GetAHORunEngineLogs
AI agents call GetAHORunEngineLogs 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 tool appears to retrieve or query logs from the AHO (Automated Hypothesis Optimization) run engine, which is a read-only operation with no side effects. Without a description, confidence is moderated, but the naming pattern is consistent with data retrieval tools. The potential blast radius of accidentally exposing logs is limited compared to write, execute, or destructive operations.
From the tool's definition Tool name 'GetAHORunEngineLogs' contains the verb 'Get', which indicates data retrieval. The description is empty, limiting confidence, but the semantic meaning of 'Get' combined with 'Logs' suggests fetching existing log data without modification.
Attacks that exploit this kind of access
GetAHORunEngineLogs. 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 GetAHORunEngineLogs: 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.
GetAHORunEngineLogs 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 GetAHORunEngineLogs 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 GetAHORunEngineLogs. 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.
GetAHORunEngineLogs 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.