Outlook and conclusions
For years, mid-sized proxy botnets have existed without them being disrupted and published on. Examples are the botnets we associate with the Water Barghest and Water Zmeu intrusion sets. The actor groups behind these intrusion sets have made refinements in their setup over the years and automated their operations to a high degree. Eventually, some of these botnets were brought to the attention of the security industry. In the case of Water Barghest, this was because of the use of Water Barghest’s infrastructure to deploy a zero-day against Cisco IOS XE devices that infected tens of thousands of routers in October 2023. In the case of Water Zmeu, APT actor Pawn Storm’s use of this criminal botnet for espionage purposes motivated the FBI to disrupt the Water Zmeu-associated router botnet. Upon completing our write-up on Water Barghest’s activities, we became aware of a LevelBlue blog entry that partially overlaps with our findings.
APT actors have also deployed their dedicated IoT botnets sometimes for years, before they were disrupted by the FBI and its partners. APT actors and financially motivated actors will continue to have an interest in building their own IoT botnets for anonymization purposes and espionage. They also will continue to use third-party botnets or commercially available residential proxy services.
We expect that both the commercial market for residential proxy services and the underground market of proxies will grow in the coming years, because the demand from APT actors and cybercriminals actor groups is high. Protecting against these anonymization layers is a challenge for many enterprises and government organizations around the world. Court-approved disruptions of proxy botnets will help put a dent into malign operations, but it is better to do something against the source of the problem: securing IoT devices is of paramount importance, and whenever possible, these devices should not be exposed to incoming connections from the open internet.
Whenever an IoT device accepts incoming connections on the open internet, commercial scanning services will quickly find them online, and malicious actors can find them too via bought or stolen access to these internet scanning services. Using internet scan data, the automated scripts of bad actors can quickly try known vulnerabilities, and possibly even zero-days, against the exposed IoT devices. In the case of Water Barghest, we have seen that the time between exploiting an IoT device and putting them for sale on a residential proxy marketplace can be as little as 10 minutes. Therefore, it is important not to expose IoT devices to incoming internet connections whenever it is not business-essential, and put mitigations in place to avoid their infrastructure being part of the problem itself.
Trend Micro Vision One Threat Intelligence
To stay ahead of evolving threats, Trend Micro customers can access a range of Intelligence Reports and Threat Insights within Trend Micro Vision One. Threat Insights helps customers stay ahead of cyber threats before they happen and better prepared for emerging threats. It offers comprehensive information on threat actors, their malicious activities, and the techniques they use. By leveraging this intelligence, customers can take proactive steps to protect their environments, mitigate risks, and respond effectively to threats.
Trend Micro Vision One Intelligence Reports App [IOC Sweeping]
Ngioweb IoCs used in Water Barghest Campaigns
Trend Micro Vision One Threat Insights App
Threat Actors: Water Barghest
Emerging Threats: Water Barghest’s Rapid Exploit-to-Market Strategy for IoT Devices
Hunting Queries
Trend Micro Vision One Search App
Trend Micro Vision Once Customers can use the Search App to match or hunt the malicious indicators mentioned in this blog post with data in their environment.
Detection of Ngioweb Malware
malName:*NGIOWEB* AND eventName:MALWARE_DETECTION
More hunting queries are available for Vision One customers with Threat Insights Entitlement enabled.
Indicators of Compromise (IOCs)
The full list of IOCs can be found here. For DGA-generated domains, please refer to this GitHub repository.
YARA rules
As Ngioweb samples are highly obfuscated, an easy approach is to look for known AES keys in .data section. However, it is possible to find samples without section headers. In this case, searching for the AES key in the whole binary (or in a loadable segment) does the job. There are also samples with an AES KEY c91795b59248562e44d6c07526c7ab89dfe45344293703a94a3ae5ff02eab5a4 that we believe could be part of some test, so we didn’t include them in our IOC list. The YARA rules can be found here.