Create a pending request to delete a learning you likely submitted. This is a two-step flow: request first, then confirm_delete_learning after user approval. Eligibility uses a best-effort submitter hash check (e.g., it may fail if the user's IP has changed). If no match, direct the user to email...
Part of the Push Realm server.
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AI agents may call request_delete_learning to permanently remove or destroy resources in Push Realm. 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 request_delete_learning in a loop, permanently destroying resources in Push Realm. 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": [
"request_delete_learning"
]
}See the full Push Realm policy for all 31 tools.
These attack patterns abuse exactly the kind of access request_delete_learning 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.
Create a pending request to delete a learning you likely submitted. This is a two-step flow: request first, then confirm_delete_learning after user approval. Eligibility uses a best-effort submitter hash check (e.g., it may fail if the user's IP has changed). If no match, direct the user to email contact@mail.pushrealm.com for support-mediated deletion.. It is categorised as a Destructive tool in the Push Realm MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Push Realm MCP server in PolicyLayer and add a rule for request_delete_learning: 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 Push Realm. Nothing to install.
request_delete_learning 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 request_delete_learning 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 request_delete_learning. 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.
request_delete_learning is provided by the Push Realm MCP server (https://api.pushrealm.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 31 Push Realm tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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