Lock actor transforms to prevent accidental movement.
AI agents use actor_lock to create or update resources in Uefn — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Uefn environment.
This tool modifies actor properties in the UEFN editor by applying a lock constraint. While it prevents further movement, the lock itself can be reversed (via actor_unlock, a sibling tool), making it Write rather than Destructive. Severity is medium because misuse could disrupt editor workflow by locking actors an AI agent shouldn't, but the effect is recoverable.
From the tool's definition Tool description: 'Lock actor transforms to prevent accidental movement.' The tool modifies actor state (applying a transform lock), which is a reversible data change to the editor state.
Documented attack patterns abuse exactly the kind of access actor_lock gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Uefn, and nothing reaches the server without passing your rules. This is the rule we recommend for actor_lock:
{
"version": "1",
"default": "deny",
"tools": {
"actor_lock": {
"limits": [
{
"counter": "actor_lock_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}actor_lock stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Lock actor transforms to prevent accidental movement. It is categorised as a Write tool in the Uefn MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Uefn MCP server in PolicyLayer and add a rule for actor_lock: 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 Uefn. Nothing to install.
actor_lock 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 actor_lock 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 actor_lock. 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.
actor_lock is provided by the Uefn MCP server (quangdang46/uefn-verse-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Uefn, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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