AI agents invoke launch_app to trigger actions in Phantom. 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 executes code/operations on real or simulated devices by launching applications. While launching a benign app is low-risk, the blast radius is high because: (1) an AI agent could be tricked into launching malicious or unwanted applications, (2) launching apps with side effects (payment apps, data deletion utilities, etc.) could cause unintended consequences, (3) repeated launches could DoS the device.
From the tool's definition Tool name 'launch_app' combined with description 'Lance une app sur le device actif' (Launch an app on the active device) indicates execution of an external operation.
Attacks that exploit this kind of access
Lance une app sur le device actif. iOS : bundle ID (ex: com.monapp.ios). Android : package name (ex: com.monapp.android). It is categorised as a Execute tool in the Phantom MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Phantom MCP server in PolicyLayer and add a rule for launch_app: 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 Phantom. Nothing to install.
launch_app 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 launch_app 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 launch_app. 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.
launch_app is provided by the Phantom MCP server (nthimpulse/phantom-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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