AI agents use update_platform_target to create or update resources in AdButler — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AdButler environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
id | number | Yes | Platform target ID |
name | string | — | Platform target name |
platform | string | — | Preset platform target |
device_targets | array | — | List of device patterns to target |
Parameters from the server's own tool schema.
This tool modifies advertising platform targeting configuration, which affects ad campaigns and delivery. The update is reversible (data can be modified again), placing it in Write rather than Destructive. Severity is medium because misconfiguration could affect ad delivery and campaign performance, but does not involve deletion, financial transactions, or code execution.
From the tool's definition Tool name 'update_platform_target' and description 'Update an existing platform target' indicate modification of existing data. The verb 'update' is a classic Write operation that creates or modifies data reversibly.
Attacks that exploit this kind of access
Update an existing platform target. It is categorised as a Write tool in the AdButler MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_platform_target accepts 4 parameters: id, name, platform, device_targets. Required: id. The full parameter table on this page comes from the server's own tool schema.
Register the AdButler MCP server in PolicyLayer and add a rule for update_platform_target: 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 AdButler. Nothing to install.
update_platform_target 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 update_platform_target 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 update_platform_target. 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.
update_platform_target is provided by the AdButler MCP server (adbutler/mcp-server). 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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