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New Mirai Uses 18 Exploits to Target IoT Devices
Samples of the latest version of the botnet virus, which was first discovered in 2016, were initially disclosed in a blog post published by Palo Alto Networks. Researchers suggested that cybercriminals working with the Linux open-source operating system are trying to take over an increasingly wide range of IoT devices and use them to run distributed denial-of-service (DDoS) attacks. Eight of the exploits in the latest Mirai malware variant are new, the researchers added.
While security experts have been studying Mirai for some time, the latest variant contains multiple previously unknown default credentials that could be used in brute-force attacks, according to researchers. A string table that spells 0xDFDAAXFD serves as the encryption key, which echoes the original Mirai source codes standard encryption scheme.
Much in the way a legitimate software product would be assessed and improved over time, researchers said the threat actors behind Mirai are continuousljy evaluating the exploits it uses, keeping those that tend to infect more machines. Four of the exploits in the current variation, for example, are designed to take over specific products, such as LG Supersign TV sets and Belkins Wemo devices.
Although two different command-and-control (C&C) server domains were identified, they did not resolve to any particular IP address, the researchers said. The final iteration of the latest Mirai malware was uploaded on May 26, following some minor updates to the directory hosting it.
Unfortunately, IoT devices are popular with cybercriminals because they often run in environments with little to no human intervention. That means security professionals need to ensure that their networks are only running products that incorporate security by design.
IBM experts suggest the best IoT manufacturers do things like conducting an attack surface analysis to see in which ways devices might be vulnerable to rogue actors, and prioritizing continuous integration and deployment automation based on the highest areas of risk.