AI agents use update_run to create or update resources in TestRail MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your TestRail MCP Server environment.
The 'update_run' tool modifies TestRail run records (test execution records). This is a Write operation as it creates or modifies data reversibly. Severity is medium because misuse could corrupt test data and invalidate test results, but effects are typically reversible through additional updates. Confidence is 0.75 due to empty tool description—direct confirmation of functionality would raise this to 0.95+.
From the tool's definition Tool name 'update_run' indicates modification of run entities. Server description confirms TestRail integration with core entities including 'runs'. Sibling tools show patterns of create (add_*) and delete operations.
Documented attack patterns abuse exactly the kind of access update_run gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and TestRail MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_run:
{
"version": "1",
"default": "deny",
"tools": {
"update_run": {
"limits": [
{
"counter": "update_run_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_run stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
update_run. It is categorised as a Write tool in the TestRail MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the TestRail MCP Server MCP server in PolicyLayer and add a rule for update_run: 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 TestRail MCP Server. Nothing to install.
update_run 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_run 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_run. 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_run is provided by the TestRail MCP Server MCP server (sker65/testrail-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from TestRail MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
29 TestRail MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.