KLara project is aimed at helping Threat Intelligence researchers hunt for new malware using Yara. In order to hunt efficiently for malware, one needs a large collection of samples to search over. Researchers usually need to fire a Yara rule over a collection / set of malicious files and then get the results back. In some cases, the rule needs adjusting. Unfortunately, scanning a large collection of files takes time. Instead, if a custom architecture is used, scanning 10TB of files can take around 30 minutes. KLara, a distributed system written in Python, allows researchers to scan one or more Yara rules over collections with samples, getting notifications by e-mail as well as the web interface when scan results are ready. Features Modern web interface, allowing researchers to 'fire and forget' their rules, getting back results by e-mail / API Powerful API, allowing for automatic Yara jobs submissions, checking their status and getting back results. API Documentation will be released soon. Distributed system, running on commodity hardware, easy to deploy and implement. Architecture KLara leverages Yara's power, distributing scans using a dispatcher-worker mode.
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ALTERNATIVES
A Go library for manipulating YARA rulesets with the ability to programatically change metadata, rule names, and more.
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Studying Android malware behaviors through Information Flow monitoring techniques.
Assembler/disassembler for the dex format used by Dalvik, Android's Java VM implementation.
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