vet
Runs go vet and returns structured static analysis diagnostics with analyzer names. Uses -json flag for native JSON output with automatic text fallback.
This record as markdown: /tools/io-github-dave-london-docker/vet.md
What vet does on Docker
AI agents invoke vet to trigger actions in Docker. 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 vet is rated High
The tool executes an external command (go vet) which performs static analysis. While read-only in terms of file modification, it runs code/toolchain execution whose effects depend on arguments passed. No data is written or deleted, but it triggers an external process execution, placing it in the Execute category. Severity is medium since misuse could analyze arbitrary code paths or be used to probe codebases.
From the tool's definition 'Runs go vet' — executes a static analysis tool against code using -json flag and automatic text fallback
Attacks that exploit this kind of access
The rule that runs vet safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Docker, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For vet, this is the rule to start with:
vet 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 Docker, apply this rule, and every vet call is checked against it from then on.
Questions about vet
Runs go vet and returns structured static analysis diagnostics with analyzer names. Uses -json flag for native JSON output with automatic text fallback. It is categorised as a Execute tool in the Docker MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Docker MCP server in PolicyLayer and add a rule for vet: 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 Docker. Nothing to install.
vet 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 vet 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 vet. 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.
vet is provided by the Docker MCP server (@paretools/docker). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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