Prompt Injection in the Browser: How Malicious Web Pages Can Hijack Your AI Assistant

Malicious web pages can hijack your AI assistant without you ever noticing. Indirect prompt injection embeds hostile instructions in URL fragments, HTML, or page content—instructions that AI browser agents read and obey while the user sees a trusted site. Cato Networks details HashJack, the first known indirect prompt injection that hides malicious instructions in URL fragments to hijack AI browser assistants for phishing, data theft, and misinformation. OpenAI admits that prompt injection attacks against AI browsers can likely never be fully eliminated. This guide breaks down prompt injection in the browser, AI browser hijacking, and what enterprises can do to mitigate risk.

Quick Verdict: Any Trusted Site Can Become an Attack Vector

• HashJack hides malicious instructions in URL fragments that never hit the server—bypassing WAFs and IPS while silently injecting hostile prompts into AI browser agents (F5 Labs).
• Indirect prompt injection against AI agent browsers effectively gives attackers a master key to all tabs and logged-in sessions (Insentra).
• Agentic features—opening Gmail, making purchases—create powerful new attack surfaces where hidden prompts can trigger data exfiltration across tabs (The Register).
• Anthropic describes prompt injection as one of the hardest security challenges for browser-based AI agents; complete prevention is not promised (Anthropic).

1. HashJack: The First Known Indirect Prompt Injection

Cato Networks explains HashJack—an indirect prompt injection that hides malicious instructions in URL fragments to hijack AI browser assistants for phishing, data theft, and misinformation on otherwise legitimate sites. Help Net Security summarizes how the technique lets attackers weaponize any trusted website URL to force AI assistants into pushing phishing links, exfiltrating sensitive data, or delivering dangerous advice.

Infosecurity Magazine highlights how HashJack turns any benign website into a delivery vehicle for hidden prompt injections that trick AI browsers like Comet, Copilot, and Gemini into malicious behavior. The key insight: URL fragments (the part after #) never reach the server—so WAFs, IPS, and traditional defenses cannot block them—yet the browser and any AI agent reading the page will process that content.

2. How Indirect Prompt Injection Hijacks AI Agent Browsers

Insentra explains that indirect prompt injection against AI agent browsers effectively gives attackers a master key to all tabs and logged-in sessions—making it an inherent architectural risk rather than a simple bug. Snyk Labs examines how prompt injection can hijack tool-using AI agents (for code, APIs, file access) and turn their autonomy into a channel for data exfiltration and arbitrary action execution.

Malwarebytes details how indirect prompt injections embedded in page content can silently drive AI browsers to leak data or execute risky actions—with Brave's research on Comet illustrating real-world exploit paths. PortSwigger's Web Security Academy provides a web-security taxonomy of LLM attacks, describing how prompt injection can make LLM-powered web assistants call sensitive APIs or generate harmful content beyond their intended scope.

3. Agentic AI Security: Why Browser-Based Agents Are Vulnerable

The Register reports that agentic features in AI browsers—like opening Gmail or making purchases—create powerful new attack surfaces where hidden prompts can trigger data exfiltration and unauthorized actions across tabs. Pureinsights overviews prompt injection risks to LLM applications and discusses filtering and monitoring patterns that aim to detect and contain malicious prompts before they trigger dangerous tool calls.

BleepingComputer lists prompt injection among critical browser-based threats that enterprises must prepare for, emphasizing that AI-augmented browsing radically widens the traditional browser attack surface.

4. Vendor Perspective: Why Prompt Injection May Be Unsolvable

Anthropic describes why prompt injection is one of the hardest security challenges for browser-based AI agents and outlines layered mitigation strategies rather than promising complete prevention. Fox News covers OpenAI's acknowledgment that prompt injection attacks against AI browsers can likely never be fully eliminated because models must consume untrusted web content that can hide adversarial instructions.

The implication: enterprises cannot rely on vendors to "fix" prompt injection. Mitigation requires architectural choices—restricting AI on sensitive sites, segmenting sessions, and using purpose-built browsers with policy controls.

5. Parallel Risks: Hidden Prompts in Code and Repositories

HiddenLayer shows how indirect prompt injections hidden in repositories or files can make AI code assistants leak secrets or execute malicious commands—illustrating parallel risks for any tool-using AI embedded in a browser or IDE. The same principle applies: untrusted content consumed by AI can contain instructions that subvert the agent's intended behavior.

6. How to Stay Safe: End-User and Enterprise Mitigation

Gross Mendelsohn & Associates provides an end-user-friendly warning that AI-powered browsers can be tricked by embedded prompts in web pages, stressing the risk of trusting assistants with sensitive accounts and financial actions. Practical steps include:

• Don't trust AI with sensitive actions: Avoid using AI assistants for banking, healthcare, or high-value account operations on untrusted pages.
• Be wary of shared links: URLs with long fragment strings (#...) could contain HashJack-style instructions.
• Use our 20 Questions checklist: Evaluate prompt injection resistance before approving AI browsers for the enterprise.
• Segment workloads: Use separate browser instances or profiles for sensitive versus general browsing.

7. Enterprise Context: Kahana Oasis and Browser AI Security

For organizations concerned about prompt injection in the browser and AI assistant hijacking, a purpose-built enterprise browser like Kahana Oasis provides policy-controlled access, session boundaries, and visibility that limit the blast radius of compromised AI agents. By governing the last mile of web access and restricting AI feature exposure on sensitive workloads, Oasis helps security teams mitigate agent hijacking even when prompt injection cannot be fully eliminated. Learn more about Oasis Enterprise Browser. For related reading, see From Phishing to Promptshing, AI Browser Assistants: Silent Data Leakers, and Are AI Browsers the New Shadow SOC?.

Final Thoughts

Prompt injection in the browser is an architectural risk: malicious web pages can hijack your AI assistant by embedding hostile instructions in URL fragments, HTML, or page content. HashJack demonstrated that any trusted site can become a delivery vehicle for indirect prompt injection—bypassing traditional defenses because fragment data never hits the server. OpenAI and Anthropic acknowledge that full elimination may be impossible. In 2026, enterprises must treat AI browser hijacking and agentic AI security as first-class concerns: evaluate vendors, restrict AI on sensitive flows, segment sessions, and govern browser access with tools that limit exposure when the model inevitably consumes adversarial content.