AI agents invoke lerna to trigger actions in Test. 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.
Lerna is a monorepo management tool that executes commands across packages. The 'run' command can execute arbitrary npm scripts, and 'version' modifies package metadata, making this an execution tool. While it can also list/query (Read), the capability to 'run' commands and modify versions places it in Execute category.
From the tool's definition Tool 'runs Lerna monorepo commands' including 'version' which modifies package versioning across multiple packages, and 'run' which executes arbitrary scripts in a monorepo context.
Attacks that exploit this kind of access
Runs Lerna monorepo commands (list, run, changed, version) and returns structured package information. It is categorised as a Execute tool in the Test MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Test MCP server in PolicyLayer and add a rule for lerna: 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 Test. Nothing to install.
lerna 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 lerna 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 lerna. 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.
lerna is provided by the Test MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.