Google Cloud Run MCP — agentic threat model

Not certain from the listing — The foundation model is not specified as this is an MCP server. The primary L1 threat is prompt injection or adversarial reprogramming of the host LLM, forcing it to deploy malicious container images or alter critical service configurations.

Not certain from the listing — No explicit data operations or vector stores are described. However, the agent must handle deployment configurations, environment variables, and potentially secrets, making configuration data exfiltration or tampering a key risk.

The agent framework layer is highly critical here as it exposes MCP tools for Cloud Run deployment. Vulnerabilities include insecure tool integration, where an LLM is tricked into executing deployment commands with malicious parameters or unauthorized container images.

The deployment and infrastructure layer is the core risk surface. The agent interacts directly with GCP APIs; compromised credentials or overly permissive IAM roles could lead to lateral movement, unauthorized container hosting, and severe billing exploitation.

Not certain from the listing — There is no mention of built-in evaluation, guardrails, or logging. Without strict external monitoring and audit logging of the MCP tool calls, unauthorized deployments could go undetected.

Security and compliance rely heavily on the GCP IAM roles assigned to the MCP server. The description notes that confirmation of deploy actions is a key security surface, highlighting the need for Human-In-The-Loop (HITL) controls to prevent unauthorized deployments.

In a multi-agent ecosystem, a compromised orchestrator or secondary agent could exploit this MCP server to deploy malicious workloads, leading to cascading infrastructure compromise across the cloud environment.