Get information about the current authenticated user
AI agents call get_current_user to retrieve information from Raalarcon Jira without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves user profile information without modifying, executing, or deleting any data. It is a straightforward read operation that poses minimal risk if misused by an AI agent.
From the tool's definition Tool name is 'get_current_user' and description states 'Get information about the current authenticated user' — a pure retrieval operation with no side effects.
Attacks that exploit this kind of access
Get information about the current authenticated user. It is categorised as a Read tool in the Raalarcon Jira MCP Server, which means it retrieves data without modifying state.
Register the Raalarcon Jira MCP server in PolicyLayer and add a rule for get_current_user: 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 Raalarcon Jira. Nothing to install.
get_current_user 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 get_current_user 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 get_current_user. 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.
get_current_user is provided by the Raalarcon Jira MCP server (raalarcon-jira-mcp-server). 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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