Same-Origin Policy for Agentic Browsers
On the map: LLM agents and tool use → Agent threats, guardrails and governance
Abstract (arXiv)
Agentic browsers integrate autonomous AI agents into web browsers, enabling users to accomplish web tasks through natural-language instructions. The same-origin policy (SOP) is a fundamental browser security mechanism that prevents unauthorized automated cross-origin data flows induced by scripts. However, whether SOP remains effective in agentic browsers is an open question that has not been systematically studied. In this work, we bridge this gap. We first observe that an agentic browser can itself serve as an automated channel for cross-origin data flows, potentially leading to SOP violations. To investigate this phenomenon, we construct SOPBench, a benchmark for evaluating SOP violations in agentic browsers. Our evaluation shows that existing agentic browsers frequently violate SOP, both in benign settings and under attacks. To address this problem, we propose SOPGuard, an SOP enforcement mechanism tailored to agentic browsers. We implement SOPGuard in BrowserOS, an open-source agentic browser. Extensive evaluations demonstrate that SOPGuard effectively enforces SOP while preserving utility and incurring only a small runtime overhead. Our code and data are available at https://github.com/wxl-lxw/BrowserOS-SOPGuard.
Key facts. Cited by 1 paper 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 12 of its 32 references that are in the map. First posted on arXiv 12 Jun 2026.
Builds on
12 of 32 references.
Closest ancestors · 8
Same direction, newest first
- 2026WARD: Adversarially Robust Defense of Web Agents Against Prompt Injections14 May
- 2026WebSentinel: Detecting and Localizing Prompt Injection Attacks for Web Agents3 Feb
- 2025WAInjectBench: Benchmarking Prompt Injection Detections for Web Agents1 Oct
- 2025PromptArmor: Simple yet Effective Prompt Injection Defenses21 Jul
- 2025AgentVigil: Generic Black-Box Red-teaming for Indirect Prompt Injection against LLM Agents9 May
- 2025WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks22 Apr
- 2024Attacking Vision-Language Computer Agents via Pop-ups4 Nov
- 2024EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage17 Sep
Other references · 4
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
- 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 563
- 2024VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Taskscited by 47
- 2025BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agentscited by 24
Built on by
Citing papers per year: 2026: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2026Atomicity for Agents: Exposing, Exploiting, and Mitigating TOCTOU Vulnerabilities in Browser-Use Agents
- 2025Building Browser Agents: Architecture, Security, and Practical Solutions
- 2026AgentWall: A Runtime Safety Layer for Local AI Agents
- 2026When Bots Take the Bait: Exposing and Mitigating the Emerging Social Engineering Attack in Web Automation Agent
- 2025The Hidden Dangers of Browsing AI Agents
- 2026From Secure Agentic AI to Secure Agentic Web: Challenges, Threats, and Future Directions
- 2025Building the Web for Agents: A Declarative Framework for Agent-Web Interaction
- 2026Beyond Single-Agent Alignment: Preventing Context-Fragmented Violations in Multi-Agent Systems