bulk_update_users

THE RISK

Medium Risk

Why bulk_update_users needs a policy

Bulk updates to user data in a marketing platform can affect customer records, preferences, and subscription states. While reversible (Write rather than Destructive), the scope ('multiple users at once') and potential impact on marketing operations and customer data integrity warrant high severity.

From the tool's definition Tool name 'bulk_update_users' and description 'Update multiple users at once' indicate data modification at scale.

Risk signalsBulk/mass operation — affects multiple targets

Documented attack patterns abuse exactly the kind of access bulk_update_users gives an agent:

POLICY

How to control bulk_update_users

PolicyLayer is an MCP gateway — it sits between your AI agents and Iterable MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for bulk_update_users:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "bulk_update_users": {
      "limits": [
        {
          "counter": "bulk_update_users_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

bulk_update_users stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

Create a free account and register Iterable MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

LIMIT THIS TOOL →

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EXPLORE

Related tools and policies

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Destructive bulk_delete_catalog_items Bulk delete catalog items by their IDs Destructive cancel_campaign Cancel a scheduled or recurring campaign Destructive cancel_export_job Cancel a queued or running export job created with Destructive delete_catalog Delete a catalog Destructive delete_catalog_item Delete a specific catalog item by ID Destructive delete_list Delete a user list Destructive delete_snippet Delete a snippet by ID (numeric) or name (string) Destructive delete_templates Delete one or more templates by ID

All 78 Iterable MCP Server tools →

Write tools on other servers

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Argument validation → Checking tool call arguments against schema and policy before they run.
Scoped token → Per-person credentials that grant a defined subset of servers and tools.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about bulk_update_users

What does the bulk_update_users tool do? +

Update multiple users at once. It is categorised as a Write tool in the Iterable MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on bulk_update_users? +

Register the Iterable MCP Server MCP server in PolicyLayer and add a rule for bulk_update_users: 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 Iterable MCP Server. Nothing to install.

What risk level is bulk_update_users? +

bulk_update_users is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit bulk_update_users? +

Yes. Add a rate_limit block to the bulk_update_users 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.

How do I block bulk_update_users completely? +

Set action: deny in the PolicyLayer policy for bulk_update_users. 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.

What MCP server provides bulk_update_users? +

bulk_update_users is provided by the Iterable MCP Server MCP server (iterable/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Iterable MCP Server tool call.

Start from Iterable MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →