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In tandem with the release of this research, Cyxtera announced new functionality in its flagship Zero Trust solution, AppGate SDP, that extends the benefits of network micro-segmentation and software-defined perimeter to connected IoT devices. The AppGate SDP IoT Connector enables enterprises to enforce consistent access control policies across users, servers, and devices to protect today’s complex and distributed resources. Key report findings include: Researchers detected more than 150 million connection attempts to 4,642 distinct IP addresses. 64 percent of incoming connections seemed to originate in China, with another 14 percent from the United States. This was followed by the United Kingdom (nine percent), Israel (eight percent) and Slovakia (six percent). Note: It’s difficult to definitively confirm the origination of Internet traffic as it is possible to re-route traffic to other locations, frequently employed as an obfuscation technique. All IoT devices saw attempted logins immediately upon coming online and the number of login attempts increased steadily over time. Within days of new malware campaigns going public – such as Mirai, Satori, and Hakai – those malware families were being used to attack IoT devices from the honeypot. In many cases, the increase in activity was identifiable in the days and weeks before the malware was publicly named. 54 percent of connections received by the honeypot were via Telnet port, while HTTP ports received almost all of the remaining connections. IP cameras received the majority of connections in the honeypot, suggesting greater attacker interest in those IoT devices as compared to others such as printers and smart switches. Several recent, large-scale attacks on IoT devices have targeted IP cameras. “IoT devices are an attractive target for attackers, because they are often a security after-thought and its harder to keep them patched and up-to-date — if patches are even available at all,” said Alejandro Correa Bahnsen, Vice President of Data Science at Cyxtera. “The researchers involved in this project accurately detected several large-scale attacks targeting IoT devices and demonstrated the frequency and speed with which these devices are targeted. This approach can be replicated by other threat researchers to broaden our collective knowledge about these vulnerabilities.”
