AI agents use execute_order to commit financial operations through Asterdex — usually the final step of a payment, billing, or trading workflow. A call moves real money.
This tool directly executes financial trades (perpetual futures orders) on a DEX, committing real financial obligations. Misuse by an AI agent could result in significant monetary losses through unintended trades, wrong position sizes, or market manipulation. Financial is the highest severity category and clearly applies here.
From the tool's definition "Place a new order or modify a position" on a DEX perpetual futures trading server
Attacks that exploit this kind of access
Place a new order or modify a position. It is categorised as a Financial tool in the Asterdex MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
Register the Asterdex MCP server in PolicyLayer and add a rule for execute_order: 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 Asterdex. Nothing to install.
execute_order is a Financial tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the execute_order 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 execute_order. 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.
execute_order is provided by the Asterdex MCP server (tyranosurasmax/asterdex-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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