Connect to SSH server using saved credentials
AI agents invoke ssh_connect_with_credential to trigger actions in SSH MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool establishes an SSH connection to a remote server, which triggers an external operation (network connection) and opens a channel through which arbitrary remote commands could subsequently be executed.
From the tool's definition Connect to SSH server using saved credentials
Attacks that exploit this kind of access
Connect to SSH server using saved credentials. It is categorised as a Execute tool in the SSH MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the SSH MCP Server MCP server in PolicyLayer and add a rule for ssh_connect_with_credential: 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 SSH MCP Server. Nothing to install.
ssh_connect_with_credential is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the ssh_connect_with_credential 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 ssh_connect_with_credential. 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.
ssh_connect_with_credential is provided by the SSH MCP Server MCP server (widjis/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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