LOS ANGELES – Feb. 13, 2020 – Gurucul, a leader in unified security and risk analytics technology for on-premises and the cloud, today announced the Gurucul Risk Analytics (GRA) platform has added and aligned machine learning (ML)models to detect and enable automated responses to adversarial tactics and techniques defined by the MITRE ATT&CK™ Framework. Gurucul’s ML models span users and entities across hybrid/ borderless environments combined with advanced threat chaining provides 83 percent coverage for MITRE ATT&CK indicators of compromise and unprecedented visibility for organizations to understand and improve their security posture. Gurucul is exhibiting its GRA unified security and risk analytics platform at RSA Conference 2020 booth #2027 in San Francisco.
“Gurucul customers using the MITRE ATT&CK Framework confirmed that these new advanced behavior models have been able to detect unknown threats associated with high risk third parties including customers, partners and contractors, that evaded signature-based approaches,” said Nilesh Dherange, CTO of Gurucul. “GRA is the only platform with ML Feature Analysis capability that provides immediate MITRE ATT&CK Framework data readiness and advanced model chaining to stitch together context across multiple behavioral indicators with a timeline view for intelligent investigations.”
The MITRE ATT&CK Framework is a globally accessible knowledge base of adversary tactics and techniques based on real-world observations. The ATT&CK knowledge base is used as a foundation for the development of specific threat models and methodologies in the private sector, government, and the cybersecurity product and service community.
Gurucul’s MITRE ATT&CK Framework alignment provides the following benefits for detecting and hunting threats at every step of the cyber kill chain:
GRA with support for the MITRE ATT&CK™ Framework is available immediately from Gurucul and its business partners worldwide.
Gurucul is a global cyber security and fraud analytics company that is changing the way organizations protect their most valuable assets, data and information from insider and external threats both on-premises and in the cloud. Gurucul’s real-time unified security analytics and fraud analytics technology combines machine learning behavior profiling with predictive risk-scoring algorithms to predict, prevent and detect breaches. Gurucul technology is used by Global 1000 companies and government agencies to fight cyber fraud, IP theft, insider threat and account compromise as well as for log aggregation, compliance and risk based security orchestration and automation. The company is based in Los Angeles. To learn more, visit https://gurucul.com/ and follow us on LinkedIn and Twitter.