Gurucul, a pacesetter in unified safety and danger analytics expertise for on-premises and the cloud, introduced the Gurucul Threat Analytics (GRA) platform has added and aligned machine studying (ML) fashions to detect and allow automated responses to adversarial techniques and methods outlined by the MITRE ATT&CK Framework.
Gurucul’s ML fashions span customers and entities throughout hybrid/ borderless environments mixed with superior risk chaining supplies 83 % protection for MITRE ATT&CK indicators of compromise and unprecedented visibility for organizations to grasp and enhance their safety posture.
“Gurucul prospects utilizing the MITRE ATT&CK Framework confirmed that these new superior habits fashions have been capable of detect unknown threats related to excessive danger third events together with prospects, companions and contractors, that evaded signature-based approaches,” mentioned Nilesh Dherange, CTO of Gurucul.
“GRA is the one platform with ML Characteristic Evaluation functionality that gives speedy MITRE ATT&CK Framework information readiness and superior mannequin chaining to sew collectively context throughout a number of behavioral indicators with a timeline view for clever investigations.”
The MITRE ATT&CK Framework is a globally accessible data base of adversary techniques and methods based mostly on real-world observations. The ATT&CK data base is used as a basis for the event of particular risk fashions and methodologies within the personal sector, authorities, and the cybersecurity product and repair neighborhood.
Automated MITRE ATT&CK Framework risk detection
Gurucul’s MITRE ATT&CK Framework alignment supplies the next advantages for detecting and searching threats at each step of the cyber kill chain:
- GRA’s prepackaged machine studying fashions present 83% protection of the greater than 350 enterprise MITRE ATT&CK Framework techniques and methods throughout on-premises, cloud and hybrid environments for speedy operationalization
- GRA makes use of habits analytics and superior risk chaining to detect unknown risk patterns by each customers and entities past the techniques and methods contained within the MITRE ATT&CK Framework
- Prepackaged habits mannequin templates in Gurucul STUDIO and risk searching queries based mostly on MITRE methods, techniques, and procedures allow environment friendly risk searching together with a contextual view for clever investigations
- GRA’s ML Characteristic Evaluation supplies MITRE ATT&CK Framework information readiness evaluation, enabling organizations to get speedy worth from current information, acquire priceless perception into lacking information and protection impacts, and the flexibility to gather lacking information routinely utilizing GRA out of the field connectors
- GRA supplies danger prioritized alerts and automatic remediation playbooks based mostly on the MITRE ATT&CK Framework
- GRA supplies unmatched visibility, metrics, dashboards, and stories into a corporation’s safety posture and maturity towards particular MITRE ATT&CK Framework techniques and methods
- Automation through API-based STIX integration retains GRA fashions present with MITRE updates and danger mitigation playbooks on a steady foundation
- Gurucul’s information science group performs routine enhancement of MITRE ATT&CK Framework fashions