Island Enterprise Browser

Secures application access from unmanaged personal and contractor devices without MDM enrollment or an endpoint agent, enforcing data controls inside the browser session rather than on the device.

Enforces per-application data controls inside the browser session, including copy and paste, download, upload, printing, and screenshot restrictions plus data obfuscation and watermarking of displayed content, without an endpoint agent or in-line traffic decryption.

Renders web content in an isolated execution environment (either locally sandboxed or remotely in a cloud browser) preventing malicious page content from reaching the endpoint OS.

Provides clientless access to internal web applications through a reverse proxy or embedded ZTNA client, replacing VPN for web application access.

Records and stores browser sessions for configured applications for audit, compliance, and insider threat investigation purposes.

Inventories the extensions installed across managed and unmanaged browsers, risk-profiles each one by permissions, publisher, and behavior, and enforces allow, block, or remove policies, so malicious or over-privileged extensions such as credential harvesters and keyloggers cannot run in enterprise sessions.

Extends SSO authentication enforcement to apps that don't support SAML/OIDC natively, using a browser extension to intercept and govern login events for shadow IT and unmanaged SaaS that are invisible to the corporate IdP.

Discovers, risk-scores, and enforces policy on workforce use of AI in the browser, covering GenAI web tools, AI browsing agents, full AI browsers, and AI features inside conventional browsers, including restricting which are allowed and blocking sensitive data from being pasted, uploaded, or acted on by an agent.

Protects web browsing with malware protection and URL filtering.

Collects device posture through the browser, such as OS settings, disk encryption, and installed endpoint protection, and uses it in conditional access decisions for web and SaaS applications, either enforced in the browser itself or exported to the identity provider's access policies.

Inserts an MFA challenge at login or before a sensitive in-app action for any web application, without modifying the application's source code.

Delivers application access that would otherwise need a virtual desktop or desktop-as-a-service session inside the managed browser, including legacy web applications and RDP or SSH delivered workloads, so organizations can reduce VDI and DaaS spend for third-party, contractor, and unmanaged-device access.

Detects and blocks phishing pages and credential theft in the browser, including newly created lookalike domains that reputation blocklists have not yet caught, and prevents enterprise credentials from being entered or reused on unsanctioned external sites.

Hides internal applications from the public internet and unauthorized users, accepting inbound connections only after the trust broker authorizes a named user and device.

Routes web application access through a remote or local isolated browser to prevent malicious content on application pages from reaching the endpoint.

Provides access to browser-based internal applications through a reverse proxy without requiring a device agent, enabling secure access from unmanaged or contractor devices.

Grants access to individual named applications rather than network segments, users and devices can only reach explicitly authorized applications regardless of network position.

Re-evaluates user and device trust signals throughout an active session, revoking or stepping down access when anomalous behavior is detected, not just at authentication time.

Checks endpoint health (OS patch level, EDR presence, disk encryption, certificate validity) at each access request, enforcing minimum device security standards before granting application access.

Brokers authentication, upstream OAuth token injection, and per-tool authorization for AI agents calling internal Model Context Protocol servers through the access proxy.

Discovers and categorizes the organization's use of third-party AI, whether consumed as a service, installed locally, or embedded inside other applications, building a continuously updated inventory of AI usage including shadow AI.

Defines organizational AI usage policies and enforces them at the point of use - allowing, blocking, redirecting, or constraining specific AI services, models, and features per user, group, or data context.

Automatically detects and anonymizes sensitive fields (names, addresses, contact details) inside prompts or pasted content before submission to an AI service, allowing the interaction to proceed with redacted data instead of blocking it outright.

Shows contextual guidance to the user at the moment a risky AI interaction is blocked or modified, explaining why the action was stopped and steering the user toward sanctioned corporate tools, turning enforcement events into awareness moments.

Inspects prompts, uploads, and AI-generated responses for sensitive data across modalities, preventing exposure of regulated or proprietary information to third-party AI services.

Assesses and scores the risk of discovered AI services and embedded AI features (data handling, training-use terms, hosting, vendor posture) to drive sanction/block decisions.

Enforces AI usage controls through multiple local inspection points - browser, endpoint, and network - coordinated from a cloud-delivered control plane, so coverage does not depend on a single interception path.

Discovers MCP servers and AI agent integrations in use, routes agent tool calls through a governed gateway or proxy, and enforces access and data policies on agent-to-tool traffic, extending AI usage control from human prompts to autonomous agent workflows.