DESTROY: Tear down previously deployed infrastructure Destroys infrastructure by calling the Oracle destroy endpoint for a session that has a prior successful deployment. IMPORTANT: This starts a long-running job. Use tfstatus/tflogs to monitor progress. SINGLE-FLIGHT: only one TF job per session...
Part of the InsideOut (Riley) server.
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AI agents may call tfdestroy to permanently remove or destroy resources in InsideOut (Riley). Without a policy, an autonomous agent could delete critical data in a loop with no way to undo the damage. PolicyLayer blocks destructive tools by default and requires explicit human approval before enabling them.
Without a policy, an AI agent could call tfdestroy in a loop, permanently destroying resources in InsideOut (Riley). There is no undo for destructive operations. PolicyLayer blocks this tool by default and only allows it when a human explicitly approves the action.
Destructive tools permanently remove data. Block by default. Only enable with explicit approval workflows.
{
"version": "1",
"default": "deny",
"hide": [
"tfdestroy"
]
}See the full InsideOut (Riley) policy for all 24 tools.
These attack patterns abuse exactly the kind of access tfdestroy gives an agent. Each links to the full case and the policy that stops it:
Other destructive tools across the catalogue. The same approach applies to each: deny by default, or require human approval.
DESTROY: Tear down previously deployed infrastructure Destroys infrastructure by calling the Oracle destroy endpoint for a session that has a prior successful deployment. IMPORTANT: This starts a long-running job. Use tfstatus/tflogs to monitor progress. SINGLE-FLIGHT: only one TF job per session at a time. If another job is already in flight, tfdestroy returns tf_job_conflict with the live job_id — attach with tfstatus/tflogs, or pass force_new=true to override. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: force_new (boolean, default false) - bypass the single-flight guard. Use only when the existing run is provably wedged. PREREQUISITE: The session must have a prior successful deployment with a project_id. After destroy completes, the session is kept for historical record but hasDeployment is set to false.. It is categorised as a Destructive tool in the InsideOut (Riley) MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the InsideOut (Riley) MCP server in PolicyLayer and add a rule for tfdestroy: 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 InsideOut (Riley). Nothing to install.
tfdestroy 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 tfdestroy 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 tfdestroy. 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.
tfdestroy is provided by the InsideOut (Riley) MCP server (oci:docker.io/luthersystems/insideout-mcp:v0.36.3). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 24 InsideOut (Riley) tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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