12 citations · 17 across the 9 of their papers we have counts for
10 papers
Climbing the Hill: Prompt Injection Red-Teaming Against Frontier Models with Curriculum Reinforcement Learning
Chenlong Yin, Xiaolong Jin, Wei Zou +2
Prompt injection is a leading security risk for LLMs and LLM-based applications such as agents. State-of-the-art red-teaming methods for prompt injection leverage reinforcement lea…
CleanBase: Detecting Malicious Documents in RAG Knowledge Databases
Weifei Jin, Xilong Wang, Wei Zou +2
Retrieval-augmented generation (RAG) is vulnerable to prompt injection attacks, in which an adversary inserts malicious documents containing carefully crafted injected prompts into…
Poison Once, Exploit Forever: Environment-Injected Memory Poisoning Attacks on Web Agents
Wei Zou, Mingwen Dong, Miguel Romero Calvo +7
Memory makes LLM-based web agents personalized, powerful, yet exploitable. By storing past interactions to personalize future tasks, agents inadvertently create a persistent attack…
AgentWatcher: A Rule-based Prompt Injection Monitor
Yanting Wang, Wei Zou, Runpeng Geng +1
Large language models (LLMs) and their applications, such as agents, are highly vulnerable to prompt injection attacks. State-of-the-art prompt injection detection methods have the…
PIShield: Detecting Prompt Injection Attacks via Intrinsic LLM Features
Wei Zou, Yupei Liu, Yanting Wang +3
LLM-integrated applications are vulnerable to prompt injection attacks, where an attacker contaminates the input to inject malicious instructions, causing the LLM to follow the att…
TracLLM: A Generic Framework for Attributing Long Context LLMs
Yanting Wang, Wei Zou, Runpeng Geng +1
Long context large language models (LLMs) are deployed in many real-world applications such as RAG, agent, and broad LLM-integrated applications. Given an instruction and a long co…
FCert: Certifiably Robust Few-Shot Classification in the Era of Foundation Models
Yanting Wang, Wei Zou, Jinyuan Jia
Few-shot classification with foundation models (e.g., CLIP, DINOv2, PaLM-2) enables users to build an accurate classifier with a few labeled training samples (called support sample…
MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models
Yanting Wang, Hongye Fu, Wei Zou +1
Different from a unimodal model whose input is from a single modality, the input (called multi-modal input) of a multi-modal model is from multiple modalities such as image, 3D poi…
PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models
Wei Zou, Runpeng Geng, Binghui Wang +1
Large language models (LLMs) have achieved remarkable success due to their exceptional generative capabilities. Despite their success, they also have inherent limitations such as a…
Provably Robust Multi-bit Watermarking for AI-generated Text
Wenjie Qu, Wengrui Zheng, Tianyang Tao +6
Large Language Models (LLMs) have demonstrated remarkable capabilities of generating texts resembling human language. However, they can be misused by criminals to create deceptive…