Assign an operator to a WhatsApp conversation.
AI agents use assign_operator to create or update resources in WhatsApp MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your WhatsApp MCP Server environment.
An AI agent can call assign_operator faster than any human can review — one bad instruction and it creates or modifies resources in WhatsApp MCP Server by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Assign an operator to a WhatsApp conversation. It is categorised as a Write tool in the WhatsApp MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the WhatsApp MCP Server MCP server in PolicyLayer and add a rule for assign_operator: 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 WhatsApp MCP Server. Nothing to install.
assign_operator is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the assign_operator 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 assign_operator. 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.
assign_operator is provided by the WhatsApp MCP Server MCP server (wati-io/wati-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.