yarGen is a generator for YARA rules. The main principle is the creation of yara rules from strings found in malware files while removing all strings that also appear in goodware files. yarGen includes a big goodware strings and opcode database as ZIP archives that have to be extracted before the first use. In version 0.24.0, yarGen introduces an output option (--ai). This feature generates a YARA rule with an expanded set of strings and includes instructions tailored for an AI. Activating the --ai flag appends the instruction text to the yargen_rules.yar output file, which can subsequently be fed into your AI for processing. With version 0.23.0 yarGen has been ported to Python3. If you'd like to use a version using Python 2, try a previous release. (Note that the download location for the pre-built databases has changed)
FEATURES
SIMILAR TOOLS
A Python library to interface with a cuckoo-modified instance.
Collects Yara rules from over 150 free resources, a free alternative to Valhalla.
Interactive .NET SQL console client with enhanced SQL Server discovery, access, and data exfiltration features
A tool for deep analysis of malicious files using ClamAV and YARA rules, with features like scoring suspect files, building visual tree graphs, and extracting specific patterns.
Fernflower is an analytical decompiler for Java with command-line options and support for external classes.
PINNED

Mandos
Fractional CISO service that helps B2B companies implement security leadership to win enterprise deals, achieve compliance, and develop strategic security programs.

Checkmarx SCA
A software composition analysis tool that identifies vulnerabilities, malicious code, and license risks in open source dependencies throughout the software development lifecycle.

Orca Security
A cloud-native application protection platform that provides agentless security monitoring, vulnerability management, and compliance capabilities across multi-cloud environments.

DryRun
A GitHub application that performs automated security code reviews by analyzing contextual security aspects of code changes during pull requests.