SoReL-20M (Sophos-ReversingLabs): A Huge Dataset of 20 Million Malware Samples Released Online

guest · Dec 14, 2020

SoReL-20M: A Huge Dataset of 20 Million Malware Samples Released Online
December 14, 2020
https://thehackernews.com/2020/12/sorel-20m-huge-dataset-of-20-million.html

Cybersecurity firms Sophos and ReversingLabs on Monday jointly released the first-ever production-scale malware research dataset to be made available to the general public that aims to build effective defenses and drive industry-wide improvements in security detection and response.

"SoReL-20M" (short for Sophos-ReversingLabs – 20 Million), as it's called, is a dataset containing metadata, labels, and features for 20 million Windows Portable Executable (.PE) files, including 10 million disarmed malware samples, with the goal of devising machine-learning approaches for better malware detection capabilities.

"Open knowledge and understanding about cyber threats also leads to more predictive cybersecurity," Sophos AI group said. "Defenders will be able to anticipate what attackers are doing and be better prepared for their next move."
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The release of SoReL-20M follows similar industry initiatives in recent months, including that of a coalition led by Microsoft, which released the Adversarial ML Threat Matrix in October to help security analysts detect, respond to, and remediate adversarial attacks against machine learning systems.

"The idea of threat intelligence sharing in security isn't new but is more critical than ever given the innovation threat actors have shown over the past several years," ReversingLabs researchers said.
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Sophos: Sophos-ReversingLabs (SOREL) 20 Million sample malware dataset

The Sophos AI team is excited to announce the release of SOREL-20M (Sophos-ReversingLabs – 20 million) – a production-scale dataset containing metadata, labels, and features for 20 million Windows Portable Executable files, including 10 million disarmed malware samples available for download for the purpose of research on feature extraction to drive industry-wide improvements in security.

This dataset is the first production scale malware research dataset available to the general public, with a curated and labeled set of samples and security-relevant metadata, which we anticipate will further accelerate research for malware detection via machine learning. Code and links to the data are available here.
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