#defense mechanisms
6 papers · 1 filter
Piggybacking on Perception: Stealthy Concurrent Audio Prompt Injections against Multimodal LLM Agents
Mingxiao Liu, Yitong Li, Haoren Zhao +6
The paper studies stealthy audio prompt injection attacks that hide malicious instructions within normal speech to hijack multimodal LLM agents, introduces a benchmark (AudioAgentS…
Agent Harness Distillation: Inference-Time Harness Extraction and Exploitation in Autonomous Multi-Agent Systems
Yu Cui, Wuli Yang, Yirui Shi +4
The paper presents Agent Harness Distillation (AHD), a method for extracting and replicating inference-time coordination mechanisms (harnesses) from autonomous multi-agent systems…
MIND: Lightweight and Effective Memory Injection Defense for LLM Agents via Intent-Aware Information Bottleneck
Dongyi Liu, Haixing He, Xiaobao Wu +1
The paper introduces MIND, a lightweight framework that uses an intent‑aware information bottleneck to detect and filter poisoned memory in large language model agents, reducing at…
Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning
Hongliang Zhang, Zhongyuan Yu, Guijuan Wang +4
The paper proposes FedDAB, a two‑phase defense for federated learning that uses contrastive regularization and alignment checking to detect and exclude malicious local updates caus…
MemPoison: Uncovering Persistent Memory Threats and Structural Blind Spots in LLM Agents
Jifeng Gao, Kang Xia, Yi Zhang +5
The paper introduces MemPoison, a benchmark and analysis framework that studies how adversarial content can be injected into the persistent external memory of large language model…
Context Contamination in LLM Analysis of Network Security Logs: Poison with Passive Prompt Injection and Mitigation Evaluation
Rabimba Karanjai, Yang Lu, Hemanth Hegadehalli Madhavarao +2
The paper shows that large language models used to analyze network security logs can be tricked by malicious log entries that inject hidden prompts, and it evaluates attacks and de…