Get random field(s) with their values from hash.
AI agents call hash_random_field_with_values 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.
This tool performs a data retrieval operation (Read category) with minimal risk. It accesses hash fields non-destructively, has no side effects, cannot modify or delete data, and poses low security risk. Low severity reflects that such reads are routine database/cache operations with limited blast radius even if misused.
From the tool's definition Tool name and description: 'Get random field(s) with their values from hash.' This operation retrieves and returns data without modifying, deleting, or executing external operations.
Attacks that exploit this kind of access
Get random field(s) with their values from hash. 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 hash_random_field_with_values: 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.
hash_random_field_with_values 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 hash_random_field_with_values 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 hash_random_field_with_values. 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.
hash_random_field_with_values 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.