AI agents invoke click_element to trigger actions in InSite. 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.
Clicking elements in a browser can trigger a wide range of side effects depending on what is clicked: form submissions, purchases, deletions, navigation, downloads, or any other interactive behavior. The effect is entirely argument-dependent and cannot be categorized as a simple read or write.
From the tool's definition 'Click an element identified by CSS selector' — triggers a browser click action on arbitrary page elements
Attacks that exploit this kind of access
Click an element identified by CSS selector. It is categorised as a Execute tool in the InSite MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the InSite MCP server in PolicyLayer and add a rule for click_element: 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 InSite. Nothing to install.
click_element 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 click_element 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 click_element. 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.
click_element is provided by the InSite MCP server (jowharshamshiri/insite). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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