Threat Research

VPNFilter Malware - Critical Update

By FortiGuard SE Team | June 06, 2018

VPNFilter, a new malware campaign first reported this past May 23rd, is part of a new line of emerging IoT threats that FortiGuard Labs has been tracking over the past few years. What makes this threat particularly dangerous is that it not only performs data exfiltration, but can also render devices completely inoperable, either individually or as a group. Because many homes, home offices, small businesses, and other entities rely on their internet connections for everything from performing transactions to IP phone lines for making emergency calls, targeting these devices en masse can easily disrupt an entire area.

Overview

As a member of the Cyber Threat Alliance (CTA), FortiGuard Labs received critical information and additional findings in advance of today’s June 6th announcement, just as we did before Talos released their first VPNFilter report on May 23rd. According to this update, which has been subsequently validated by FortiGuard Labs, the VPNFilter campaign is targeting significantly more devices than initially thought, and contains additional capabilities, including the ability to deliver exploits to endpoints.

Recent findings also reveal several additional manufacturers not previously on the list that are affected by VPNFilter. 

As previously reported, the VPNFilter malware delivers an attack in three stages. Stage 1 is focused on persistence and redundancy and can survive a reboot. Stage 2 contains data exfiltration, command execution, file collection, and device management. And Stage 3 is comprised of modules that perform different tasks. At the time, we had confirmed that three different Stage 3 modules had been identified, with the possibility that there were others. Now we can confirm that additional Stage 3 modules have been identified.

Two new modules—ssler and dstr—are outlined below:

ssler – exploitation module

The ssler endpoint exploitation module provides data exfiltration and JavaScript injection capabilities by performing a man in the middle attack (MITM) on all traffic traversing port 80. This module uses a predefined set of parameters that enable the attacker to target specific websites for JavaScript file injection, as well as the ability to hone an attack depending on the type of campaign being run.

The ssler module can also redirect all port 80 traffic to a local listening service on port 8888. To ensure that these rules do not get removed, ssler deletes and restores them approximately every four minutes.

Adding further insult to injury, any outgoing web requests on port 80 are intercepted by ssler and can be inspected and manipulated before being sent to a legitimate HTTP service. SSL requests over HTTPS:// are automatically converted to HTTP:// thereby allowing the attacker to harvest credentials from traffic that would normally be sent over port 443. Once credentials to that domain have been harvested it is added to a list that allows subsequent requests to revert back to traveling via HTTPS over port 443.

dstr - device destruction module

The dstr module is used to render an infected device inoperable by deleting files necessary for normal operation, thus taking the victim and anything connected to it completely offline. This new module arms Stage 2 deployments with a kill command that can disable the resident device. It deletes all files and folders related to itself by searching for all running processes named vpnfilter, security, and tor and terminating them. It then clears flash memory by overwriting the bytes of all available /dev/mtdX devices with a 0xFF byte. Finally, it executes the shell command rm -rf /* to delete the remainder of the file system and the device is rebooted. As a result, the device is rendered completely inoperable and will need to be replaced.

Summary

This is a perfect example of a campaign that has been exposed but is still quite active as more samples, devices, and URIs involved are still being discovered. This highlights one of the difficulties that researchers face on a daily basis in the modern era of malware research. Threat actors are not only becoming more and more adept at refining their craft and finding ways to evade analysts and detection, but are now creating botnets that span and target multiple vendors, devices, and attack scenarios.  This evolution is especially alarming as we are now in the Internet of Things era, with hundreds of millions of exploitable devices online, compared to the past where threat actors focused on one particular operating system.

Armed with the knowledge that many users simply do not change the default settings for their IoT devices, or that vendors either do not take security seriously, or have a limited security focus, sophisticated attacks targeting the IoT space have now evolved from a theory to a reality. The exploitation vector and complexity is especially serious due to sheer magnitude of devices now online that are directly connected to the internet by themselves, often without a security solution in place, giving attackers a wide range of potential infection vectors to choose from.

When the world first saw Mirai we were all shocked at its malicious impact. But the fact is that Mirai was simply a DDoS platform for hire that attackers could leverage in taking down webservers/hosts and other online targets. As reported in various media outlets, the original intent of the authors was to simply knock down servers hosting the game Minecraft. While its results were impressive, it was simply a DDoS attack, and nothing like what we see today, where multiple devices can be targeted, attack vectors can be dynamically updated, data can be exfiltrated, and devices can literally be destroyed with a single command. In addition, the attack platform is broader in scope, which makes a coordinated, joint takedown between industry and law enforcement even more difficult, let alone attributing a threat to a known actor or nation state. And bad actors know this.

They also count on the fact that it takes significant man-hours and effort to effectively respond to a threat because various organizations across the security space have traditionally had a difficult time sharing information efficiently. Which is one of the reasons why the Cyber Threat Alliance was formed: to help first responders and other security professionals more effectively protect the digital ecosystem.

Because of our membership in the Cyber Threat Alliance and its open information sharing model, information on threat actors, their campaigns, and associated IOCs are shared in real time between security professionals in order to provide all of our customers with the fastest coverage and response possible.

FortiGuard Labs and the other members of the Cyber Threat Alliance are actively monitoring this event for any further developments, and will provide any updates when they become available.

------------

Protections

AV coverage is in place for all known available samples as: Elf/Agent.1731!tr (AVDB 58.785)

IPS coverage was deemed not feasible.

The Web Filtering team has blacklisted all network IOCs.

Additional IOCs have been added to the FortiGuard Botnet Protection list. (Botnet IP Reputation DB 2.00007)

Mitigations

Because of the potential for catastrophic failure, and because manufacturer updates can take a long time, FortiGuard Labs recommends entirely replacing affected devices where possible

IOCs

Below is the full list of IOCs, including updates as of June 6th, 2018:

Known C2 Domains and IPs

Associated with the 1st Stage

photobucket[.]com/user/nikkireed11/library

photobucket[.]com/user/kmila302/library

photobucket[.]com/user/lisabraun87/library

photobucket[.]com/user/eva_green1/library

photobucket[.]com/user/monicabelci4/library

photobucket[.]com/user/katyperry45/library

photobucket[.]com/user/saragray1/library

photobucket[.]com/user/millerfred/library

photobucket[.]com/user/jeniferaniston1/library

photobucket[.]com/user/amandaseyfried1/library

photobucket[.]com/user/suwe8/library

photobucket[.]com/user/bob7301/library

toknowall[.]com

 

Associated with the 2nd Stage

91.121.109[.]209

217.12.202[.]40

94.242.222[.]68

82.118.242[.]124

46.151.209[.]33

217.79.179[.]14

91.214.203[.]144

95.211.198[.]231

195.154.180[.]60

5.149.250[.]54

94.185.80[.]82

62.210.180[.]229

91.200.13[.]76

23.111.177[.]114

6b57dcnonk2edf5a[.]onion/bin32/update.php

tljmmy4vmkqbdof4[.]onion/bin32/update.php

zuh3vcyskd4gipkm[.]onion/bin32/update.php

4seiwn2ur4f65zo4.onion/bin256/update.php

zm3lznxn27wtzkwa.onion/bin16/update.php

Known File Hashes

1st Stage Malware

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2nd Stage Malware

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3rd Stage Plugins

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Self-Signed Certificate Fingerprints

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044bfa11ea91b5559f7502c3a504b19ee3c555e95907a98508825b4aa56294e4

c0f8bde03df3dec6e43b327378777ebc35d9ea8cfe39628f79f20b1c40c1b412

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