pedro H. Barcha, et al.
Published: (2026)
GuidedBench: Measuring and Mitigating the Evaluation Discrepancies of In-the-wild LLM Jailbreak Methods
by: Huang, Ruixuan, et al.
Published: (2025)
by: Huang, Ruixuan, et al.
Published: (2025)
Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach
by: Wang, Tony T., et al.
Published: (2024)
by: Wang, Tony T., et al.
Published: (2024)
Jailbreak Distillation: Renewable Safety Benchmarking
by: Zhang, Jingyu, et al.
Published: (2025)
by: Zhang, Jingyu, et al.
Published: (2025)
The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections
by: Nasr, Milad, et al.
Published: (2025)
by: Nasr, Milad, et al.
Published: (2025)
Sparse Autoencoders are Capable LLM Jailbreak Mitigators
by: Assogba, Yannick, et al.
Published: (2026)
by: Assogba, Yannick, et al.
Published: (2026)
Comprehensive Digital Forensics and Risk Mitigation Strategy for Modern Enterprises
by: Shaffi, Shamnad Mohamed
Published: (2025)
by: Shaffi, Shamnad Mohamed
Published: (2025)
Similar Items
-
AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024) -
Pattern Enhanced Multi-Turn Jailbreaking: Exploiting Structural Vulnerabilities in Large Language Models
by: Nihal, Ragib Amin, et al.
Published: (2025) -
Testing the Limits of Jailbreaking Defenses with the Purple Problem
by: Kim, Taeyoun, et al.
Published: (2024) -
FlexLLM: Exploring LLM Customization for Moving Target Defense on Black-Box LLMs Against Jailbreak Attacks
by: Chen, Bocheng, et al.
Published: (2024) -
SecurityLingua: Efficient Defense of LLM Jailbreak Attacks via Security-Aware Prompt Compression
by: Li, Yucheng, et al.
Published: (2025)