删除百度网盘中的文件或文件夹
AI agents call delete_files to permanently remove resources in Baidu Pan — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
This tool permanently removes files or folders from cloud storage without recovery options, making it a destructive action. The blast radius is high as an AI agent could inadvertently delete critical user data if given incorrect or malicious instructions.
From the tool's definition Tool name 'delete_files' and description '删除百度网盘中的文件或文件夹' (delete files or folders from Baidu Netdisk) directly indicate irreversible deletion of data.
Attacks that exploit this kind of access
删除百度网盘中的文件或文件夹. It is categorised as a Destructive tool in the Baidu Pan MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Baidu Pan MCP server in PolicyLayer and add a rule for delete_files: 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 Baidu Pan. Nothing to install.
delete_files 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 delete_files 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 delete_files. 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.
delete_files is provided by the Baidu Pan MCP server (xileforcly/baidu-pan-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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