Run isolated code in a BlockRun-hosted Modal sandbox \u2014 disposable remote container, optional GPU. Use when you need: a clean ephemeral environment, GPU access (T4/L4/A10G/A100/A100-80GB/H100), or a safer place for untrusted code. Prefer local tools for normal repo work. Common paths (all POS...
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AI agents invoke blockrun_modal to trigger processes or run actions in Blockrun. 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.
blockrun_modal 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": {
"blockrun_modal": {
"limits": [
{
"counter": "blockrun_modal_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Blockrun policy for all 16 tools.
These attack patterns abuse exactly the kind of access blockrun_modal 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.
Run isolated code in a BlockRun-hosted Modal sandbox \u2014 disposable remote container, optional GPU. Use when you need: a clean ephemeral environment, GPU access (T4/L4/A10G/A100/A100-80GB/H100), or a safer place for untrusted code. Prefer local tools for normal repo work. Common paths (all POST): - sandbox/create \u2014 body: { image?, timeout?, cpu?, memory?, gpu?, setup_commands? } ($0.01) - sandbox/exec \u2014 body: { sandbox_id, command: [. It is categorised as a Execute tool in the Blockrun MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Blockrun MCP server in PolicyLayer and add a rule for blockrun_modal: 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 Blockrun. Nothing to install.
blockrun_modal 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 blockrun_modal 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 blockrun_modal. 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.
blockrun_modal is provided by the Blockrun MCP server (@blockrun/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 16 Blockrun tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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