VPNFilter is a botnet with capabilities to support both intelligence collection and destructive cyberattack operations. The Cisco Talos team recently notified members of the Cyber Threat Alliance (CTA) of its findings and published this blog.

The malware is believed to target networking devices, although the malware’s initial infection vector is still unclear. Talos, which first reported this attack, claims that it has impacted at least 500,000 networking devices during the last few years. The malware can persist on infected devices and can steal website credentials and monitor Modbus SCADA protocols. It also implements file collection, command execution, data extraction, and device management and, even worse, it can render some or all of the infected devices unusable.

The known devices affected by VPNFilter are some network-attached storage (NAS) devices such as Linksys, MikroTik, Netgear, and TP-Link networking equipment in the small and home office (SOHO) space, as well at QNAP.

Malware infection stages

VPNFilter has a three-stage infection.

Stage 1 completes the persistence on the system and uses multiple control mechanisms to find and connect the Stage 2 deployment server.

Stage 2 focuses on file collection, command execution, data extraction, and device management. Some versions possess a self-destruct capability to render itself unusable.

Stage 3 includes two known modules:

• A traffic sniffer to steal website credentials and monitor Modbus SCADA protocols
• Tor to communicate with anonymous addresses 

Indicators of compromise and sample hashes

URLs and IPs

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

91.121.109[.]209
217.12.202[.]40
94.242.222[.]68
82.118.242[.]124
46.151.209[.]33
217.79.179[.]14
95.211.198[.]231
195.154.180[.]60
5.149.250[.]54
91.200.13[.]76
94.185.80[.]82
62.210.180[.]229
91.200.13[.]76
91.214.203[.]144
6b57dcnonk2edf5a[.]onion/bin32/update.php
tljmmy4vmkqbdof4[.]onion/bin32/update.php
zuh3vcyskd4gipkm[.]onion/bin32/update.php
6b57dcnonk2edf5a[.]onion/bin32/update.php

File hashes

• First-Stage Malware
  • 50ac4fcd3fbc8abcaa766449841b3a0a684b3e217fc40935f1ac22c34c58a9ec
  • 0e0094d9bd396a6594da8e21911a3982cd737b445f591581560d766755097d92

• Second-Stage Malware
  • 9683b04123d7e9fe4c8c26c69b09c2233f7e1440f828837422ce330040782d17
  • d6097e942dd0fdc1fb28ec1814780e6ecc169ec6d24f9954e71954eedbc4c70e
  • 4b03288e9e44d214426a02327223b5e516b1ea29ce72fa25a2fcef9aa65c4b0b
  • 9eb6c779dbad1b717caa462d8e040852759436ed79cc2172692339bc62432387
  • 37e29b0ea7a9b97597385a12f525e13c3a7d02ba4161a6946f2a7d978cc045b4
  • 776cb9a7a9f5afbaffdd4dbd052c6420030b2c7c3058c1455e0a79df0e6f7a1d
  • 8a20dc9538d639623878a3d3d18d88da8b635ea52e5e2d0c2cce4a8c5a703db1
  • 0649fda8888d701eb2f91e6e0a05a2e2be714f564497c44a3813082ef8ff250b

• Third-Stage Malware
  • f8286e29faa67ec765ae0244862f6b7914fcdde10423f96595cb84ad5cc6b344
  • afd281639e26a717aead65b1886f98d6d6c258736016023b4e59de30b7348719

Coverage and mitigation

The aforementioned IOCs are covered as follows:

• Detection names for files: Linux/VPNFilter and Linux/VPNFilter.a
  • V3 DAT with coverage version: 3353
  • V2 DAT with coverage version: 8902
• All samples are GTI classified as malware
• All relevant URLs are GTI classified

Further recommendations from the Talos threat research team:

• Reboot SOHO routers and NAS devices to remove the potentially destructive, nonpersistent Stage 2 and Stage 3 malware
• Work with the manufacturer to ensure that your device is up to date with the latest patches. Apply the updated patches immediately.

ISPs should work aggressively with their customers to ensure their devices are patched to the most recent firmware/

The post VPNFilter Botnet Targets Networking Devices appeared first on McAfee Blogs.

Intel Skylake die shot. (credit: Intel)

A new attack that uses processors' speculative-execution capabilities to leak data, named Speculative Store Bypass (SSB), has been published after being independently discovered by Microsoft's Security Response Center and Google Project Zero. Processors from Intel and AMD, along with some of those using ARM's designs, are all affected.

Since the Meltdown and Spectre flaws were announced earlier this year, the speculative and predictive capabilities of modern microprocessors have been closely examined, revealing several new attacks.

All the attacks follow a common set of principles. Each processor has an architectural behavior (the documented behavior that describes how the instructions work and that programmers depend on to write their programs) and a microarchitectural behavior (the way an actual implementation of the architecture behaves). These can diverge in subtle ways. For example, architecturally, a program that loads a value from a particular address in memory will wait until the address is known before trying to perform the load. Microarchitecturally, however, the processor might try to speculatively guess at the address so that it can start loading the value from memory (which is slow) even before it's absolutely certain of which address it should use.

In early May, researchers disclosed a Mobile malware campaign by a group focused on Middle Eastern targets. This actor was found to be an evolving and sophisticated group using fake Android apps, namely Telegram, to trick users into installing malicious software. They have been active since 2015 and evolved over several campaigns into 2018. On May 14, a Reddit post linked to LamePT, claiming to have leaked their infrastructure including a database containing victim information.

The current leaked assets include:

• MYSQL database
• Audio recordings
• The old C2 server and assets
• AppData folder (presumably of the C2 server)
• Current C2 server and control panel

Further leaked documents are behind a paywall payable to a fresh bitcoin address. The first payment was made on May 13^th, 2018 leaving a balance of $1,110.87. It’s difficult to verify if someone paid to have the first dataset released or the actor paid themselves to appear more authentic. With that said, the authenticity of the data is still in question as we have some significant doubts on at least a portion of the data. For example, the following SMS caught our attention:

“Wife.how she knew the time of murder exactly”.

This text can be found in an SMS spam dataset used for training spam engines. Many other English based SMS messages can also be found here. “will be office around 4 pm. Now I am going hospital” is another example. Universities tend to use these datasets to teach computer science concepts. In this case, the concept is likely related to machine learning techniques for categorizing messages into spam. One university came up often when searching for these messages based on its Computer Science I: Fundamentals homework postings. Other messages could be found in cached websites.

“Credit shuma ka mast jahat ezdiad credit ba hesab tan shumarai 222 ra dair namoda w aba taqeeb aan code 14 raqami ra dakhel nomaed .”

This translates to “Credit card is not available for sale at 222 days or less than 142 days.” and found cached in a language translation site. This particular phrase was being translated from Turkish to Urdu. Not all of the messages were found publicly online. Most of the messages were in Middle Eastern languages presenting its own challenges. Other sources were found such as Facebook posts; however, sources for the vast majority of the SMS message have not yet been located. For these reasons, we remain skeptical of the authenticity of the data.

Other data such as the recordings do not appear to be publicly available. After sampling 100 of these files we’ve found them to sound like authentic recordings. The majority are in 7 minute 59 second .3gpp files. Most appear to be ambient conversations and daily activities and not phone calls as was expected. Searching for public audio is difficult but we can verify that the hashes of the 100 are not publicly indexed by major search engines nor are the file names themselves.

Until we know for certain whether the data is authentic we cannot grantee that this data dump represents ZooPark and its capabilities but we can look at what they could be up to. After reviewing the leaked MySQL database we’ve learned much about the ZooPark’s potential operations.

Tables Included:

• Appinfotracking
• Audiotracking
• Calltracking
• Emailtracking
• geolog
• gpslocation
• phonebookaccess
• phototracking
• recordcall
• registration
• sales_user_info
• settings
• smstracking
• urltracking

From the table names alone, we can infer a lot of the access ZooPark had to user devices and the data they were after. Call tracing, phonebook access, and SMS tracking are unfortunately very common to collect amongst malicious app developers. However, audio tracking caught our attention. While we are still analyzing the dataset, the database records indicate over 102,571 recordings have been uploaded to their C2 server between 2015 and 2018. The dump contains approximately 3,887 of these, jeopardizing private and potentially highly sensitive conversations. Our sampling of these files indicate that the audio was recorded in roughly 8-minute blocks. Most, but not all audio files took place with time gaps between them. There was at least one group conversation that continued on for at least 3 recorded blocks. A surprisingly low number of phone numbers generated these recordings. Only eight phone numbers are part of the recording available through this data dump.

Other conversations were also captured such as SMS texts although portions of these have been found publicly in open datasets. Conceivably, these could have been generated by researchers investigating the malicious Android apps but it’s more likely they were generated by the data leaker to sell the dump. The SMS texts contain much of what you expect such as general chat, and advertisements. However, it’s also riddled with embarrassing or explicit texts which could be used against the users should they prove legitimate. Additionally, we’ve found cleartext two-factor authentication messages from major services such as Google and LinkedIn, and popular chat apps such as Telegram. ZooPark could have used these to gain access to additional services unbeknownst to the victims. After attempting and failing to rebuild several English based conversations we have little confidence that the entire data set came from ZooPark. However, It does exemplify the real danger of sensitive conversations being collected by Zoopark and available for their operations.

Another surprising find is in the Appinfotracking table, where there are 1541 unique apps listed, indicating a very large campaign. Here are a few notable ones:

• Youtube
• Wikipedia
• WhatsApp
• WinZip
• Weather
• VLC
• Twitter
• Telegram
• TrueCaller
• Tango
• Pinterest
• ICQ
• Flashlight
• Facebook
• DUO
• Dropbox
• Crunchyroll

There were relatively few games listed compared to other social and utility apps, perhaps suggesting a more utilitarian or professional target. Approximately, 92 phone numbers are listed in relation to the apps. Of the GPS coordinates we’ve checked the middle east is still the main focus, with a significant footprint in Egypt.

While the data leakers request is for Bitcoin payment, we believe they are primarily interested in acquiring Monero coin. Once payments are made the actors use a popular tool called ShapeShift to turn the Bitcoin into Monero (XMR). Shapeshift allows the actors to pay in from one cryptocoin and receive a payout in another without creating an account for the service. The added Monero features enable them to maintain greater anonymity during the transfer. It is anonymity that usually motivates cybercriminals to move to Monero.  Monero coins are of interest due to their improved anonymity and privacy-related improvements, making it difficult to for law enforcement and security researchers to trace.

The actor who leaked this data is obviously motivated by money as evidenced by the requested payment for further data leaks. Fake datasets, especially those that contain credit card information, email addresses and passwords, have been known to be for sale to scam other cybercriminals. It’s a distinct possibility that this could be the case with the current data dump but it has yet to be determined. However, competition also can play a primary motivator. Many times competing bad actors will attempt to sabotage others in the space. Altruism can play a role as well. Some vigilante actors may believe that their motivations are for the greater good regardless of the laws they break and collateral damage. Whatever the motivations are, data leaks like these can be embarrassing, damaging and in some cases dangerous for the victims whose information it may contain.
Other points of interest:

• There are a surprisingly low number of unique victim numbers in the database with only 169.
• The latest URL record is as recent as May 12,2018
• The latest SMS record is as recent as May 8,2018
• 81 unique numbers had 47,784 records of GPS data stored

Bitcoin Address:

• 1AUMs2ieZ7qN4d3M1oUPCuP3CH9WGQxpbd

The post It’s a Zoo Out There! Data Analysis of Alleged ZooPark Dump appeared first on McAfee Blogs.