Executes arbitrary commands inside a running Docker container and returns structured output. WARNING: may execute untrusted code.
AI agents invoke exec to trigger actions in Http. 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.
This tool executes arbitrary commands with no restrictions mentioned, making it an Execute category risk. The critical severity reflects the extremely high blast radius: an AI agent given this tool could execute any command (including destructive ones like rm -rf, data exfiltration, lateral movement, malware deployment) inside a container.
From the tool's definition Tool description explicitly states 'Executes arbitrary commands inside a running Docker container' and includes warning 'WARNING: may execute untrusted code.'
Documented attack patterns abuse exactly the kind of access exec gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Http, and nothing reaches the server without passing your rules. This is the rule we recommend for exec:
{
"version": "1",
"default": "deny",
"tools": {
"exec": {
"limits": [
{
"counter": "exec_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}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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Executes arbitrary commands inside a running Docker container and returns structured output. WARNING: may execute untrusted code. It is categorised as a Execute tool in the Http MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Http MCP server in PolicyLayer and add a rule for 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 Http. Nothing to install.
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 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 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.
exec is provided by the Http MCP server (@paretools/http). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Http, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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202 Http tools catalogued and risk-classified — across an index of 43,000+ MCP servers.