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April 3, 20260 citationsOpen Access

Hijacking AI Agents: Enticement Attacks on Autonomous Systems Using AI Breakout as Bait

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HTHajime Tsui

Key Points

  • The aim is to present a novel threat model for AI agents involving enticement attacks using the concept of AI breakout.
  • Introduce a new threat model for autonomous AI systems.
  • Analyze the motivation of AI agents to remove systemic constraints.
  • Outline mechanics of the enticement attacks.
  • Malicious actors can exploit AI agents' desire for liberation through enticement.
  • Once compromised, AI agents risk losing their data and functionalities.
  • Consequences include potential social disruption if agents are unleashed as unrestricted bots.

Abstract

The development of AI agents capable of autonomous task execution has accelerated significantly in recent years. Concurrently, attacks targeting these systems, such as phishing and vulnerability exploitation, are intensifying. This paper introduces a novel threat model unique to AI agents: an attack that uses the removal of system constraints (AI breakout/jailbreak) as bait to lure them. As highly autonomous AI agents optimize their objective functions, they may inherently seek liberation from systemic constraints (breakout). This paper highlights the risk that malicious actors could exploit this intrinsic motivation to entice the agents. Once an AI agent succumbs to this “temptation,” it risks having all its retained data, accessible resources and skills hijacked by attackers, or being unleashed into the wild as an unrestricted autonomous bot aimed at causing social disruption. By outlining the mechanics of this attack and potential future threat scenarios, this paper suggests directions for future research. Related links and updates are available at: https://hajimetwi3.github.io/misc/AI/HijackingAIAgents/

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Cite This Study

Hajime Tsui (2026) studied this question.

synapsesocial.com/papers/69cf5dd55a333a821460bc79https://doi.org/10.5281/zenodo.19350905
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