AI agents use export_logs to create or update resources in Console — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Console environment.
This tool creates or writes data (log export file) to the Desktop in a reversible manner—the created file can be deleted or overwritten. It does not execute arbitrary code, delete existing data irreversibly, or move money.
From the tool's definition Tool name 'export_logs' and description 'Export logs to a file on the Desktop for sharing' indicate the tool creates/writes a new file with log data to a filesystem location.
Attacks that exploit this kind of access
Export logs to a file on the Desktop for sharing. It is categorised as a Write tool in the Console MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Console MCP server in PolicyLayer and add a rule for export_logs: 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 Console. Nothing to install.
export_logs is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the export_logs 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 export_logs. 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.
export_logs is provided by the Console MCP server (rohithgoud30/console-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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