Prismata: Confining Cross-Site Prompt Injection in Web Agents
On the map: LLM agents and tool use → Agent threats, guardrails and governance
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Abstract (arXiv)
Autonomous web agents promise to automate everyday browsing tasks, but inherit one of the web's oldest attack surfaces. Cross-Site Scripting proved that mixing trusted and untrusted content is dangerous, even on benign pages. Agents resurface this risk by interpreting natural language as instructions, allowing third-party and user-generated content to hijack the agent via prompt injection. The core challenge is that deriving a task-specific security policy requires reasoning over page structure that is entangled with the attacker's content. We present Prismata, a defense enforcing contextual least privilege for web agents, constraining both what the agent sees and what it can do. Prismata's dynamic trust derivation produces permission labels for page content, with structural confinement guarantees, inspired by classical integrity models, that bound any labeling errors so that labels can only decrease in privilege and mislabelings are bounded. Prismata's mechanical confinement enforces these labels by redacting content and restricting agent capabilities. Importantly, these mechanisms require no developer annotations, so Prismata supports the long tail of websites. Across recent published web agent attacks, including adaptive variants, Prismata substantially reduces attack success while preserving benign task utility.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 48 of its 94 references that are in the map. First posted on arXiv 9 Jul 2026.
Builds on
48 of 94 references.
Closest ancestors · 20
Same direction, newest first
- 2026WebAgentGuard: A Reasoning-Driven Guard Model for Detecting Prompt Injection Attacks in Web Agents14 Apr
- 2026The Cognitive Firewall:Securing Browser Based AI Agents Against Indirect Prompt Injection Via Hybrid Edge Cloud Defense24 Mar
- 2026MUZZLE: Adaptive Agentic Red-Teaming of Web Agents Against Indirect Prompt Injection Attacks9 Feb
- 2026WebSentinel: Detecting and Localizing Prompt Injection Attacks for Web Agents3 Feb
- 2026When Bots Take the Bait: Exposing and Mitigating the Emerging Social Engineering Attack in Web Automation Agent12 Jan
- 2025RL Is a Hammer and LLMs Are Nails: A Simple Reinforcement Learning Recipe for Strong Prompt Injection6 Oct
- 2025AgentSentinel: An End-to-End and Real-Time Security Defense Framework for Computer-Use Agents9 Sep
- 2025Security Challenges in AI Agent Deployment: Insights from a Large Scale Public Competition28 Jul
- 2025WebGuard: Building a Generalizable Guardrail for Web Agents18 Jul
- 2025Design Patterns for Securing LLM Agents against Prompt Injections10 Jun
- 2025AdInject: Real-World Black-Box Attacks on Web Agents via Advertising Delivery27 May
- 2025Prompt Injection Attack to Tool Selection in LLM Agents28 Apr
8 more
- 2025WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks22 Apr
- 2025In-Context Defense in Computer Agents: An Empirical Study12 Mar
- 2025Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents27 Feb
- 2025RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage13 Feb
- 2024Attacking Vision-Language Computer Agents via Pop-ups4 Nov
- 2024AdvAgent: Controllable Blackbox Red-teaming on Web Agents22 Oct
- 2024When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs18 Oct
- 2024EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage17 Sep
Other references · 28
- 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 2,914
- 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,339
- 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,210
- 2022Ignore Previous Prompt: Attack Techniques For Language Modelscited by 760
- 2024The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructionscited by 441
- 2023FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Promptscited by 368
- 2024WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?cited by 348
- 2024Agent Workflow Memorycited by 342
- 2024StruQ: Defending Against Prompt Injection with Structured Queriescited by 325
- 2024TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Taskscited by 306
- 2025DataSentinel: A Game-Theoretic Detection of Prompt Injection Attackscited by 124
- 2025Securing AI Agents with Information-Flow Controlcited by 108
16 more
- 2025The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injectionscited by 108
- 2024WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Explorationcited by 100
- 2024System-Level Defense against Indirect Prompt Injection Attacks: An Information Flow Control Perspectivecited by 91
- 2018Tranco: A Research-Oriented Top Sites Ranking Hardened Against Manipulationcited by 61
- 2024Caution for the Environment: Multimodal LLM Agents are Susceptible to Environmental Distractionscited by 55
- 2025Contextual Agent Security: A Policy for Every Purposecited by 55
- 2024Proposer-Agent-Evaluator(PAE): Autonomous Skill Discovery For Foundation Model Internet Agentscited by 50
- 2025Towards Enterprise-Ready Computer Using Generalist Agentcited by 31
- 2025A Critical Evaluation of Defenses against Prompt Injection Attackscited by 31
- 2025BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agentscited by 23
- 2025LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection Challengecited by 20
- 2025ceLLMate: Sandboxing Browser AI Agentscited by 14
- 2025How Not to Detect Prompt Injections with an LLMcited by 11
- 2025Con Instruction: Universal Jailbreaking of Multimodal Large Language Models via Non-Textual Modalitiescited by 6
- 2025When AI Meets the Web: Prompt Injection Risks in Third-Party AI Chatbot Pluginscited by 6
- 2018Tracing Information Flows Between Ad Exchanges Using Retargeted Adscited by 1
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Citing papers per year: 2026: 1.
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- 2026WARD: Adversarially Robust Defense of Web Agents Against Prompt Injections
- 2026From Secure Agentic AI to Secure Agentic Web: Challenges, Threats, and Future Directions
- 2025The Hidden Dangers of Browsing AI Agents
- 2026Atomicity for Agents: Exposing, Exploiting, and Mitigating TOCTOU Vulnerabilities in Browser-Use Agents
- 2026Out of Sight: Compression-Aware Content Protection against Agentic Crawlers