AI agents use stats_by_assignee to create or update resources in GLPI MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GLPI MCP environment.
An AI agent can call stats_by_assignee faster than any human can review — one bad instruction and it creates or modifies resources in GLPI MCP by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Retourne le nombre de tickets par technicien assigné. It is categorised as a Write tool in the GLPI MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GLPI MCP server in PolicyLayer and add a rule for stats_by_assignee: 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 GLPI MCP. Nothing to install.
stats_by_assignee 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 stats_by_assignee 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 stats_by_assignee. 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.
stats_by_assignee is provided by the GLPI MCP server (svtica/glpi-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.