An AI Agent Execution Environment to Safeguard User Data

Abstract

AI agents promise to serve as general-purpose personal assistants for their users, which requires them to have access to private user data (e.g., personal and financial information). This poses a serious risk to security and privacy. Adversaries may attack the AI model (e.g., via prompt injection) to exfiltrate user data. Furthermore, sharing private data with an AI agent requires users to trust a potentially unscrupulous or compromised AI model provider with their private data. This paper prese

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@misc{stanley2026ai,
  title = {{An AI Agent Execution Environment to Safeguard User Data}},
  author = {Robert Stanley and Avi Verma and Lillian Tsai and Konstantinos Kallas and Sam Kumar},
  year = {2026},
  month = apr,
  eprint = {2604.19657},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2604.19657}
}