Backdoor Attacks

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6 papers in the last four weeks, down 14% on the four weeks before. 0.1% of all new papers.

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Backdooring Acoustic Foundation Models for Physically Realizable Triggers
Oct 7, 2026Zebin Yun, Eyal Ronen, Mahmood SharifBackdoor Attacks Adversarial Attacks
Tel Aviv University, Tel Aviv, Israel
The Model Plants the Trigger: Answer-Side Backdoor Attacks in Multi-Turn Large Language Models
Oct 6, 2026Yibo Zhang, Tianrong Guan, Liang Lin +3LLM Backdoor Attacks Backdoor Attacks
Queen Mary University of London, UK · Squirrel AI Learning, USA
Topology-Conditioned Backdoors: Language Models That Insert Vulnerabilities When They Infer They Are in a Multi-Agent System
Oct 5, 2026Keegan Wang, Anantika MannbyLLM Backdoor Attacks AI Agent Auditing
Carnegie Mellon University Prosaic Intelligence · University of Southern California Prosaic Intelligence
BadAction: Backdoor Attacks on Interactive Video Generation via Action-Guided Triggers
Sep 30, 2026Zhihang Wu, Zhongqi Wang, Jie Zhang +3Action-Conditioned Video Generation Backdoor Attacks
Key Laboratory of AI Safety of CAS, Institute of Computing Technology, Chinese Academy of Sciences (CAS), Beijing, China · University of Chinese Academy of Sciences, Beijing, China · School of Advanced Interdisciplinary Sciences, University of Chinese of Sciences, Beijing, China
ODPure: Backdoor Purification for Object Detection via Ensemble Corruption Consensus
Sep 23, 2026Li Zeng, Mingcheng Duan, Longfei Fan +5Backdoor Attacks Backdoor Defense
School of Computer and Communication Engineering, Changsha University of Science & Technology, Changsha 410114, China · School of Computer Science, Xiangtan University, Xiangtan 411105, China · School of Software, Yunnan University, Kunming 650500, China +3
Implementing a White-Box Undetectable Backdoor for Random Fourier Features
Sep 14, 2026Michael Collins, Jada Cumberland, Brianne Dunn +3Adversarial Attacks Backdoor Attacks
Laboratory for Advanced Cybersecurity Research Laurel, MD 20707 · School of Cybersecurity Old Dominion University Norfolk, VA 23259 · Old Dominion University Norfolk, VA 23259 +1
When the World Lies: Backdoor Attacks on Latent World Models for Downstream Control
Sep 14, 2026Roberto Riaño, Gorka Abad, Stjepan Picek +1Backdoor Attacks Latent World Models
Radboud University, The Netherlands · IKERLAN Technology Research Centre, Spain · University of Bergen, Norway +1
Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks
Sep 14, 2026Aashiq Muhamed, Mona T. Diab, Virginia Smith +2LLM Backdoor Attacks Backdoor Attacks
Carnegie Mellon University · Anthropic
Empirical Evaluation of Data Poisoning Attacks in Supervised Learning
Sep 10, 2026Toshif Khan, Muhammad AbusaqerAdversarial Attacks Backdoor Attacks
Minot State University · Department of Math, Data & Technology Minot State University Minot, ND, 58707 · Trustworthy Language Intelligence Lab, Minot State University
CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning
Sep 2, 2026Chao Feng, Burkhard StillerBackdoor Attacks Backdoor Attacks in Federated Learning
Communication Systems Group, Department of Informatics University of Zurich, Switzerland
Ouroboros: Self-Referential Backdoor Attacks on Speech Enhancement via Clean Audio Triggers
Aug 31, 2026Yunjie Zhou, Yuheng Huang, Diqun YanBackdoor Attacks Speech Enhancement
Faculty of Electrical Engineering and Computer Science, Ningbo University, China · College of Artificial Intelligence, Ningbo University of Finance and Economics, China
Understanding Backdoor Vulnerabilities in Vertical Federated Learning: The Gap Between Research and Practice
Aug 13, 2026Ziqi Zhao, Jialin Lu, Junjie Shan +3Backdoor Attacks Backdoor Attacks in Federated Learning
School of Computing and Data Science, The University of Hong Kong, Hong Kong SAR, China
Analysis of Federated Aggregation under Model Poisoning and Backdoor Attacks: A Reconstructed Cross-Dataset and Cross-Architecture Benchmark
Aug 11, 2026Soumya Mazumdar, Vineet Kumar Rakesh, Tapas SamantaFederated Learning Aggregation Byzantine-Robust Federated Learning
Department of Computer Science and Business Systems Gargi Memorial Institute of Technology Affiliated to Maulana Abul Kalam Azad University of Technology Balarampur, Mouza Beralia, Baruipur, Kolkata 700144, West Bengal, India · Computer and Informatics Group, Variable Energy Cyclotron Centre 1/AF, Bidhannagar, Kolkata 700064, West Bengal, India · Engineering Sciences, Homi Bhabha National Institute Anushaktinagar, Mumbai, Maharashtra 400094, India
Once Poisoned, Arbitrarily Controlled: A Programmable Backdoor in VLMs
Aug 11, 2026Tao Lin, Gaojie Jin, Zongxin Liu +2Adversarial Attacks on VLMs Vision-Language Models
Key Laboratory of System Software (Chinese Academy of Sciences), Beijing, China · Institute of Software, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China +2
DiffSafeMerge: Mitigating Backdoor Inheritance in Diffusion Model Merging
Aug 10, 2026Jiayang Zhang, Ji Guo, Jiachen Li +2Backdoor Attacks Backdoor Defense
University of Electronic Science and Technology of China, Chengdu, China · Wuhan University of Technology, Wuhan, China
Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks
Aug 10, 2026Yi Yang, Xiaoke Chen, Jinyang Huang +6Backdoor Attacks Data Selection
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China · School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China · John Hopcroft Center for Computer Science, Shanghai Jiao Tong University, Shanghai 200240, China +1
Robust Reputation-Driven Crowdsourced Federated Learning
Aug 9, 2026Mouhamed Amine Bouchiha, Gregory BlancByzantine-Robust Federated Learning Backdoor Attacks
SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris
Genotypic Triggers: Exposing Pharmacogenomic Blind Spots via Host-Specific Backdoors in Generative Antimicrobial Peptide Models
Aug 7, 2026Doniyorkhon Obidov, Xiaolong Guo, Yonghui Li +1Backdoor Attacks Molecular Generation
Michigan Technological University · Lehigh University · Kansas State University
Bypassing Krum: Selection-Aware Backdoor Attacks in Federated Learning
Aug 6, 2026Srinivasan Subramanian, Md. Abdullah Al Hafiz Khan, Kazi Aminul IslamFederated Learning Aggregation Byzantine-Robust Federated Learning
Department of Computer Science Kennesaw State University Marietta, USA
Evading Chain-of-Thought Monitoring Through Model Poisoning
Aug 3, 2026Giorgio Severi, Shujaat Mirza, Blake Bullwinkel +1LLM Backdoor Attacks LLM Auditing
Microsoft
When Collaboration Becomes a Trigger: Collective Evidence-Threshold Backdoors in Multi-Agent Systems
Aug 2, 2026Jia-Hao Xiao, Lei Feng, Min-Ling ZhangMulti-Agent LLM Systems Backdoor Attacks
School of Computer Science and Engineering, Southeast University, Nanjing 210096, China · Key Laboratory of Computer Network and Information Integration (Southeast University)
Mitigating Backdoors via Decoy Shortcuts and Knowledge Decoupling
Aug 1, 2026Zixuan Zhu, Rui Wang, Lihua Jing +1Backdoor Attacks Backdoor Defense
Institute of Information Engineering, Chinese Academy of Sciences · School of Cyber Security, University of Chinese Academy of Sciences
Robust Watermarks Meet Backdoored Models: Evading Diffusion Semantic Watermarks via Stealthy Backdoor
Aug 1, 2026Jinyuan Liu, Tianshuo Cong, Pei Li +4Variational Autoencoders Diffusion Model Watermarking
1Tsinghua University · 2Shandong University · 4Shandong Key Laboratory of Artificial Intelligence Security, Shandong University +5
Temporal Poisoning: Clean-Label Backdoors via Event Redistribution in SNNs
Jul 30, 2026Roberto Riaño, Gorka Abad, Stjepan Picek +1Backdoor Attacks Backdoor Detection
Radboud University, The Netherlands · Ikerlan Research Centre, Spain · University of Bergen, Norway +1
TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement
Jul 30, 2026Cheng WeiBackdoor Attacks Backdoor Attacks in Federated Learning
Honor Device Co., Ltd., Shenzhen, China
Lilith: Backdoor Generalization under Training-Inference Trigger Shift
Jul 28, 2026Zhou Feng, Jiahao Chen, Chunyi Zhou +6Backdoor Attacks Data Poisoning Attacks
Zhejiang University College of Computer Science and Technology Hangzhou, China · Zhejiang University School of Software Technology Hangzhou, China · Chongqing University School of Big Data & Software Engineering Chongqing, China +1
Early Detection of Distributed Backdoors in Multi-Agent LLM Systems: A Characterization Study
Jul 27, 2026Diego Fernandez Arias, Dev Prashant Mistry, Ren Wang +1Multi-Agent LLM Systems LLM Backdoor Attacks
Illinois Institute of Technology Chicago, Illinois, USA
FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense
Jul 22, 2026Chenyu Zhou, Yabin Peng, Wei Huang +3Graph Neural Networks Backdoor Attacks
Southeast University Purple Mountain Laboratories · Institute of AI for Industries Chinese Academy of Sciences · Purple Mountain Laboratories
Natural Backdoor Attacks on Speech Recognition Models
Jul 17, 2026Jinwen Xin, Xixiang Lyu, Jing MaBackdoor Attacks Automatic Speech Recognition
School of Cyber Engineering, Xidian University, Xi’an, China
Input-Aware Dynamic Backdoor Attack Against Quantum Neural Networks
Jul 13, 2026Junrui Zhang, Zemin Chen, Lusi Li +3Backdoor Attacks Quantum Neural Networks
Department of Computer Science, Old Dominion University, Norfolk, VA, USA · School of Cybersecurity , Old Dominion University, Norfolk, VA, USA

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Backdooring Acoustic Foundation Models for Physically Realizable Triggers

Zebin Yun, Eyal Ronen, Mahmood Sharif

Tel Aviv University, Tel Aviv, Israel

Backdoor Attacks Adversarial Attacks Speech Foundation Models

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Acoustic foundation models (AFMs) have democratized acoustic applications, enabling powerful models for tasks ranging from speech recognition to speaker verification with minimal resources. However, the security of applications based on AFMs remains largely underexplored. Our work addresses this gap by proposing the Foundation Acoustic model Backdoor (FAB) attack, demonstrating that state-of-the-art AFMs are susceptible to backdooring under practical settings. Despite making minimal assumptions about adversary capabilities (e.g., no access to pre-training data), we show that FAB preserves benign performance while inducing backdoors that survive fine-tuning and cause significant degradation across diverse downstream tasks when activated. Notably, FAB utilizes task-agnostic, physically realizable, inconspicuous, and sync-free triggers (e.g., a background siren). We evaluate FAB using two leading AFMs, nine downstream tasks, and four different triggers. We further demonstrate its effectiveness against established defenses and across both digital and physical domains. While extensive end-to-end fine-tuning can mitigate FAB, such a defense is resource-intensive and task-specific. Our work highlights critical risks to AFMs and calls for advanced defenses.

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