browser_evaluate
AI agents invoke browser_evaluate to trigger actions in AWS IoT SiteWise MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The name 'browser_evaluate' is consistent with browser automation APIs that execute arbitrary JavaScript in a browser page. This would be an Execute-category action with critical severity due to arbitrary code execution potential. Confidence is reduced because the description is empty, leaving the exact behavior unconfirmed.
From the tool's definition Tool name 'browser_evaluate' strongly implies executing JavaScript or code in a browser context, similar to browser automation evaluate functions (e.g., Playwright's page.evaluate)
Attacks that exploit this kind of access
browser_evaluate. It is categorised as a Execute tool in the AWS IoT SiteWise MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS IoT SiteWise MCP Server MCP server in PolicyLayer and add a rule for browser_evaluate: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AWS IoT SiteWise MCP Server. Nothing to install.
browser_evaluate is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the browser_evaluate rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for browser_evaluate. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
browser_evaluate is provided by the AWS IoT SiteWise MCP Server MCP server (awslabs.aws-iot-sitewise-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.