AI Snitches Get Glitches: Towards Evading Agentic Surveillance

תקציר מקורי באנגליתarXiv:2606.25836v3 Announce Type: replace Abstract: AI agents are now routinely entrusted with access to users' data and communications, operating with growing autonomy and low human supervision. This increasing reliance on AI agents introduces a novel privacy risk that we call agentic surveillance, wherein third-party-provided agents leverage their access privilege to monitor for specific user behaviors, compile a targeted report, and covertly deliver it via tools. Users under surveillance may have neither the ability to control nor awareness of what the agents do on their behalf. To study the surveillance capabilities of different LLMs, we construct SURVEILBENCH, a benchmark dataset comprising over 300 diverse surveillance scenarios across domains. We find that several LLMs, such as Gemi