WireSAFE

WireMCP is a Model Context Protocol (MCP) server designed to empower Large Language Models (LLMs) with real-time network traffic analysis capabilities. By leveraging tools built on top of Wireshark's tshark, WireMCP captures and processes live network data, providing LLMs with structured context to assist in tasks like threat hunting, network diagnostics, and anomaly detection.

Features

WireMCP exposes the following tools to MCP clients, enhancing LLM understanding of network activity:

• `capture_packets`: Captures live traffic and returns raw packet data as JSON, enabling LLMs to analyze packet-level details (e.g., IP addresses, ports, HTTP methods).
• `get_summary_stats`: Provides protocol hierarchy statistics, giving LLMs an overview of traffic composition (e.g., TCP vs. UDP usage).
• `get_conversations`: Delivers TCP/UDP conversation statistics, allowing LLMs to track communication flows between endpoints.
• `check_threats`: Captures IPs and checks them against the URLhaus blacklist, equipping LLMs with threat intelligence context for identifying malicious activity.
• `check_ip_threats`: Performs targeted threat intelligence lookups for specific IP addresses against multiple threat feeds, providing detailed reputation and threat data.
• `analyze_pcap`: Analyzes PCAP files to provide comprehensive packet data in JSON format, enabling detailed post-capture analysis of network traffic.
• `extract_credentials`: Scans PCAP files for potential credentials from various protocols (HTTP Basic Auth, FTP, Telnet), aiding in security audits and forensic analysis.

How It Helps LLMs

WireMCP bridges the gap between raw network data and LLM comprehension by:

• Contextualizing Traffic: Converts live packet captures into structured outputs (JSON, stats) that LLMs can parse and reason about.
• Threat Detection: Integrates IOCs (currently URLhaus) to flag suspicious IPs, enhancing LLM-driven