AI agents invoke gemini_code_exec to trigger actions in Gpal. 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.
The name 'gemini_code_exec' contains 'code_exec', which almost certainly indicates execution of code via the Gemini model. Code execution tools carry high blast radius as an AI agent could run arbitrary code. Confidence is reduced due to the empty description, but the naming convention is a strong signal. Classified as Execute with high severity given the potential for arbitrary code to be run.
From the tool's definition Tool name 'gemini_code_exec' strongly implies code execution; description is empty so cannot confirm scope
Documented attack patterns abuse exactly the kind of access gemini_code_exec gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Gpal, and nothing reaches the server without passing your rules. This is the rule we recommend for gemini_code_exec:
{
"version": "1",
"default": "deny",
"tools": {
"gemini_code_exec": {
"limits": [
{
"counter": "gemini_code_exec_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}gemini_code_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.
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gemini_code_exec. It is categorised as a Execute tool in the Gpal MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Gpal MCP server in PolicyLayer and add a rule for gemini_code_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 Gpal. Nothing to install.
gemini_code_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 gemini_code_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 gemini_code_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.
gemini_code_exec is provided by the Gpal MCP server (tobert/gpal). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Gpal, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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19 Gpal tools catalogued and risk-classified — across an index of 43,000+ MCP servers.