identity_get_api_key_provider
AI agents call identity_get_api_key_provider to retrieve information from Amazon SageMaker AI MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The 'get' prefix and 'api_key_provider' naming suggest this retrieves or queries API key provider configuration data without modifying it. However, confidence is reduced to 0.6 due to the empty description; if this actually returns sensitive credentials or API keys, the severity could be elevated to medium. The lack of description limits certainty of the actual behavior and potential security implications.
From the tool's definition Tool name contains 'get' which typically indicates a read/retrieval operation for an API key provider. No description provided to confirm intent or scope.
Attacks that exploit this kind of access
identity_get_api_key_provider. It is categorised as a Read tool in the Amazon SageMaker AI MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for identity_get_api_key_provider: 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.
identity_get_api_key_provider is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the identity_get_api_key_provider 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 identity_get_api_key_provider. 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.
identity_get_api_key_provider 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.