ListAHOConfigurations
AI agents call ListAHOConfigurations 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 'List' prefix universally indicates read-only enumeration of resources. Even without a description, this naming convention maps clearly to the Read category. Severity is low because listing configurations has minimal blast radius—it retrieves metadata without side effects. Confidence is moderate (0.7) due to the missing description, but the verb 'List' is a strong signal.
From the tool's definition Tool name 'ListAHOConfigurations' uses the 'List' verb, which is a read-only retrieval operation. The description is empty, but the naming pattern strongly suggests querying or enumerating AHO (AWS Healthomics) configuration objects without modification.
Attacks that exploit this kind of access
ListAHOConfigurations. 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 ListAHOConfigurations: 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.
ListAHOConfigurations 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 ListAHOConfigurations 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 ListAHOConfigurations. 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.
ListAHOConfigurations 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.