getEffectivePermission
Compute a user's effective permission level on a resource (taking team grants, inheritance, and 3-state overrides into account) and the source. Asking about another user requires can_manage_perms on the org. Use when the user asks 'can X access this', 'what level of access does X have', 'why can ...
This record as markdown: /tools/io-stablebaseline-sb/geteffectivepermission.md
What getEffectivePermission does on Stable Baseline
AI agents call getEffectivePermission to retrieve information from Stable Baseline without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
user_id | string | Yes | UUID of the user to check |
resource_id | string | Yes | |
resource_type | string | Yes |
Parameters from the server's own tool schema.
Why getEffectivePermission is rated Low
This tool retrieves and queries permission metadata about users and resources without modifying any state. However, it is not a simple 'low' severity read because: (1) it can expose sensitive authorization information that could inform privilege escalation attacks, (2) querying another user's permissions requires can_manage_perms on the org (access control noted but not enforced by the tool itself), and (3) misuse…
From the tool's definition Tool name is 'getEffectivePermission' and description states it 'Compute a user's effective permission level on a resource' and returns 'the source'. The verb 'compute' and 'get' indicate data retrieval. Description explicitly mentions 'Use when the user asks.
Attacks that exploit this kind of access
The rule that runs getEffectivePermission safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Stable Baseline, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For getEffectivePermission, this is the rule to start with:
getEffectivePermission is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Stable Baseline, apply this rule, and every getEffectivePermission call is checked against it from then on.
Questions about getEffectivePermission
Compute a user's effective permission level on a resource (taking team grants, inheritance, and 3-state overrides into account) and the source. Asking about another user requires can_manage_perms on the org. Use when the user asks 'can X access this', 'what level of access does X have', 'why can X see this', or to debug an unexpected permission outcome. It is categorised as a Read tool in the Stable Baseline MCP Server, which means it retrieves data without modifying state.
getEffectivePermission accepts 3 parameters: user_id, resource_id, resource_type. Required: user_id, resource_id, resource_type. The full parameter table on this page comes from the server's own tool schema.
Register the Stable Baseline MCP server in PolicyLayer and add a rule for getEffectivePermission: 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 Stable Baseline. Nothing to install.
getEffectivePermission is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the getEffectivePermission 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 getEffectivePermission. 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.
getEffectivePermission is provided by the Stable Baseline MCP server (https://api.stablebaseline.io/functions/v1/cloud-serve/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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