AI agents invoke gcloud_run_trigger to trigger actions in Gcloud. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool executes a build process in Google Cloud, which runs code and triggers external operations. While not immediately destructive or financial, it has significant blast radius: a malicious agent could trigger resource-intensive builds, consume quotas, incur costs, or deploy malicious code.
From the tool's definition Tool description explicitly states 'Manually trigger a Cloud Build' and warns 'This creates a new build — use with care.' The tool initiates external operations (build execution) whose effects depend on which trigger/build configuration is invoked.
Attacks that exploit this kind of access
Manually trigger a Cloud Build. Returns the build ID of the triggered build. WARNING: This creates a new build — use with care. It is categorised as a Execute tool in the Gcloud MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Gcloud MCP server in PolicyLayer and add a rule for gcloud_run_trigger: 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 Gcloud. Nothing to install.
gcloud_run_trigger is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the gcloud_run_trigger 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 gcloud_run_trigger. 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.
gcloud_run_trigger is provided by the Gcloud MCP server (prmichaelsen/gcloud-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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