Start a LoRA fine-tuning job on a base VLA model using a prepared dataset
Part of the Srv D7aoqmh5pdvs7391dcqg server.
Free to start. No card required.
AI agents invoke start_finetune_job to trigger processes or run actions in Srv D7aoqmh5pdvs7391dcqg. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
start_finetune_job can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"start_finetune_job": {
"limits": [
{
"counter": "start_finetune_job_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Srv D7aoqmh5pdvs7391dcqg policy for all 70 tools.
These attack patterns abuse exactly the kind of access start_finetune_job gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Start a LoRA fine-tuning job on a base VLA model using a prepared dataset. It is categorised as a Execute tool in the Srv D7aoqmh5pdvs7391dcqg MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Srv D7aoqmh5pdvs7391dcqg MCP server in PolicyLayer and add a rule for start_finetune_job: 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 Srv D7aoqmh5pdvs7391dcqg. Nothing to install.
start_finetune_job 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 start_finetune_job 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 start_finetune_job. 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.
start_finetune_job is provided by the Srv D7aoqmh5pdvs7391dcqg MCP server (ciprianpater/srv-d7aoqmh5pdvs7391dcqg). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 70 Srv D7aoqmh5pdvs7391dcqg tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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