Developer builds 28-rule prompt injection firewall to protect AI agents from MCP threats

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Edison Flores of AliceLabs LLC has released L1.9, a prompt injection defense layer designed to scan AI agent inputs before potentially malicious content enters a large language model's context window. The tool targets a known vulnerability in MCP (Model Context Protocol) servers, where tool descriptions can carry hidden instructions to override agent behavior or exfiltrate sensitive data. L1.9 applies 28 detection rules across skill names, descriptions, system prompts, and capability schemas, flagging threats at critical, high, or medium severity levels and quarantining dangerous skills automatically. Each detected finding is mapped to a MITRE ATT&CK technique ID and includes a snippet of the offending text for transparency. Flores claims L1.9 is part of a broader 10-layer security stack, which he says is unmatched by most existing MCP directories that offer no such protections.

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