GREYCORTEX is happy to report that it is able to detect the BadRabbit ransomware. This ransomware appeared in Eastern Europe (Russia, Ukraine) but has begun to spread across several countries including South Korea, Poland, the Baltic, and regions. It uses an NSA-based exploit known as “EternalRomance” to enter networks and spreads by SMB port.
MENDEL is able to detect this ransomware in two different ways:
- MENDEL’s integrated ruleset includes a rule specifically detecting the BadRabbit ransomware.
- Independent from this IDS rule, MENDEL’s advanced artificial intelligence and machine learning detects the ransomware’s anomalous port sweep activity.
This detection capability demonstrates that MENDEL can identify unknown threats before rules are created in rules-based security tools. MENDEL provides network security teams vital extra time to protect their networks.
About Version 2
Version 2 is one of the most dynamic IT companies in Asia. The company develops and distributes IT products for Internet and IP-based networks, including communication systems, Internet software, security, network, and media products. Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.
About GREYCORTEX
GREYCORTEX uses advanced artificial intelligence, machine learning, and data mining methods to help organizations make their IT operations secure and reliable.
MENDEL, GREYCORTEX’s network traffic analysis solution, helps corporations, governments, and the critical infrastructure sector protect their futures by detecting cyber threats to sensitive data, networks, trade secrets, and reputations, which other network security products miss.
MENDEL is based on 10 years of extensive academic research and is designed using the same technology which was successful in four US-based NIST Challenges.
