AI Snitches Get Glitches: Towards Evading Agentic Surveillance
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 acro...
| Authors | Hyejun Jeong, Dzung Pham, Amir Houmansadr et al. |
|---|---|
| Primary category | cs.AI |
| Published | 24 June 2026 |
| Last updated at source | 4 September 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.