AI agents use update_time_registration to create or update resources in Timelog — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Timelog environment.
An AI agent can call update_time_registration faster than any human can review — one bad instruction and it creates or modifies resources in Timelog by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Update an existing time registration (hours, comment, date, billable status). It is categorised as a Write tool in the Timelog MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Timelog MCP server in PolicyLayer and add a rule for update_time_registration: 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 Timelog. Nothing to install.
update_time_registration is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_time_registration 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 update_time_registration. 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.
update_time_registration is provided by the Timelog MCP server (timelog-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.