RAG Security

RAG: Retrieval-Augmented Generation

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7 papers in the last four weeks, up 17% on the four weeks before. 0.1% of all new papers.

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RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems
Oct 6, 2026Niveen O. Jaffal, Ahmet Yuksel, David MohaisenRAG Security Prompt Injection Attacks on LLMs
Birzeit University, Birzeit, Palestine · Independent Researcher · University of Central Florida, Orlando, FL, USA
Mapping the RAG Landscape: A Four Axis Taxonomy of Efficiency, Defense, Interactivity, and Reasoning
Oct 1, 2026Meghana Sunil, Shravya V, Shravan Venkatraman +1Retrieval-Augmented Generation RAG Security
School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India. · Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE.
Quantization Enables Private Dense Retrieval against Malicious Service Providers
Sep 28, 2026Louis Tremblay Thibault, Sofiane Azogagh, Marc-Olivier Killijian +1RAG Security Dense Retrieval
École de technologie supérieure and Mila · Eurecom · Université du Québec à Montréal
RAG-NAROK: Retrieval-Aware Knowledge Corpus Poisoning in RAG with Source-specific Refutation
Sep 21, 2026Abdullahil Kafi, Alvi Ataur KhalilRAG Poisoning Attacks RAG Security
Transformative Innovation for Trustworthy AI and Network Security (TITANS) Lab, Computer Science, Southern Illinois University, USA
RAG-CT: Mitigating Privacy Risks on Retrieval-Augmented Generation Systems via Scanning Prompt Distribution
Sep 14, 2026Xingyu Lyu, Jiayimei Wang, Jianfeng He +3Privacy Leakage in Language Models RAG Security
University of Massachusetts Lowell, Lowell, MA 01854, USA · City University of Hong Kong, Kowloon, Hong Kong SAR, 999077, China · Virginia Tech, Blacksburg, VA 24061, USA +2
CiteShade: Citation Laundering in Multi-Source Retrieval-Augmented Generation and Its Counterfactual Defense
Sep 14, 2026Guo FuzhengRAG Poisoning Attacks RAG Security
City University of Hong Kong
RAG-Safety-Bench: Reliable Evaluation of Retrieval-Augmented LLM Safety
Sep 11, 2026Adithiyan Rajan Indira Saravanan, Kathleen C. FraserLLM Safety Benchmarks LLM Safety
Faculty of Engineering University of Ottawa Ottawa, Canada
In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning
Sep 10, 2026Iliano FasolinoRAG Poisoning Attacks RAG Security
Department of Computer Science University of Milan Milan, Italy
Rent-a-RAG: Embedding-Space Watermarks for Auditing Third-Party RAG
Sep 3, 2026Alexandr Goultiaev Tolstokorov, Kyriakos Mouratidis, Javad Dogani +1Dataset Watermarking RAG Security
IMDEA Networks Institute, Madrid, Spain · Universidad Carlos III de Madrid, Madrid, Spain · Singapore Management University, Singapore
TRIS: A Tri-Layer Retrieval Integrity Sieve Against Knowledge Poisoning
Aug 31, 2026Muhaimin Bin Munir, Akib Jawad Ononto, Nazia Shehnaz Joynab +2RAG Poisoning Attacks Retrieval Robustness
University of Texas at Dallas
When Detection Does Not Guarantee Resistance: Reasoning and Poisoned Context in RAG
Aug 17, 2026Mehrdad Ghassabi, Audrina Ebrahimi, Sadra Hakim +3Knowledge Conflicts in Language Models RAG Poisoning Attacks
University of Isfahan · University of Texas at Dallas · University of Windsor
RAGSieve: Self-Referenced Local Contrast for Knowledge-Poison Detection in Retrieval-Augmented Generation
Aug 13, 2026Xinlong Xu, Yoshua Y. LiRAG Poisoning Attacks RAG Security
Nanjing University of Information Science and Technology · Meituan
Privacy-Preserving RAG by Concealing Sensitive Information from External LLMs
Aug 13, 2026Saleh Almohaimeed, Saad Almohaimeed, Mousa Jari +2Retrieval-Augmented Generation Privacy Leakage in Language Models
College of Applied Computer Science, King Saud University, Riyadh, Saudi Arabia
Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation
Aug 10, 2026Yanhang Li, Zhichao Fan, Zexin ZhuangRetrieval-Augmented Generation RAG Security
Northeastern University · University of Illinois Urbana-Champaign · Southern Methodist University
HERALD: Counterfactual Audits and Minimal Repairs for Proof-of-Retrieval Rewards
Aug 6, 2026Zhuowen Liu, Bohan Cui, YinShang Guo +2Reward Hacking LLM Auditing
The Chinese University of Hong Kong · Fudan University · Nanjing University +2
Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework
Aug 5, 2026Zhaoqi Wang, Daqing He, Zijian Zhang +13RAG Poisoning Attacks AI Agent Security
Beijing Institute of Technology, Beijing, China
GoldenRetriever: Non-Interactive Homomorphic Encrypted Retrieval for Privacy-Preserving RAG
Jul 31, 2026Yang Gao, Gang Quan, Scott Piersall +3Retrieval-Augmented Generation Homomorphic Encryption
Department of Computer Science, University of Central Florida, Orlando, FL, USA · Electrical and Computer Engineering Department, Florida International University, Miami, FL, USA · College of Design, Construction and Planning, University of Florida, Gainesville, FL, USA
RAGuard: A Layered Defense Framework for Retrieval-Augmented Generation Systems Against Data Poisoning
Jul 28, 2026Pushkal Kumar, Tucker Nielson, Tanish Kolhe +2RAG Poisoning Attacks RAG Security
TriShieldRAG: A Three-Ring Defense-in-Depth Framework Against Knowledge Corruption in Retrieval-Augmented Generation
Jul 26, 2026Susil Kumar Mohanty, Rohit Patel, Kosuru Yuvaraj +2Retrieval-Augmented Generation RAG Poisoning Attacks
Department of Computer Science and Engineering, Indian Institute of Technology Jodhpur, Jodhpur, India
Salience Induction against Multi-Hop RAG Agents: Threat and Defense
Jul 20, 2026Xingfu Zhou, Pengfei Wang, Yuan Zhou +2Multi-Hop QA Adversarial Attacks
National University of Defense Technology China
MIRAGE: Defending Long-Form RAG Against Misinformation Pollution
Jul 6, 2026Saadeldine Eletter, Ruihong Zeng, Yuxia Wang +3RAG Poisoning Attacks Retrieval Robustness
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) · INSAIT, Sofia University St. Kliment Ohridski
A Failure-Mode Benchmark for Polymorphic Sybil Poisoning in RAG
Jul 4, 2026Donghyun Lee, Juntae KimRAG Poisoning Attacks RAG Security
Dongguk University · Department of Computer Engineering Dongguk University Seoul, Republic of Korea
A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems
Jun 30, 2026Seyed Bagher Hashemi Natanzi, Bo TangAI Agent Security LLM Security
Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
MIRROR: Novelty-Constrained Memory-Guided MCTS Red-Teaming for Agentic RAG
Jun 25, 2026Inderjeet Singh, Andrés Murillo, Motoyoshi Sekiya +2Multimodal RAG Tool-Augmented Language Model Agents
Fujitsu Research of Europe, United Kingdom · Fujitsu Limited, Japan
Tracing Target Answers in Poisoned Retrieval Corpora via Token Influence Attribution
Jun 24, 2026Yan-Lun Chen, Pin-Yu Chen, Chia-Mu Yu +3RAG Poisoning Attacks RAG Security
National Yang Ming Chiao Tung University · IBM Research · Hon Hai Research Institute
Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems
Jun 24, 2026Balamurugan Palanisamy, G S S Chalapathi, Vikas Hassija +1Retrieval-Augmented Generation Privacy-Preserving Language Models
Department of Electrical and Electronics Engineering Birla Institute of Technology and Science, Pilani, Pilani Campus Vidya Vihar, Pilani, Rajasthan 333031, India · Department of Computer Engineering, KIIT University Bhubaneshwar, Odisha 751024, India · Quantum Cloud Computing and Distributed Systems (qCLOUDS) Laboratory Department of Computing and Information Systems The University of Melbourne, Melbourne, Australia
Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity
Jun 23, 2026Yuanhe Zhao, Tianyu Zhang, Huafei Xing +3Retrieval-Augmented Generation Privacy Leakage in Language Models
School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China · Department of Computer & Information Science & Engineering, University of Florida, Gainesville, Florida, 32611, USA · NLP2CT Lab, Department of Computer and Information Science, University of Macau, Macao, 999078, Macao SAR +1
$π$ -RAG: Oblivious Retrieval via Semantic Quantization and Transcendental Addressing for Large Language Models
Jun 20, 2026Aniket Wattamwar, Mrunal KakirwarPrivacy-Preserving Language Models RAG Security
A Layered Security Framework Against Prompt Injection in RAG-Based Chatbots
Jun 17, 2026Gulshan Saleem, Nisar Ahmed, Muhammad Imran Zaman +1LLM Guardrails Indirect Prompt Injection
Sparkverse AI Ltd, Bradford, 100190, West Yorkshire, England, UK
Ghost Vectors: Soft-Deleted Embeddings Remain Reconstructible in HNSW Vector Databases
Jun 16, 2026Chandranil Chakraborttii, Jackeline García Alvarado, Sitora Abdulofizova +1Cybersecurity Privacy-Preserving ML
Trinity College, USA

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RAG-PIBench: A Leakage-Aware Benchmark for Prompt-Injection Detection in Trustworthy RAG Systems

Niveen O. Jaffal, Ahmet Yuksel, David Mohaisen

Birzeit University, Birzeit, Palestine · Independent Researcher · University of Central Florida, Orlando, FL, USA

RAG Security Prompt Injection Attacks on LLMs Prompt Injection Detection

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Retrieval-Augmented Generation (RAG) systems are vulnerable to prompt-injection attacks embedded in retrieved content. We introduce RAG-PIBench, a benchmark for RAG-style prompt-injection detection containing 4,876 contextual examples across frozen train, validation, and protected-test splits. Using a leakage-aware construction pipeline and strict evaluation protocol, we compare keyword-based, semantic-reference, TF-IDF, and transformer-based detectors. DistilBERT achieves the best protected-test performance (F1 = 0.896, PR-AUC = 0.968), while TF-IDF SVM and logistic regression remain competitive. Our results demonstrate the value of leakage-aware benchmark design and strong sparse baselines for reliable prompt-injection detection in RAG systems.

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Latest papers 74