Danny Adamitis on an 'unkillable' router botnet used by Chinese .gov hackers
Jan 5, 2024
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Danny Adamitis, a principal information security engineer at Black Lotus Labs, dives into the alarming discovery of a resilient botnet utilizing outdated SOHO routers. He reveals how this covert network aids Volt Typhoon, a Chinese state-sponsored hacking group. The conversation highlights the global danger of obsolete devices and the urgent need for organizations to bolster their network defenses. Danny shares practical strategies for detecting and mitigating threats, emphasizing robust monitoring and awareness of network assets.
The KV botnet, comprised of outdated SOHO routers, exemplifies how vulnerable end-of-life devices can facilitate covert cyber operations by threat actors.
Effective network defense strategies include regular reboots and enhanced logging practices to detect and mitigate risks from persistent botnets like KV.
Deep dives
Understanding Black Lotus Labs
Black Lotus Labs operates under Lumen Technologies, which resulted from the merger of several prominent telecommunications companies. The lab focuses on analyzing telemetry data from diverse sources to enhance cybersecurity and protect their corporate network and clients. By correlating data from various points, the team aims to uncover sophisticated threat actors who might evade traditional detection methods. Their extensive data collection includes monitoring billions of net flow sessions and DNS resolutions daily, essential for identifying security threats.
The KV Botnet and Its Implications
The KV botnet is made up of outdated small office/home office routers that are exploited by advanced threat actors, specifically linked to a Chinese group known as Volt Typhoon. These compromised devices serve as a covert network for data transfer, enabling malicious activities while bypassing conventional detections. The aging technology often remains unpatched, creating vulnerabilities that can be exploited for prolonged periods. The discussion highlights how this botnet evades traditional defenses and maintains its effectiveness through stealthy operations.
Discovery of the KV Botnet
The discovery of the KV botnet resulted from an unexpected analytical finding related to another activity cluster called Zuorat, which targeted compromised routers. The investigative process involved tracking malicious behaviors and noting anomalies in router communications, leading to the identification of interconnected infected devices. This method revealed a pattern of cohabitation among malware, where multiple types of threats compete for dominance on the same infrastructure. The identification of specific routers, such as Cisco models, emphasized the vulnerability these older devices present in the face of persistent cyber threats.
Proactive Measures for Cyber Defense
Organizations are urged to prioritize monitoring and management of their network devices, particularly older routers that may be vulnerable to exploitation. Implementing regular reboots can effectively clear existing malware from memory and help mitigate risks from the KV botnet. Additionally, teams should enhance their logging practices, particularly on critical systems like domain controllers, to detect unusual access and potential compromises early. By maintaining vigilance and conducting routine checks, organizations can reduce the likelihood of falling victim to these advanced threats.
Danny Adamitis is a principal information security engineer at Black Lotus Labs, the threat research division within Lumen Technologies. On this episode of the show, we discuss his team's recent discovery of an impossible-to-kill botnet packed with end-of-life SOHO routers serving as a covert data transfer network for Volt Typhoon, a Chinese government-backed hacking group previously caught targeting US critical infrastructure.
Danny digs into the inner workings of the botnet, the global problem end-of-life devices becoming useful tools for malicious actors, and the things network defenders can do today to mitigate threats at this layer.