Request cancellation for a queued/running job.
AI agents invoke cancelJob to trigger actions in Ltspice. 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.
Cancelling a job triggers an operational side effect (stopping a running or queued simulation/task). It is not a simple read, nor does it delete data, but it executes an action that affects the state of an ongoing process. The blast radius is medium since cancelling a job could abort a needed simulation but is generally recoverable.
From the tool's definition Request cancellation for a queued/running job
Documented attack patterns abuse exactly the kind of access cancelJob gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ltspice, and nothing reaches the server without passing your rules. This is the rule we recommend for cancelJob:
{
"version": "1",
"default": "deny",
"tools": {
"cancelJob": {
"limits": [
{
"counter": "canceljob_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}cancelJob stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Request cancellation for a queued/running job. It is categorised as a Execute tool in the Ltspice MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ltspice MCP server in PolicyLayer and add a rule for cancelJob: 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 Ltspice. Nothing to install.
cancelJob 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 cancelJob 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 cancelJob. 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.
cancelJob is provided by the Ltspice MCP server (xuio/ltspice-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Ltspice, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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