AI agents use select_kube_context to create or update resources in Kube Lint — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Kube Lint environment.
This tool modifies the active Kubernetes context configuration, affecting all subsequent operations. It writes/updates the current context state rather than just reading it. Misuse could redirect all subsequent kubectl/API calls to an unintended cluster, but it doesn't directly destroy data or move money.
From the tool's definition "Select the Kubernetes context for all subsequent operations"
Attacks that exploit this kind of access
Select the Kubernetes context for all subsequent operations.\n. It is categorised as a Write tool in the Kube Lint MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Kube Lint MCP server in PolicyLayer and add a rule for select_kube_context: 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 Kube Lint. Nothing to install.
select_kube_context 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 select_kube_context 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 select_kube_context. 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.
select_kube_context is provided by the Kube Lint MCP server (sophotechlabs/kube-lint-mcp). 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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