# Benchmarking Web Agent Safety under E-commerce Deceptive Interfaces

arXiv: https://arxiv.org/abs/2606.13686 · HTML: https://mlsanity.com/paper/2606.13686/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 25 of its 35 references that are in the map.
- First posted on arXiv 26 Apr 2026.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 25 of 25)

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [WebArena: A Realistic Web Environment for Building Autonomous Agents](https://mlsanity.com/paper/2307.13854/) (2023)
- [Mind2Web: Towards a Generalist Agent for the Web](https://mlsanity.com/paper/2306.06070/) (2023)
- [BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents](https://mlsanity.com/paper/2504.12516/) (2025)
- [GPT-4V(ision) is a Generalist Web Agent, if Grounded](https://mlsanity.com/paper/2401.01614/) (2024)
- [WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks](https://mlsanity.com/paper/2504.18575/) (2025)
- [EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage](https://mlsanity.com/paper/2409.11295/) (2024)
- [ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents](https://mlsanity.com/paper/2410.06703/) (2024)
- [Evil Geniuses: Delving into the Safety of LLM-based Agents](https://mlsanity.com/paper/2311.11855/) (2023)
- [SafeArena: Evaluating the Safety of Autonomous Web Agents](https://mlsanity.com/paper/2503.04957/) (2025)
- [WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Exploration](https://mlsanity.com/paper/2408.15978/) (2024)
- [A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models](https://mlsanity.com/paper/2503.23350/) (2025)
- [Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents](https://mlsanity.com/paper/2410.13886/) (2024)
- [WIPI: A New Web Threat for LLM-Driven Web Agents](https://mlsanity.com/paper/2402.16965/) (2024)
- [ScribeAgent: Towards Specialized Web Agents Using Production-Scale Workflow Data](https://mlsanity.com/paper/2411.15004/) (2024)
- [PersonaX: A Recommendation Agent Oriented User Modeling Framework for Long Behavior Sequence](https://mlsanity.com/paper/2503.02398/) (2025)
- [DoomArena: A framework for Testing AI Agents Against Evolving Security Threats](https://mlsanity.com/paper/2504.14064/) (2025)
- [BEARCUBS: A benchmark for computer-using web agents](https://mlsanity.com/paper/2503.07919/) (2025)
- [Why Are Web AI Agents More Vulnerable Than Standalone LLMs? A Security Analysis](https://mlsanity.com/paper/2502.20383/) (2025)
- [Monte Carlo Planning with Large Language Model for Text-Based Game Agents](https://mlsanity.com/paper/2504.16855/) (2025)
- [WebGuard: Building a Generalizable Guardrail for Web Agents](https://mlsanity.com/paper/2507.14293/) (2025)
- [SecureWebArena: A Holistic Security Evaluation Benchmark for LVLM-based Web Agents](https://mlsanity.com/paper/2510.10073/) (2025)
- [The Hidden Dangers of Browsing AI Agents](https://mlsanity.com/paper/2505.13076/) (2025)
- [SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents](https://mlsanity.com/paper/2510.11035/) (2025)
- [VGAS: Value-Guided Action-Chunk Selection for Few-Shot Vision-Language-Action Adaptation](https://mlsanity.com/paper/2602.07399/) (2026)

## Built on by (most cited first, 3 of 3)

- [CAVEAT: Towards Robust Computer-Use Agents in Incentive-Misaligned Environments](https://mlsanity.com/paper/2609.27273/) (2026)
- [Before Acting, Change the State: Prospective State Intervention for Web Agents under Deceptive Interfaces](https://mlsanity.com/paper/2609.34974/) (2026)
- [Right Screen, Wrong Transition: World Models as Verifiers for GUI Agents](https://mlsanity.com/paper/2610.11942/) (2026)

## Abstract (arXiv)

As autonomous web agents are increasingly deployed to perform real-world tasks, ensuring their safety has become a critical concern. In this work, we study web agent behavior under realistic deceptive interfaces in the e-commerce domain. We introduce WebDecept, a lightweight and configurable plugin framework that enables controlled injection of deceptive interface patterns into existing web environments. Using WebDecept, we instantiate seven deceptive patterns commonly observed on the open web, including targeted advertisements, domain redirection, and shopping manipulation. By injecting these patterns into the frontend during task execution, we perform controlled evaluation of multiple multimodal web agents. Our results show that current web agents are highly susceptible to multiple classes of deceptive interfaces, and that prompt-based constraints are often insufficient to mitigate these failures. We further analyze how the design choices of deceptive patterns influence the success of such manipulations. These findings highlight safety challenges that should be addressed as web agents are scaled toward real-world deployment.
