guardrails_scan_injection
AI agents call guardrails_scan_injection to retrieve information from ThinkNEO MCP SMB without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool appears to scan content for prompt injection vulnerabilities, analogous to security intrusion detection. Scanning and detection are non-destructive read operations that analyze data without modifying it.
From the tool's definition Tool name is 'guardrails_scan_injection' and is part of a Guardrails module described as detecting 'prompt injection' attacks.
Attacks that exploit this kind of access
guardrails_scan_injection. It is categorised as a Read tool in the ThinkNEO MCP SMB MCP Server, which means it retrieves data without modifying state.
Register the ThinkNEO MCP SMB MCP server in PolicyLayer and add a rule for guardrails_scan_injection: 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 ThinkNEO MCP SMB. Nothing to install.
guardrails_scan_injection is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the guardrails_scan_injection 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 guardrails_scan_injection. 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.
guardrails_scan_injection is provided by the ThinkNEO MCP SMB MCP server (thinkneo-ai/mcp-smb-products). 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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