pisas-contextual-integrity-multi-user-agentic

name	pisas-contextual-integrity-multi-user-agentic
description	Benchmarking contextual integrity in multi-user agentic systems. As LLM agents evolve into shared organizational infrastructure, new privacy risks emerge from inter-agent messages, shared memory, and cross-user information exposure. Activation: contextual integrity, multi-user agents, privacy benchmark, agentic privacy, inter-agent communication, shared memory privacy.
metadata	{"arxiv_id":"2607.05318","published":"2026-07-06","authors":"Shubham Gupta, Nazanin Mohammadi Sepahvand, Abhinav Kumar, Cem Subakan, Spandana Gella, Pierre-André Noël, Perouz Taslakian, Eugene Bagdasarian, Valentina Zantedeschi","tags":["contextual-integrity","multi-user-agents","privacy","benchmark","inter-agent-communication","shared-memory"]}

PiSAs: Benchmarking Contextual Integrity in Multi-User Agentic Systems

Overview

As LLM agents evolve from single-user assistants into shared organizational infrastructure, new privacy risks emerge: inappropriate information may not only be exposed through outputs for external recipients, but also internally across users through inter-agent messages, shared memory and agents. This paper introduces PiSAs, a benchmark for evaluating contextual integrity in multi-user agentic systems.

Key Problem

Multi-User Privacy Risks in Agentic Systems

• Inter-agent message leakage: Agents sharing information with other agents serving different users
• Shared memory exposure: Common memory stores accessible across user contexts
• Contextual integrity violations: Information appropriate in one context may be inappropriate in another
• Internal vs external risks: Privacy violations can occur internally (across users) not just externally