AI agents use log_work to create or update resources in Framedeck — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Framedeck environment.
This tool creates or modifies time tracking records associated with a card, which is a reversible data modification. It does not delete data (Destructive), execute code (Execute), move money (Financial), or have broader system effects. The blast radius of misuse is minimal—incorrect time entries can be corrected.
From the tool's definition Tool name 'log_work' and description 'Logs time spent on a card' indicates writing/recording time tracking data to a card.
Attacks that exploit this kind of access
Logs time spent on a card. It is categorised as a Write tool in the Framedeck MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Framedeck MCP server in PolicyLayer and add a rule for log_work: 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 Framedeck. Nothing to install.
log_work 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 log_work 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 log_work. 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.
log_work is provided by the Framedeck MCP server (lukaris/framedeck-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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