AI agents use close_connection to create or update resources in Mcp Ssh — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Ssh environment.
An AI agent can call close_connection faster than any human can review — one bad instruction and it creates or modifies resources in Mcp Ssh by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Close the SSH connection to a host. It is categorised as a Write tool in the Mcp Ssh MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mcp Ssh MCP server in PolicyLayer and add a rule for close_connection: 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 Mcp Ssh. Nothing to install.
close_connection is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the close_connection 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 close_connection. 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.
close_connection is provided by the Mcp Ssh MCP server (zhouxiangjing/mcp-ssh). 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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