policy_create
AI agents use policy_create to create or update resources in Amazon SageMaker AI MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Amazon SageMaker AI MCP Server environment.
Policy creation is a reversible write operation that modifies authorization state. While not inherently destructive, misconfigured policies can severely impact security posture and system access, warranting high severity. Confidence is moderate (0.7) because the description is empty; the category is inferred from the tool name and server context.
From the tool's definition Tool name 'policy_create' indicates creation of a policy artifact. Given the AWS SageMaker context and sibling tool 'add_inline_policy', this tool likely creates IAM policies or SageMaker resource policies that define permissions or access controls.
Attacks that exploit this kind of access
policy_create. It is categorised as a Write tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for policy_create: 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.
policy_create 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 policy_create 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 policy_create. 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.
policy_create 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.