audit
Runs cargo audit and returns structured vulnerability data.
This record as markdown: /tools/io-github-dave-london-docker/audit.md
What audit does on Docker
AI agents invoke audit 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 audit is rated High
The tool runs an external command (cargo audit) on the system, making it an Execute category. While cargo audit is read-only in intent (scanning for vulnerabilities), it executes a real process with potential side effects (network requests to advisory databases, file system access).
From the tool's definition 'Runs cargo audit' — actively executes the cargo audit command to perform vulnerability scanning
Attacks that exploit this kind of access
The rule that runs audit 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 audit, this is the rule to start with:
audit 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 audit call is checked against it from then on.
Questions about audit
Runs cargo audit and returns structured vulnerability data. 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 audit: 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.
audit 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 audit 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 audit. 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.
audit 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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