페이지 컨텍스트에서 JS 표현식 실행 후 결과 반환.
AI agents invoke web_evaluate to trigger actions in K-Personal MCP. 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.
This tool runs arbitrary JavaScript in a browser page context, which constitutes code execution. An AI agent could misuse it to exfiltrate data, manipulate the DOM maliciously, interact with web APIs, or perform other operations depending on the arguments passed. This places it firmly in the Execute category with high severity due to the broad blast radius of arbitrary JS execution.
From the tool's definition 'JS 표현식 실행' — executes JavaScript expressions in the page context and returns the result
Attacks that exploit this kind of access
페이지 컨텍스트에서 JS 표현식 실행 후 결과 반환. It is categorised as a Execute tool in the K-Personal MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the K-Personal MCP server in PolicyLayer and add a rule for web_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 K-Personal MCP. Nothing to install.
web_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 web_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 web_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.
web_evaluate is provided by the K-Personal MCP server (lee30934-byte/k-personal-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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