revoke_sandbox_execution
Manually revoke (terminate) a running sandboxed execution.
This record as markdown: /tools/todo-for-ai-todo-for-ai-mcp/revoke-sandbox-execution.md
What revoke_sandbox_execution does on Todo for AI MCP Server
AI agents call revoke_sandbox_execution to permanently remove resources in Todo for AI MCP Server, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why revoke_sandbox_execution is rated Critical
An AI agent that decides to call revoke_sandbox_execution doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Todo for AI MCP Server is gone. There is no undo for destructive operations.
Attacks that exploit this kind of access
The rule that runs revoke_sandbox_execution safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Todo for AI MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For revoke_sandbox_execution, this is the rule to start with:
revoke_sandbox_execution is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Todo for AI MCP Server, apply this rule, and every revoke_sandbox_execution call is checked against it from then on.
Questions about revoke_sandbox_execution
Manually revoke (terminate) a running sandboxed execution. It is categorised as a Destructive tool in the Todo for AI MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Todo for AI MCP Server MCP server in PolicyLayer and add a rule for revoke_sandbox_execution: 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 Todo for AI MCP Server. Nothing to install.
revoke_sandbox_execution is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the revoke_sandbox_execution 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 revoke_sandbox_execution. 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.
revoke_sandbox_execution is provided by the Todo for AI MCP Server MCP server (todo-for-ai/todo-for-ai-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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