Medium Risk

lock_release

Release a lock you are holding.

How to control lock_release ↓

What lock_release does on Agent Orchestration

AI agents use lock_release to create or update resources in Agent Orchestration — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Agent Orchestration environment.

Medium Risk

Why lock_release needs a policy

This tool modifies the state of locks in the agent coordination system, enabling or disabling access to shared resources. While reversible (the lock can be re-acquired), misuse could cause coordination failures, resource contention, or task deadlocks across multiple agents. It is not Destructive because the action is reversible and the lock state can be restored.

From the tool's definition Tool name 'lock_release' and description 'Release a lock you are holding' indicates modification of lock state in a shared coordination system. This reverses a previous lock acquisition action.

Documented attack patterns abuse exactly the kind of access lock_release gives an agent:

How to control lock_release

PolicyLayer is an MCP gateway — it sits between your AI agents and Agent Orchestration, and nothing reaches the server without passing your rules. This is the rule we recommend for lock_release:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "lock_release": {
      "limits": [
        {
          "counter": "lock_release_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

lock_release 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.

  1. Create a free account and register Agent Orchestration — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about lock_release

What does the lock_release tool do? +

Release a lock you are holding. It is categorised as a Write tool in the Agent Orchestration MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on lock_release? +

Register the Agent Orchestration MCP server in PolicyLayer and add a rule for lock_release: 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 Agent Orchestration. Nothing to install.

What risk level is lock_release? +

lock_release is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit lock_release? +

Yes. Add a rate_limit block to the lock_release 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.

How do I block lock_release completely? +

Set action: deny in the PolicyLayer policy for lock_release. 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.

What MCP server provides lock_release? +

lock_release is provided by the Agent Orchestration MCP server (madebyaris/agent-orchestration). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agent Orchestration tool call.

Start from Agent Orchestration, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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