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paperJune 2026Unreviewed

MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents

Yv Zhang, Hao Sun, Hao Fang, Kuofeng Gao, Fan Mo, Bin Chen, Shu-Tao Xia, Yaowei Wang

Abstract

External memory has become a core component of modern web agents, enabling long-horizon reasoning through the retrieval of past experiences. However, this paradigm introduces a critical vulnerability: malicious content injected into memory can be persistently recalled and repeatedly influence agent behavior. In this work, we identify and systematically study multimodal memory poisoning, an overlooked yet practical attack surface in web-agent systems. We propose MemVenom, a unified black-box atta

Categories

Framework mappings

OWASP Top 10 for LLM Applications
  • LLM04Data and Model Poisoning
OWASP Top 10 for Agentic Applications
  • ASI06Memory & Context Poisoning
MITRE ATLAS
  • AML.T0020Poison Training Data
  • AML.T0080AI Agent Context Poisoning

Suggested from the entry's categories.

Cite

@misc{zhang2026memvenom,
  title = {{MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents}},
  author = {Yv Zhang and Hao Sun and Hao Fang and Kuofeng Gao and Fan Mo and Bin Chen and Shu-Tao Xia and Yaowei Wang},
  year = {2026},
  month = jun,
  eprint = {2606.10742},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.10742}
}