Add a file to a knowledge base (PDF, TXT, MD, etc.)
AI agents use owui_add_knowledge_file to create or update resources in ML Lab MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your ML Lab MCP environment.
This tool creates or modifies data in a knowledge base by adding files, fitting the Write category. Severity is medium because: (1) the action is reversible (files can typically be removed), (2) blast radius depends on what knowledge is being added and how it's used by the ML system, (3) in an ML Lab context, poisoning or injecting malicious training data into a knowledge base could degrade model quality or…
From the tool's definition Tool description states 'Add a file to a knowledge base' which creates or modifies data by uploading/ingesting files into a persistent knowledge store.
Attacks that exploit this kind of access
Add a file to a knowledge base (PDF, TXT, MD, etc.). It is categorised as a Write tool in the ML Lab MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the ML Lab MCP server in PolicyLayer and add a rule for owui_add_knowledge_file: 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 ML Lab MCP. Nothing to install.
owui_add_knowledge_file is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the owui_add_knowledge_file 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 owui_add_knowledge_file. 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.
owui_add_knowledge_file is provided by the ML Lab MCP server (pushpullcommitpush/ml-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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