Undo the last edit operation
AI agents use undo to create or update resources in Ice Puzzle — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ice Puzzle environment.
Undo operations modify data state (the level being edited) but are designed to be safely reversible—the next action can redo what was undone. This distinguishes it from Destructive (irreversible deletion) and makes it Write-class. Severity is low because undoing an edit has minimal blast radius and can be corrected immediately by a redo or further edits.
From the tool's definition Tool name 'undo' and description 'Undo the last edit operation' indicate it reverses the most recent edit to a level design.
Attacks that exploit this kind of access
Undo the last edit operation. It is categorised as a Write tool in the Ice Puzzle MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ice Puzzle MCP server in PolicyLayer and add a rule for undo: 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 Ice Puzzle. Nothing to install.
undo 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 undo 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 undo. 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.
undo is provided by the Ice Puzzle MCP server (wmoten/ice-puzzle-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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