Remove resource from state
AI agents call tf_state_rm to permanently remove resources in Terraform MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Removing resources from Terraform state is an irreversible operation that destroys the mapping between infrastructure code and actual cloud resources. This can lead to orphaned infrastructure, loss of resource tracking, and inability to manage those resources through Terraform again.
From the tool's definition Tool name 'tf_state_rm' and description 'Remove resource from state' indicate irreversible deletion of Terraform state entries.
Attacks that exploit this kind of access
Remove resource from state. It is categorised as a Destructive tool in the Terraform MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Terraform MCP Server MCP server in PolicyLayer and add a rule for tf_state_rm: 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 Terraform MCP Server. Nothing to install.
tf_state_rm is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the tf_state_rm 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 tf_state_rm. 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.
tf_state_rm is provided by the Terraform MCP Server MCP server (mjrestivo16/mcp-terraform). 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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