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)
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A .Net wrapper library for the native Yara library with interoperability and portability features.
Interactive incremental disassembler with data/control flow analysis capabilities.
A proof-of-concept tool for generating payloads that exploit unsafe Java object deserialization.
A collection of XSS payloads designed to turn alert(1) into P1
Cybersecurity tool merging DarunGrim's analysis algorithms, currently in internal testing for official release.
A serverless, real-time, and retroactive malware detection tool that scans files with YARA rules and alerts incident response teams.
A minimal, consistent API for building integrations with malware sandboxes
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