sandbox_exec
Execute a shell command inside a sandbox. Returns stdout, stderr, exitCode, durationMs. Default timeout 60s, max 600s.
This record as markdown: /tools/cloud-easybits-easybits/sandbox-exec.md
What sandbox_exec does on EasyBits
AI agents invoke sandbox_exec to trigger actions in EasyBits. 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.
Why sandbox_exec is rated High
Arbitrary shell command execution with full output access enables complete system compromise and data exfiltration.
From the tool's definition Execute a shell command inside a sandbox. Returns stdout, stderr, exitCode.
Attacks that exploit this kind of access
The rule that runs sandbox_exec safely
PolicyLayer is an MCP gateway: it sits between your AI agents and EasyBits, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For sandbox_exec, this is the rule to start with:
sandbox_exec 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.
The button opens the PolicyLayer dashboard: create your workspace, connect EasyBits, apply this rule, and every sandbox_exec call is checked against it from then on.
Questions about sandbox_exec
Execute a shell command inside a sandbox. Returns stdout, stderr, exitCode, durationMs. Default timeout 60s, max 600s. It is categorised as a Execute tool in the EasyBits MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the EasyBits MCP server in PolicyLayer and add a rule for sandbox_exec: 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 EasyBits. Nothing to install.
sandbox_exec 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 sandbox_exec 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 sandbox_exec. 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.
sandbox_exec is provided by the EasyBits MCP server (@easybits.cloud/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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