delete_instance_in_series
AI agents call delete_instance_in_series to permanently remove resources in Amazon SageMaker AI MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The tool performs a delete operation on what appears to be a SageMaker instance or similar AWS resource. Delete operations are inherently destructive and irreversible. While the empty description limits full certainty, the explicit 'delete' verb in a cloud infrastructure context (SageMaker) indicates this belongs in the Destructive category rather than Write.
From the tool's definition Tool name 'delete_instance_in_series' contains 'delete', which indicates irreversible removal of data or resources.
Attacks that exploit this kind of access
delete_instance_in_series. It is categorised as a Destructive tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for delete_instance_in_series: 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 Amazon SageMaker AI MCP Server. Nothing to install.
delete_instance_in_series is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the delete_instance_in_series 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 delete_instance_in_series. 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.
delete_instance_in_series is provided by the Amazon SageMaker AI MCP Server MCP server (awslabs.sagemaker-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.