A Network Forensic Analysis Tool (NFAT) for deep inspection of PCAP files and live traffic, extracting credentials, building network maps, and reconstructing sessions.
BruteShark is a Network Forensic Analysis Tool (NFAT) that performs deep inspection of network traffic from PCAP files or live captures. It extracts credentials, builds network maps, reconstructs sessions, carves files, and analyzes VoIP calls to help identify security vulnerabilities. The tool provides both a GUI for Windows and a CLI for Windows and Linux, with a modular architecture for extensibility.
Security researchers, network administrators, and forensic analysts who need to analyze network traffic for weaknesses, incident response, or penetration testing.
BruteShark offers a comprehensive, open-source alternative to commercial NFAT tools, with features like Hashcat integration for hash cracking, visual network mapping, and cross-platform support. Its modular design allows for easy expansion and independent use of components.
Network Analysis Tool
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Extracts usernames, passwords, and authentication hashes from protocols like HTTP, FTP, and Kerberos, with direct Hashcat integration for offline cracking, as shown in the modules table.
Builds interactive network diagrams showing nodes and ports, and exports to JSON for use with tools like Neo4j, enhancing topology analysis and forensic investigations.
Uses a pluggable module system in .NET Core, allowing easy addition of new analysis features via the IModule interface, as described in the architecture section.
Command-line interface works on both Windows and Linux, with prerequisites like libpcap, making it accessible for diverse operational environments.
The BruteSharkDesktop application is available only for Windows, forcing Linux and macOS users to rely solely on the CLI for graphical analysis needs.
The README explicitly warns that analyzing network traffic consumes significant time and resources, especially with TCP/UDP session reconstruction enabled, slowing down processing of large PCAPs.
Relies on 'Header-Footer' carving for files like JPG and PNG, which may not effectively recover fragmented or encrypted files compared to more advanced forensic tools.