The End of Trust: How Agentic AI Breaks Security Assumptions
Osama Zafar, Alexander Nemecek, Erman Ayday

TL;DR
Agentic AI fundamentally alters digital security by enabling high-fidelity, mass-scale deception, challenging existing detection and verification paradigms and requiring new governance approaches.
Contribution
The paper introduces the Infinite Impostor attack model and proposes a shift from actor authentication to action evaluation for security.
Findings
Agentic AI enables scalable, personalized deception at mass scale.
Detection systems assuming synthetic outputs are distinguishable are likely to fail.
Governance tensions increase as platforms become regulators of digital interactions.
Abstract
For decades, the security of digital interaction has rested on an unacknowledged economic constraint. Attackers faced a tradeoff between the fidelity of a deception and the scale at which it could be deployed. Convincing impersonation required sustained human effort and was confined to a narrow set of high-value targets, while mass-market attacks sacrificed plausibility for reach. Detection systems, verification mechanisms, and user awareness training have all been implicitly calibrated to the artifacts of cheap deception that this tradeoff produced. Agentic AI collapses the tradeoff, allowing high-fidelity, individually tailored deception to be produced at mass-market scale. We argue that this shift exhausts a security paradigm rather than merely intensifying the threat landscape. We introduce the Infinite Impostor, an attack model in which an autonomous agent interposes itself between…
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