AI agents invoke set_leverage to trigger actions in Bybit. 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.
On a trading exchange like Bybit, 'set_leverage' changes the leverage multiplier for a trading position. This is a configuration change that affects trading risk and exposure. It doesn't directly move money but can dramatically amplify losses/gains on subsequent trades.
From the tool's definition Tool name 'set_leverage' on a trading exchange MCP server; description is empty and uninformative.
Attacks that exploit this kind of access
set_leverage. It is categorised as a Execute tool in the Bybit MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Bybit MCP server in PolicyLayer and add a rule for set_leverage: 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 Bybit. Nothing to install.
set_leverage 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 set_leverage 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 set_leverage. 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.
set_leverage is provided by the Bybit MCP server (johnnywic/bybit-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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