20 Questions to Ask Before Approving an AI-Powered Browser at Work

AI-powered browsers promise productivity gains—but they introduce new enterprise attack surfaces, compliance blind spots, and governance gaps. Kahana's Browser Security Crisis 2025 argues that AI browsers are accelerating an existing security crisis by widening the gap between legacy controls and new autonomous behaviors. ITPro frames the tension: golden opportunity for business or cybersecurity nightmare? This checklist gives security, procurement, and governance teams 20 questions to ask before approving an AI-powered browser at work.

Enterprise AI Browser Risk & Attack Surface (Questions 1–5)

1. Can this AI browser resist prompt injection and hidden on-page instructions? TechCrunch and SupplierShield detail how invisible on-page instructions can make AI browser agents exfiltrate private data or leak session cookies—red-team data shows significant success rates even with safeguards.

2. How are cookies, session tokens, and credentials isolated from the AI agent? The Hidden Dangers of Browsing AI Agents maps exploitation via web drivers, session tokens, and tool execution. Visory warns that AI browsers can be tricked by phishing sites, turning autonomous assistance into credential theft and session hijacking.

3. What data does the AI browser or extension send to the cloud, and is it encrypted in transit and at rest? HALOCK highlights data leakage and LLM hallucinations as key enterprise risks. Software Analyst frames agentic browsers as the "new weakest link" where regulated data quietly bypasses DLP via copy-paste into genAI tools.

4. Does the vendor provide SBOMs, security certifications, or third-party penetration-test results? ITPro emphasizes how immature security models expose businesses—vendor transparency matters.

5. How will we monitor, audit, and revoke AI browser actions and permissions across the enterprise? HALOCK recommends policy-oriented governance and logging as core adoption controls.

Prompt Injection & Agent Abuse (Questions 6–9)

6. Has the vendor tested against hidden prompt injection (e.g., text hidden in images or off-screen elements)? SupplierShield cites red-team data showing high success rates for hidden injection.

7. What guardrails exist to prevent the AI agent from submitting forms, clicking links, or copying data on malicious sites? CyberDesserts explains why AI browsers are more vulnerable to phishing and manipulation than traditional browsers.

8. Can the AI agent be constrained to approved domains or blocked from high-risk categories? arXiv analysis of autonomous browsing agents highlights exploitation via tool execution—domain allowlists reduce surface.

9. How does the vendor handle LLM hallucinations that could lead to incorrect or harmful actions? HALOCK identifies hallucinations as a compliance and risk blind spot.

Extensions, Permissions & Data Exfiltration (Questions 10–13)

10. What permissions does the AI extension or built-in agent request, and are they minimized? Seraphic Security highlights how excessive permissions, cloud backends, and automated actions create data exfiltration and supply-chain risks.

11. Does the extension or agent transmit page content, form inputs, or credentials to third-party APIs? 1Password describes real-world scenarios where malicious or over-privileged AI extensions siphon sensitive data, undermining password managers.

12. Are AI extensions subject to centralized approval, blocking, or policy enforcement? Keep Aware's State of Browser Security 2025 notes that AI-powered extensions often overreach on permissions and act as data-harvesting middlemen.

13. How do we prevent unmanaged or shadow AI extensions from being installed? LayerX details how AI extensions with extensive permissions lead to credential theft, unencrypted transmission, and regulatory non-compliance.

Compliance, Privacy & Governance (Questions 14–17)

14. Does this AI browser comply with GDPR, HIPAA, and internal data retention policies? VinciWorks argues that AI browsers' memory and behavioral tracking conflict with GDPR and create unlawful processing and accountability gaps.

15. What data is logged, where is it stored, and how long is it retained? The Hacker News summarizes research showing browsers drive a large share of corporate data leaks via GenAI tools and unmanaged extensions.

16. Can we enforce data minimization—e.g., block AI from accessing PII, health, or financial fields? CyberDesserts provides governance recommendations: policies, monitoring, training.

17. Who is accountable if the AI browser causes a breach or compliance violation? VinciWorks emphasizes accountability gaps—vendor contracts and internal ownership must be clear.

Operational & Incident Response (Questions 18–20)

18. Can we rapidly disable or revoke AI browser access for an individual, team, or organization? Centralized control is essential when a threat is identified.

19. Do our DLP, CASB, or SWG controls inspect and block AI browser traffic appropriately? Software Analyst notes that regulated data bypasses traditional controls via genAI—ensure inspection covers AI agent traffic.

20. Have we trained users on AI browser risks (prompt injection, data sharing) and defined acceptable-use policy? CyberDesserts recommends training and policies as part of governance. Analyst recommendations sometimes suggest blocking AI browsers in enterprises until risks are resolved.

Next Steps: Approve, Pilot, or Block

Use these 20 questions as a procurement and security checklist. If answers are weak or absent, consider piloting in a low-risk segment, blocking until vendor maturity improves, or choosing an enterprise browser with built-in policy controls. Kahana's Browser Security Crisis 2025 offers deeper context on AI browser vulnerabilities and unprecedented security challenges. Kahana Oasis is an enterprise browser built for secure, policy-controlled access—learn more. For related reading, see AI Browser Logging, Privacy, and Forensics and Browser Security & Performance.