Enhanced Features Extend ReversingLabs Explainable Threat Intelligence Capabilities for Threat Hunters and Security Operations Teams

MITRE ATT&CK® Mapping, Indicator Transparency and Interactive Storytelling Provide Added Context, Transparency and Prescriptive Recommendations

CAMBRIDGE, Mass. - August 4, 2020 - ReversingLabs, the leading provider of explainable threat intelligence solutions, today announced new capabilities for its Titanium Platform, continuing to support its novel approach to machine learning malware detection. The platform remains the first machine learning-powered classification system designed to provide explainable insights and verification that better support humans in the incident response decision making process. ReversingLabs new capabilities are accessible for  in the Virtual Business Hall at Black Hat August 5-6. Registered attendees of Black Hat may visit  beginning August 5.ReversingLabs Explainable Threat Intelligence approach to threat intelligence and detection automates time-intensive threat research efforts with the level of detail practitioners need to better understand events, improve productivity and refine their skills.  optimize analysts’ ability to quickly understand and take action, reducing the time to detect and respond to threats and minimize organizational impact. Direct integration with and better visibility into MITRE ATT&CK tactics, techniques and procedures; unique full indicator transparency for confident classification and understanding; and interactive storytelling linking malware sample behaviors all combine to deliver actionable intelligence and upskill threat hunting and security operations teams.“Inundated by volumes of threat data and lacking the skills or tools necessary to analyze and understand it, security operations and threat hunting teams struggle to adequately assess and respond to malware risks effectively,” said Mario Vuksan, CEO and Co-Founder, ReversingLabs. “ReversingLabs Explainable Threat Intelligence approach and enhanced platform capabilities combined with the depth and scale of objects and file formats in our repository and split-second analysis ensures that security teams gain human-readable, actionable insights that enable them to quickly and accurately detect, classify and remediate malware threats.”Modern digital objects, made up of layers of structured code and data, are central to the exchange or storage of information and are becoming increasingly complex. Moreover, because signature, AI and machine learning-based threat classifications from “black box” detection engines come with little to no context, security analysts are left in the dark as to why a verdict was determined, negatively impacting their ability to verify threats, take informed action and extend critical job skills. ReversingLabs Explainable Threat Intelligence approach leverages threat data from both internal and external sources to systematically analyze each layer of these complex objects, generating transparent “glass box” actionable intelligence and human interpretable data to detect, classify and respond to malware threats. Combining static, dynamic, and machine learning analysis, ReversingLabs Titanium Platform automates the vast majority of repeatable, time-consuming, and error-prone analysis tasks using a breadth of modern techniques, including object reputation, similarity analysis, and metadata correlation to discern, define and describe good from bad.