AI agents invoke press_back to trigger actions in Rn Debug. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool triggers a navigation action (pressing the back button) on a connected app/device. It causes an external operation (UI interaction/navigation) whose effect depends on the current app state. It's not purely reading data, nor is it destructive or financial — it executes a UI action that changes the app's state.
From the tool's definition Trigger back navigation on the current platform
Attacks that exploit this kind of access
Trigger back navigation on the current platform. It is categorised as a Execute tool in the Rn Debug MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Rn Debug MCP server in PolicyLayer and add a rule for press_back: 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 Rn Debug. Nothing to install.
press_back is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the press_back 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 press_back. 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.
press_back is provided by the Rn Debug MCP server (rn-debug-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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