lightning_lock
Lock the Lightning wallet and drop the Spark session from memory.
This record as markdown: /tools/io-github-aibtcdev-mcp-server/lightning-lock.md
What lightning_lock does on Aibtc
AI agents call lightning_lock to permanently remove resources in Aibtc, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why lightning_lock is rated Critical
Dropping a session from memory is an irreversible action in the moment — the session state is lost and cannot be recovered without re-authentication. Locking a wallet and destroying an active session constitutes an irreversible disruption to an active financial/operational context, making it at minimum Destructive.
From the tool's definition Lock the Lightning wallet and drop the Spark session from memory
Attacks that exploit this kind of access
The rule that runs lightning_lock safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Aibtc, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For lightning_lock, this is the rule to start with:
lightning_lock is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Aibtc, apply this rule, and every lightning_lock call is checked against it from then on.
Questions about lightning_lock
Lock the Lightning wallet and drop the Spark session from memory. It is categorised as a Destructive tool in the Aibtc MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Aibtc MCP server in PolicyLayer and add a rule for lightning_lock: 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 Aibtc. Nothing to install.
lightning_lock is a Destructive 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 lightning_lock 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 lightning_lock. 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.
lightning_lock is provided by the Aibtc MCP server (aibtcdev/aibtc-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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