Imagen de Portada

Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Murphy, Brendan, Bowen, Dillon, Mohammadzadeh, Shahrad, Tseng, Tom, Broomfield, Julius, Gleave, Adam, Pelrine, Kellin
Formato:	Preprint
Publicado:	2025
Materias:	Cryptography and Security Artificial Intelligence Computation and Language Computers and Society
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Emerging Vulnerabilities in Frontier Models: Multi-Turn Jailbreak Attacks
por: Gibbs, Tom, et al.
Publicado: (2024)

Exposing the Systematic Vulnerability of Open-Weight Models to Prefill Attacks
por: Struppek, Lukas, et al.
Publicado: (2026)

Scaling Trends for Data Poisoning in LLMs
por: Bowen, Dillon, et al.
Publicado: (2024)

Exploiting Novel GPT-4 APIs
por: Pelrine, Kellin, et al.
Publicado: (2023)

TombRaider: Entering the Vault of History to Jailbreak Large Language Models
por: Ding, Junchen, et al.
Publicado: (2025)

LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
por: Li, Nathaniel, et al.
Publicado: (2024)

A StrongREJECT for Empty Jailbreaks
por: Souly, Alexandra, et al.
Publicado: (2024)

How Alignment and Jailbreak Work: Explain LLM Safety through Intermediate Hidden States
por: Zhou, Zhenhong, et al.
Publicado: (2024)

How Real is Your Jailbreak? Fine-grained Jailbreak Evaluation with Anchored Reference
por: Liu, Songyang, et al.
Publicado: (2026)

Jailbreaking Leaves a Trace: Understanding and Detecting Jailbreak Attacks from Internal Representations of Large Language Models
por: Kadali, Sri Durga Sai Sowmya, et al.
Publicado: (2026)

A Simple and Efficient Jailbreak Method Exploiting LLMs' Helpfulness
por: Luo, Xuan, et al.
Publicado: (2025)

JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models
por: Feng, Yingchaojie, et al.
Publicado: (2024)

How Susceptible are Large Language Models to Ideological Manipulation?
por: Chen, Kai, et al.
Publicado: (2024)

Proactive defense against LLM Jailbreak
por: Zhao, Weiliang, et al.
Publicado: (2025)

Mitigating Jailbreaks with Intent-Aware LLMs
por: Yeo, Wei Jie, et al.
Publicado: (2025)

Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs
por: Liu, Fan, et al.
Publicado: (2024)

Knowledge-to-Jailbreak: Investigating Knowledge-driven Jailbreaking Attacks for Large Language Models
por: Tu, Shangqing, et al.
Publicado: (2024)

InfoFlood: Jailbreaking Large Language Models with Information Overload
por: Yadav, Advait, et al.
Publicado: (2025)

JailbreakEval: An Integrated Toolkit for Evaluating Jailbreak Attempts Against Large Language Models
por: Ran, Delong, et al.
Publicado: (2024)

AJAR: Adaptive Jailbreak Architecture for Red-teaming
por: Dou, Yipu, et al.
Publicado: (2026)

Harnessing Task Overload for Scalable Jailbreak Attacks on Large Language Models
por: Dong, Yiting, et al.
Publicado: (2024)

Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs
por: Li, Xiang, et al.
Publicado: (2025)

Defense Against the Dark Prompts: Mitigating Best-of-N Jailbreaking with Prompt Evaluation
por: Armstrong, Stuart, et al.
Publicado: (2025)

SecurityLingua: Efficient Defense of LLM Jailbreak Attacks via Security-Aware Prompt Compression
por: Li, Yucheng, et al.
Publicado: (2025)

One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs
por: Li, Linbao, et al.
Publicado: (2025)

Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models
por: Yang, Guangyu, et al.
Publicado: (2025)

Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models
por: Yu, Zhiyuan, et al.
Publicado: (2024)

Soft Begging: Modular and Efficient Shielding of LLMs against Prompt Injection and Jailbreaking based on Prompt Tuning
por: Ostermann, Simon, et al.
Publicado: (2024)

Jailbreaking Commercial Black-Box LLMs with Explicitly Harmful Prompts
por: Zhang, Chiyu, et al.
Publicado: (2025)

Sugar-Coated Poison: Benign Generation Unlocks LLM Jailbreaking
por: Wu, Yu-Hang, et al.
Publicado: (2025)

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs
por: Chen, Yunhao, et al.
Publicado: (2025)

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning
por: Sun, Bowen, et al.
Publicado: (2026)

The Shawshank Redemption of Embodied AI: Understanding and Benchmarking Indirect Environmental Jailbreaks
por: Li, Chunyang, et al.
Publicado: (2025)

Imperceptible Jailbreaking against Large Language Models
por: Gao, Kuofeng, et al.
Publicado: (2025)

Large Reasoning Models Are Autonomous Jailbreak Agents
por: Hagendorff, Thilo, et al.
Publicado: (2025)

LightDefense: A Lightweight Uncertainty-Driven Defense against Jailbreaks via Shifted Token Distribution
por: Yang, Zhuoran, et al.
Publicado: (2025)

PandaGuard: Systematic Evaluation of LLM Safety against Jailbreaking Attacks
por: Shen, Guobin, et al.
Publicado: (2025)

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking
por: Li, Jindong, et al.
Publicado: (2026)

AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak Defender
por: Zhao, Weixiang, et al.
Publicado: (2025)

LITMUS: Benchmarking Behavioral Jailbreaks of LLM Agents in Real OS Environments
por: Zhang, Chiyu, et al.
Publicado: (2026)