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Superplatforms Have to Attack AI Agents

Jianghao Lin, Jiachen Zhu, Zheli Zhou, Yunjia Xi, Weiwen Liu, Yong Yu, Weinan Zhang

TL;DR

This paper argues that superplatforms risk disintermediation by AI agents and should proactively attack GUI-based agents to preserve gatekeeping and advertising-driven revenue. It applies gatekeeping theory to analyze threats and outlines three strategic countermeasures—proprietary agents, API gating, and proactive adversarial attacks—with a focus on GUI interactions as the hardest to curb. A detailed taxonomy of attack goals, attacker knowledge, visibility, and timing for superplatform-initiated attacks is provided, along with discussion of unique challenges like universal task obstruction and environmental injections. The authors also present alternative views on data moats and potential complementarities, ultimately asserting that, despite ethical cautions, understanding these tensions is essential for safeguarding digital ecosystems in the AI era.

Abstract

Over the past decades, superplatforms, digital companies that integrate a vast range of third-party services and applications into a single, unified ecosystem, have built their fortunes on monopolizing user attention through targeted advertising and algorithmic content curation. Yet the emergence of AI agents driven by large language models (LLMs) threatens to upend this business model. Agents can not only free user attention with autonomy across diverse platforms and therefore bypass the user-attention-based monetization, but might also become the new entrance for digital traffic. Hence, we argue that superplatforms have to attack AI agents to defend their centralized control of digital traffic entrance. Specifically, we analyze the fundamental conflict between user-attention-based monetization and agent-driven autonomy through the lens of our gatekeeping theory. We show how AI agents can disintermediate superplatforms and potentially become the next dominant gatekeepers, thereby forming the urgent necessity for superplatforms to proactively constrain and attack AI agents. Moreover, we go through the potential technologies for superplatform-initiated attacks, covering a brand-new, unexplored technical area with unique challenges. We have to emphasize that, despite our position, this paper does not advocate for adversarial attacks by superplatforms on AI agents, but rather offers an envisioned trend to highlight the emerging tensions between superplatforms and AI agents. Our aim is to raise awareness and encourage critical discussion for collaborative solutions, prioritizing user interests and perserving the openness of digital ecosystems in the age of AI agents.

Superplatforms Have to Attack AI Agents

TL;DR

This paper argues that superplatforms risk disintermediation by AI agents and should proactively attack GUI-based agents to preserve gatekeeping and advertising-driven revenue. It applies gatekeeping theory to analyze threats and outlines three strategic countermeasures—proprietary agents, API gating, and proactive adversarial attacks—with a focus on GUI interactions as the hardest to curb. A detailed taxonomy of attack goals, attacker knowledge, visibility, and timing for superplatform-initiated attacks is provided, along with discussion of unique challenges like universal task obstruction and environmental injections. The authors also present alternative views on data moats and potential complementarities, ultimately asserting that, despite ethical cautions, understanding these tensions is essential for safeguarding digital ecosystems in the AI era.

Abstract

Over the past decades, superplatforms, digital companies that integrate a vast range of third-party services and applications into a single, unified ecosystem, have built their fortunes on monopolizing user attention through targeted advertising and algorithmic content curation. Yet the emergence of AI agents driven by large language models (LLMs) threatens to upend this business model. Agents can not only free user attention with autonomy across diverse platforms and therefore bypass the user-attention-based monetization, but might also become the new entrance for digital traffic. Hence, we argue that superplatforms have to attack AI agents to defend their centralized control of digital traffic entrance. Specifically, we analyze the fundamental conflict between user-attention-based monetization and agent-driven autonomy through the lens of our gatekeeping theory. We show how AI agents can disintermediate superplatforms and potentially become the next dominant gatekeepers, thereby forming the urgent necessity for superplatforms to proactively constrain and attack AI agents. Moreover, we go through the potential technologies for superplatform-initiated attacks, covering a brand-new, unexplored technical area with unique challenges. We have to emphasize that, despite our position, this paper does not advocate for adversarial attacks by superplatforms on AI agents, but rather offers an envisioned trend to highlight the emerging tensions between superplatforms and AI agents. Our aim is to raise awareness and encourage critical discussion for collaborative solutions, prioritizing user interests and perserving the openness of digital ecosystems in the age of AI agents.

Paper Structure

This paper contains 31 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Why Superplatforms Have to Attack AI Agents -- Gatekeeping Theory
  3. Threat Analysis with Gatekeeping Theory
  4. Countermeasures Leading to Proactive Adersarial Attack
  5. Development of Proprietary AI Agents
  6. API Gating and Pricing
  7. Proactive Adversarial Attack
  8. How Superplatforms Attack AI Agents -- Taxonomy & Challenges
  9. Attack Goals
  10. Literature Review.
  11. Superplatform-Initiated Attack.
  12. Attacker Knowledge
  13. Literature Review.
  14. Superplatform-Initiated Attack.
  15. Attack Visibility
  16. ...and 16 more sections

Figures (2)

  • Figure 1: The illustration of three paradigms of user interacting with Internet services (i.e., content providers). (a) In the pre-agent age, superplatforms serve as the gatekeeper between the users and content providers. (b) The emerging AI agents intermediate between the users and superplatforms, becoming new gatekeepers. (c) Given the agent-as-gatekeeper fact, content providers can simply bypass superplatforms and offer their Internet services directly to agents.
  • Figure 2: The taxonomy of general adversarial attacks on AI agents, as well as the necessary attributes required by superplatform-initiated attacks.