lake_query
AI agents invoke lake_query to trigger actions in AWS IoT SiteWise MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The name 'lake_query' suggests querying a data lake (likely AWS Lake Formation or similar), which could involve executing arbitrary queries against large datasets. Without a description, it's unclear if it's read-only or can execute destructive SQL. Given the 'query' verb typically implies execution of arbitrary statements, Execute is the most appropriate category. Confidence is lowered due to the empty description.
From the tool's definition Tool name 'lake_query' on an AWS IoT SiteWise MCP server; description is empty and uninformative.
Attacks that exploit this kind of access
lake_query. It is categorised as a Execute tool in the AWS IoT SiteWise MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS IoT SiteWise MCP Server MCP server in PolicyLayer and add a rule for lake_query: 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 AWS IoT SiteWise MCP Server. Nothing to install.
lake_query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the lake_query 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 lake_query. 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.
lake_query is provided by the AWS IoT SiteWise MCP Server MCP server (awslabs.aws-iot-sitewise-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.