Medium Risk

apply_app_version

Start deploying an existing app at a specific version. Use the 'version' value (not 'name') from get_app_versions. Returns true if accepted and deployment started; use get_app_status to observe completion.

Part of the AppDeploy server.

apply_app_version can modify AppDeploy data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use apply_app_version to create or modify resources in AppDeploy. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call apply_app_version repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach AppDeploy.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

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

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These attack patterns abuse exactly the kind of access apply_app_version gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so apply_app_version only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the apply_app_version tool do? +

Start deploying an existing app at a specific version. Use the 'version' value (not 'name') from get_app_versions. Returns true if accepted and deployment started; use get_app_status to observe completion.. It is categorised as a Write tool in the AppDeploy MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on apply_app_version? +

Register the AppDeploy MCP server in PolicyLayer and add a rule for apply_app_version: 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 AppDeploy. Nothing to install.

What risk level is apply_app_version? +

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

Can I rate-limit apply_app_version? +

Yes. Add a rate_limit block to the apply_app_version 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 apply_app_version completely? +

Set action: deny in the PolicyLayer policy for apply_app_version. 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 apply_app_version? +

apply_app_version is provided by the AppDeploy MCP server (appdeploy/deploy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AppDeploy tool call.

Deterministic rules across all 11 AppDeploy tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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