Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
Fuente:
arXiv
Saved in:
| Main Authors: | Liang, Zi, Ye, Qingqing, Liu, Xuan, Wang, Yanyun, Xu, Jianliang, Hu, Haibo |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can a Single Message Paralyze the AI Infrastructure? The Rise of AbO-DDoS Attacks through Targeted Mobius Injection
by: Liang, Zi, et al.
Published: (2026)
by: Liang, Zi, et al.
Published: (2026)
"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced Distillation
by: Liang, Zi, et al.
Published: (2024)
by: Liang, Zi, et al.
Published: (2024)
PrivDPR: Synthetic Graph Publishing with Deep PageRank under Differential Privacy
by: Zhang, Sen, et al.
Published: (2025)
by: Zhang, Sen, et al.
Published: (2025)
Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs
by: He, Xi, et al.
Published: (2024)
by: He, Xi, et al.
Published: (2024)
Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
by: Bai, Li, et al.
Published: (2025)
by: Bai, Li, et al.
Published: (2025)
Why Are My Prompts Leaked? Unraveling Prompt Extraction Threats in Customized Large Language Models
by: Liang, Zi, et al.
Published: (2024)
by: Liang, Zi, et al.
Published: (2024)
How Much Do Large Language Model Cheat on Evaluation? Benchmarking Overestimation under the One-Time-Pad-Based Framework
by: Liang, Zi, et al.
Published: (2025)
by: Liang, Zi, et al.
Published: (2025)
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
by: Liang, Zi, et al.
Published: (2025)
by: Liang, Zi, et al.
Published: (2025)
Membership Inference Attacks and Defenses in Federated Learning: A Survey
by: Bai, Li, et al.
Published: (2024)
by: Bai, Li, et al.
Published: (2024)
When Routine Chats Turn Toxic: Unintended Long-Term State Poisoning in Personalized Agents
by: Xu, Xiaoyu, et al.
Published: (2026)
by: Xu, Xiaoyu, et al.
Published: (2026)
LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy
by: Sun, Xinyue, et al.
Published: (2024)
by: Sun, Xinyue, et al.
Published: (2024)
AdvSGM: Differentially Private Graph Learning via Adversarial Skip-gram Model
by: Zhang, Sen, et al.
Published: (2025)
by: Zhang, Sen, et al.
Published: (2025)
A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks
by: Li, Haoyang, et al.
Published: (2025)
by: Li, Haoyang, et al.
Published: (2025)
Interactive Trimming against Evasive Online Data Manipulation Attacks: A Game-Theoretic Approach
by: Fu, Yue, et al.
Published: (2024)
by: Fu, Yue, et al.
Published: (2024)
From Domains to Instances: Dual-Granularity Data Synthesis for LLM Unlearning
by: Xu, Xiaoyu, et al.
Published: (2026)
by: Xu, Xiaoyu, et al.
Published: (2026)
RAG Safety: Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation
by: Zhao, Tianzhe, et al.
Published: (2025)
by: Zhao, Tianzhe, et al.
Published: (2025)
Continual Pretraining on Encrypted Synthetic Data for Privacy-Preserving LLMs
by: Liu, Honghao, et al.
Published: (2026)
by: Liu, Honghao, et al.
Published: (2026)
Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
by: Xu, Xiaoyu, et al.
Published: (2025)
by: Xu, Xiaoyu, et al.
Published: (2025)
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models
by: Xu, Xiaoyu, et al.
Published: (2025)
by: Xu, Xiaoyu, 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)
Is Your Prompt Safe? Investigating Prompt Injection Attacks Against Open-Source LLMs
by: Wang, Jiawen, et al.
Published: (2025)
by: Wang, Jiawen, et al.
Published: (2025)
Enhancing Prompt Injection Attacks to LLMs via Poisoning Alignment
by: Shao, Zedian, et al.
Published: (2024)
by: Shao, Zedian, et al.
Published: (2024)
SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks
by: He, Xuanli, et al.
Published: (2024)
by: He, Xuanli, et al.
Published: (2024)
Denial-of-Service Poisoning Attacks against Large Language Models
by: Gao, Kuofeng, et al.
Published: (2024)
by: Gao, Kuofeng, et al.
Published: (2024)
Sharpness-Aware Data Poisoning Attack
by: He, Pengfei, et al.
Published: (2023)
by: He, Pengfei, et al.
Published: (2023)
Privacy for Free: Leveraging Local Differential Privacy Perturbed Data from Multiple Services
by: Du, Rong, et al.
Published: (2025)
by: Du, Rong, et al.
Published: (2025)
CBPF: Filtering Poisoned Data Based on Composite Backdoor Attack
by: Xia, Hanfeng, et al.
Published: (2024)
by: Xia, Hanfeng, et al.
Published: (2024)
TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack
by: Wang, Yanyun, et al.
Published: (2022)
by: Wang, Yanyun, et al.
Published: (2022)
Fact2Fiction: Targeted Poisoning Attack to Agentic Fact-checking System
by: He, Haorui, et al.
Published: (2025)
by: He, Haorui, et al.
Published: (2025)
Federated Heavy Hitter Analytics with Local Differential Privacy
by: Zhang, Yuemin, et al.
Published: (2024)
by: Zhang, Yuemin, et al.
Published: (2024)
Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs
by: Xu, Zhao, et al.
Published: (2024)
by: Xu, Zhao, et al.
Published: (2024)
P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs
by: Zhao, Shuai, et al.
Published: (2025)
by: Zhao, Shuai, et al.
Published: (2025)
Protecting Your LLMs with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)
by: Liu, Zichuan, et al.
Published: (2024)
Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs
by: Liu, Fan, et al.
Published: (2024)
by: Liu, Fan, et al.
Published: (2024)
Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data
by: Baumgärtner, Tim, et al.
Published: (2024)
by: Baumgärtner, Tim, et al.
Published: (2024)
Semantic-Preserving Adversarial Attacks on LLMs: An Adaptive Greedy Binary Search Approach
by: Zhang, Chong, et al.
Published: (2025)
by: Zhang, Chong, et al.
Published: (2025)
Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs
by: German, Eyal, et al.
Published: (2025)
by: German, Eyal, et al.
Published: (2025)
Defending Against Neural Network Model Inversion Attacks via Data Poisoning
by: Zhou, Shuai, et al.
Published: (2024)
by: Zhou, Shuai, et al.
Published: (2024)
PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
by: Fu, Tingchen, et al.
Published: (2024)
by: Fu, Tingchen, et al.
Published: (2024)
ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking
by: Wu, Yutao, et al.
Published: (2025)
by: Wu, Yutao, et al.
Published: (2025)
Similar Items
-
Can a Single Message Paralyze the AI Infrastructure? The Rise of AbO-DDoS Attacks through Targeted Mobius Injection
by: Liang, Zi, et al.
Published: (2026) -
"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced Distillation
by: Liang, Zi, et al.
Published: (2024) -
PrivDPR: Synthetic Graph Publishing with Deep PageRank under Differential Privacy
by: Zhang, Sen, et al.
Published: (2025) -
Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs
by: He, Xi, et al.
Published: (2024) -
Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
by: Bai, Li, et al.
Published: (2025)