Medium Risk

update_project_settings

Update project-level settings: merge strategy (merge/rebase/fast-forward), squash policy, pipeline requirements, source branch cleanup, Auto DevOps, shared runners, and container registry

Part of the GitLab Operations server.

update_project_settings can modify GitLab Operations 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 update_project_settings to create or modify resources in GitLab Operations. 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 update_project_settings 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 GitLab Operations.

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

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

See the full GitLab Operations policy for all 22 tools.

Get this rule live on your own GitLab Operations server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access update_project_settings 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 update_project_settings 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 update_project_settings tool do? +

Update project-level settings: merge strategy (merge/rebase/fast-forward), squash policy, pipeline requirements, source branch cleanup, Auto DevOps, shared runners, and container registry. It is categorised as a Write tool in the GitLab Operations MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_project_settings? +

Register the GitLab Operations MCP server in PolicyLayer and add a rule for update_project_settings: 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 GitLab Operations. Nothing to install.

What risk level is update_project_settings? +

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

Can I rate-limit update_project_settings? +

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

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

update_project_settings is provided by the GitLab Operations MCP server (jarecsni/gitlab-ops-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every GitLab Operations tool call.

Deterministic rules across all 22 GitLab Operations tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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