AI agents use protect_funds to commit financial operations through Smokeball — usually the final step of a payment, billing, or trading workflow. A call moves real money.
This tool directly manipulates financial funds by reserving/protecting them in a trust account, which constitutes a financial operation. Trust accounts in law firms hold client funds and any modification to them has significant financial and legal implications. Misuse could improperly lock client funds or affect financial obligations.
From the tool's definition Protect (reserve) funds in a trust account for a matter
Attacks that exploit this kind of access
Protect (reserve) funds in a trust account for a matter. It is categorised as a Financial tool in the Smokeball MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
Register the Smokeball MCP server in PolicyLayer and add a rule for protect_funds: 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 Smokeball. Nothing to install.
protect_funds 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 protect_funds 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 protect_funds. 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.
protect_funds is provided by the Smokeball MCP server (rosenadvertising/smokeball-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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