Cover Image

Hijacking Large Language Models via Adversarial In-Context Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhou, Xiangyu, Qiang, Yao, Zade, Saleh Zare, Khanduri, Prashant, Zhu, Dongxiao
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Computation and Language Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to Poison Large Language Models for Downstream Manipulation
by: Zhou, Xiangyu, et al.
Published: (2024)

Automatic Calibration for Membership Inference Attack on Large Language Models
by: Zade, Saleh Zare, et al.
Published: (2025)

Not All Tokens Are Meant to Be Forgotten
by: Zhou, Xiangyu, et al.
Published: (2025)

Image Hijacks: Adversarial Images can Control Generative Models at Runtime
by: Bailey, Luke, et al.
Published: (2023)

Empirical Analysis of Large Vision-Language Models against Goal Hijacking via Visual Prompt Injection
by: Kimura, Subaru, et al.
Published: (2024)

In-Context Representation Hijacking
by: Yona, Itay, et al.
Published: (2025)

Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models
by: Liu, Hongfu, et al.
Published: (2024)

PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
by: Zhu, Kaijie, et al.
Published: (2023)

Attention Smoothing Is All You Need For Unlearning
by: Zade, Saleh Zare, et al.
Published: (2026)

Privacy Preserving In-Context-Learning Framework for Large Language Models
by: Bhusal, Bishnu, et al.
Published: (2025)

Moshi Moshi? A Model Selection Hijacking Adversarial Attack
by: Petrucci, Riccardo, et al.
Published: (2025)

Osmosis Distillation: Model Hijacking with the Fewest Samples
by: Shi, Yuchen, et al.
Published: (2026)

Adversarial Attack on Large Language Models using Exponentiated Gradient Descent
by: Biswas, Sajib, et al.
Published: (2025)

VERA: Variational Inference Framework for Jailbreaking Large Language Models
by: Lochab, Anamika, et al.
Published: (2025)

Temporal Context Awareness: A Defense Framework Against Multi-turn Manipulation Attacks on Large Language Models
by: Kulkarni, Prashant, et al.
Published: (2025)

Model Hijacking Attack in Federated Learning
by: Li, Zheng, et al.
Published: (2024)

AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models
by: Liang, Jiacheng, et al.
Published: (2025)

MARAGE: Transferable Multi-Model Adversarial Attack for Retrieval-Augmented Generation Data Extraction
by: Hu, Xiao, et al.
Published: (2025)

PrisonBreak: Jailbreaking Large Language Models with at Most Twenty-Five Targeted Bit-flips
by: Coalson, Zachary, et al.
Published: (2024)

The Resurgence of GCG Adversarial Attacks on Large Language Models
by: Tan, Yuting, et al.
Published: (2025)

On Adversarial Robustness of Language Models in Transfer Learning
by: Turbal, Bohdan, et al.
Published: (2024)

Large Language Models for Code: Security Hardening and Adversarial Testing
by: He, Jingxuan, et al.
Published: (2023)

Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
by: Liu, Fuqiang, et al.
Published: (2024)

SSCAE -- Semantic, Syntactic, and Context-aware natural language Adversarial Examples generator
by: Asl, Javad Rafiei, et al.
Published: (2024)

Adversarial Text Purification: A Large Language Model Approach for Defense
by: Moraffah, Raha, et al.
Published: (2024)

Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models
by: Antari, Ahmad, et al.
Published: (2025)

Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
by: Yin, Haoteng, et al.
Published: (2024)

Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals
by: Zheng, Rui, et al.
Published: (2024)

Adaptive Pre-training Data Detection for Large Language Models via Surprising Tokens
by: Zhang, Anqi, et al.
Published: (2024)

Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign
by: Zhang, Ruisi, et al.
Published: (2025)

Model Provenance Testing for Large Language Models
by: Nikolic, Ivica, et al.
Published: (2025)

A Watermark for Large Language Models
by: Kirchenbauer, John, et al.
Published: (2023)

On the Reliability of Watermarks for Large Language Models
by: Kirchenbauer, John, et al.
Published: (2023)

RECAP: A Resource-Efficient Method for Adversarial Prompting in Large Language Models
by: Chugh, Rishit
Published: (2026)

Time Will Tell: Timing Side Channels via Output Token Count in Large Language Models
by: Zhang, Tianchen, et al.
Published: (2024)

Con Instruction: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalities
by: Geng, Jiahui, et al.
Published: (2025)

Defending Jailbreak Prompts via In-Context Adversarial Game
by: Zhou, Yujun, et al.
Published: (2024)

Modeling Behavioral Preferences of Cyber Adversaries Using Inverse Reinforcement Learning
by: Shinde, Aditya, et al.
Published: (2025)

Malware Classification from Memory Dumps Using Machine Learning, Transformers, and Large Language Models
by: Dweib, Areej, et al.
Published: (2025)

User Inference Attacks on Large Language Models
by: Kandpal, Nikhil, et al.
Published: (2023)