job_output
Poll recent bounded stdout and stderr from a background job.
This record as markdown: /tools/zebbern-zebbern-kali-mcp/job-output.md
What job_output does on Zebbern Kali MCP
AI agents call job_output to retrieve information from Zebbern Kali MCP without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why job_output is rated Low
Retrieves job output with no side effects, but context of Kali penetration testing toolkit elevates severity.
From the tool's definition Poll recent bounded stdout and stderr from background job.
Attacks that exploit this kind of access
The rule that runs job_output safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Zebbern Kali MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For job_output, this is the rule to start with:
job_output is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Zebbern Kali MCP, apply this rule, and every job_output call is checked against it from then on.
Questions about job_output
Poll recent bounded stdout and stderr from a background job. It is categorised as a Read tool in the Zebbern Kali MCP MCP Server, which means it retrieves data without modifying state.
Register the Zebbern Kali MCP server in PolicyLayer and add a rule for job_output: 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 Zebbern Kali MCP. Nothing to install.
job_output is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the job_output 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 job_output. 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.
job_output is provided by the Zebbern Kali MCP server (zebbern/zebbern-kali-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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