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Zloader 2: The Silent Night

14 April 2022 at 19:08

In this study we are considering one of Zeus successors – Zloader 2. We’ll show how it works and its code peculiarities. We’ll present the result of our deep dive into the botnets and campaigns and show some interesting connections between Zloader and other malware families.


Zloader 2 (also known as Silent Night) is a multifunctional modular banking malware, aimed at providing unauthorized access to online banking systems, payment systems and other financial-related services. In addition to these functions it’s able to download and execute arbitrary files, steal files, inject arbitrary code to visited HTML pages and so on.


According to ZeusMuseum, first versions of Zeus were observed in 2006-2008. Later, in 2011 its source code leaked. As a result, new versions and variants appeared. One of the Zeus successors named Zloader appeared at the turn of 2016 and 2017. Finally, another successor named Silent Night appeared in 2019. It was for sale on the underground market.

The earliest version of this variant we found has a SHA256:
Timestamp 4 December 2019 and version number In the middle of July 2021 the version was spotted.

Microsoft recently announced a joint investigation of multiple security companies and information sharing and analysis centers (ISACs) with the aim to take down the Zloader botnet and took the whole case to court.

Although the original name of the malware likely was Silent Night and the ZeusMuseum calls it Zloader 2 we are simply going to use the name Zloader.

Technical analysis

Modules and components

Zloader consists of different modules and components:

  • Downloader – initial infector
  • Backdoor – main module, exists in x86 and x64 versions
  • VNC module (x86 and x64)
  • Web Injects – received from C&C
  • Additional libraries (openssl, sqlite, zlib, Mozilla libraries)

Backdoors, VNC modules and additional libraries have assigned module IDs that are used by other components to refer to them.


Zloader was distributed using classic email spam. In 2021 the attackers abused Google AdWords to advertise sites with fake Zoom communication tool which actually installed Zloader. Another campaign in 2021 used fake pornsites, where users needed to download additional software to watch video. Downloaders are distributed in a packed form sometimes signed with a valid digital signature.

Map showing the distribution of infected systems:

Code peculiarities

Zloader code is very recognizable. First of all, it is diluted with functions which will never be called. Downloader module may contain functions from the Backdoor module and vice versa. In total, about a half of the code will never be called.

Second, simple x86 instructions like CMP, ADD and XOR are replaced with special functions. These functions contain a lot of useless code to complicate the analysis and they can call other β€œreplacement” functions. To add more insult to the injury multiple β€œreplacement” functions exist for a particular instruction. Also some constants are calculated in runtime using aforementioned β€œreplacement” functions.

Strings are encrypted with a simple XOR algorithm.

Samples have very little imported functions. APIs are resolved in runtime by the hashes of their names.

As a result, more than a half of the file size is useless and serves as an obfuscation of simple operations.


Both Downloader and Backdoor modules have built in configuration encrypted with RC4. The decryption key is stored in a plaintext and looks like vcvslrpvwwfanquofupxt. The structure of earlier versions (1.0.x, for example) differs from later versions (1.6.x and 1.8.x). Modern versions store the following information in config:

  • Botnet name (divader on the picture below)
  • Campaign name (xls_s_2010)
  • List of hardcoded C&Cs
  • RC4 key (03d5ae30a0bd934a23b6a7f0756aa504)


We have to briefly cover the BinStorage – the data format used by Zloader to communicate with C&Cs and to store various data: web injects, system information, stolen data and logs. BinStorages consists of the header and records (also called fields). Main header stores information about the number of records, data size (in bytes) and their MD5. Records have their own small headers, containing FieldID - DWORD describing the meaning of the data.

Some FieldIDs are hardcoded. For example, in FieldID=0x4E20 the last working C&C is stored. Other FieldIDs are derived from file paths (used to store stolen files).

Registry usage

Zloader modules (at least Downloaders and Backdoors) use a registry to store various data necessary for their work. The ROOT_KEY for this data is HKEY_CURRENT_USER\Software\Microsoft\

The most important and interesting data structure, stored by the Zloader in the registry is called MAIN_STRUCT. It’s subkey in the ROOT_KEY and the value name is derived from the RC4 key found in the configuration. We suppose that bots from one actor use the same RC4 key, so they can easily find and read the MAIN_STRUCT.

MAIN_STRUCT is encrypted using RC4 with the key from the configuration. It stores:

  • Registry paths to other storages, used by Zloader
  • Files and directories path, used by Zloader
  • Encryption key(s) to decrypt those storages

Files usage

Root path is %APPDATA%. Zloader creates directories with random names inside it to store modules, stolen data and logs. These paths are stored into the MAIN_STRUCT.


As was mentioned before, communication between the bot and C&C is done using BinStorages. Depending on the actual type of the message, field list may be changed, but there are 5 constant fields sent to C&C:

  • Some DWORD from the Configuration
  • Botnet name from the Configuration
  • BotID, derived from the system information
  • Debug flag from the Configuration
  • 16 random bytes

Requests are encrypted using the RC4 key from the Configuration. C&C responses are signed with RSA.

PING request

This request is used to check if C&C is alive. Response contains only random bytes sent by a bot.


This request is used to download modules by their ID from the C&C. The response is not in a BinStorage form!

GET CONFIG request

Used to receive configuration updates: new C&Cs, WebInjects, tasks for downloading etc.

C&Cs and DGA

As was shown before, built in configuration has a list of hardcoded C&Cs. Actually, these lists have not changed for years. To bypass blocking of these hardcoded C&Cs, Zloader uses DGA – Domain Generation Algorithm. In the Zloader, DGA produces 32 domains, based on the current date and RC4 key from the configuration.

There is a 3rd type of C&Cs – received in the response from the server. They’re stored into the Registry.

Downloader module

Analysis based on version, 44ede6e1b9be1c013f13d82645f7a9cff7d92b267778f19b46aa5c1f7fa3c10b

Function of Downloader is to download, install and run the next module – the Backdoor.

Main function

Just after the start of the Downloader module, junk code is started. It consists of many junk functions, which forms a kind of a β€œnetwork”. In the image below there is a call graph from just a single junk function. These functions also trying to read, write and delete some *.txt files %TEMP%. The purpose of this is to delay the execution of the payload and, We suppose, to complicate the emulation, debugging and analysis.

The second and the last task of the Main function is to start msiexec.exe and perform the PE injection of the code into it. Injected data consists of two buffers: the big one, where the Downloader is stored in the encrypted form and the small one (0x42 bytes) with decryption code. Just after the injection Downloader terminates himself.

Injected code

Control flow passed to the small buffer, which decrypts the Downloader in the address space of msiexec.exe After the decryption, Downloader begins to execute its main task.Β 

First of all, the injected code tries to read MAIN_STRUCT from the registry. If this fails, it thinks it was not installed on this system and the installation process begins: MAIN_STRUCT is created, Downloader module is copied into %APPDATA% and added to the autorun key HKCU\Software\Microsoft\Windows\CurrentVersion\Run with random value name.

In any case, the Backdoor module is requested from the disk or from the network and executed.

Backdoor module

Analysis based on version, c7441a27727069ce11f8d54676f8397e85301b4d65d4d722c6b239a495fd0282

There are actually two Backdoor modules: for 32-bit systems (moduleID 0x3EE) and for 64-bit systems (moduleID 0x3E9). Downloader always requests a 32-bit Backdoor.

Backdoors are much more complicated than Downloaders. If we compare the size of our samples (after unpacking), Backdoor will be twice bigger.

Key Backdoor abilities:

  • Starting VNC module
  • Injecting WebInjects into the pages visited using browsers
  • Downloading and execute arbitrary file
  • Keylogging
  • Making screenshots
  • Stealing files and sending to C&C

Stealing files

The largest group of software from which Zloader steal files is crypto wallets:

  • Electrum
  • Ethereum
  • Exodus cryptowallet
  • Zcash
  • Bitcoin-Qt
  • Etc.

It also steals data from browsers: cookies from Chrome, Firefox and IE; saved logins from Chrome. And, finally, it is able to steal accounts information from Microsoft Outlook.


To achieve his goals, Zloader performs WinAPI hooking. In order to perform it, Backdoor module enumerates processes and injects itself into the following ones:

  • explorer.exe
  • msiexec.exe
  • iexplore.exe
  • firefox.exe
  • chrome.exe
  • msedge.exe

64-bit version of Backdoor is injected into 64-bit processes, 32-bit version – into 32-bit processes.

Injected code hooks the following WinAPI functions:

  • NtCreateUserProcess
  • NtCreateThread
  • ZwDeviceIoControlFile
  • TranslateMessage
  • CertGetCertificateChain
  • CertVerifyCertificateChainPolicy

Hooks might be divided in 3 groups, depending on the purpose:

  1. NtCreateUserProcess and NtCreateThread are hooked to inject a Backdoor module to newly created threads and processes.
  2. ZwDeviceIoControlFile, CertGetCertificateChain and CertVerifyCertificateChainPolicy are hooked to support WebInjection mechanism
  3. TranslateMessage is hooked to log the keys pressed and to create screenshots

Web Injecting

First of all, browsers must have a Backdoor module injected. At this moment, there are multiple instances of Backdoor Modules running in the system: one, started by Downloader which is β€œMain Instance” and others, running in browsers. Main Instance starts Man-in-the-browser proxy, other modules hooks ZwDeviceIoControlFile and cert-related WinAPIs (see above). Proxy port number is stored in the BinStorage structure into the Registry, so it is synchronized between Backdoor instances.

Hooked ZwDeviceIoControlFile function is waiting for IOCTL_AFD_CONNECT or IOCTL_AFD_SUPER_CONNECT and routing connections to the proxy. Hooked cert-related functions inform browsers what everything is good with certificates.

Botnets, Campaigns and their activity

Most active botnets and campaigns use RC4 key 03d5ae30a0bd934a23b6a7f0756aa504 and we’ll focus on them in our analysis. Samples with the aforementioned key have versions 1.x, usually 1.6.28, but some have even 1.0.x.

Botnet and Campaign names

Among botnet names it is worth mentioning the following groups:

  1. DLLobnova, AktualizacjaDLL, googleaktualizacija, googleaktualizacija1, obnovlenie19, vasja, ivan
  2. 9092zi, 9092ti, 9092ca, 9092us, 909222, 9092ge

The first one contains transliterated Slavic words and names (vasja, ivan), maybe with errors. It sheds light on the origins of bad guys – they are definitely Slavs.

Samples with botnet names from the second group were first observed in November 2021 and we found 6 botnet names from this group in the next two months. Letters after numbers, like ca and us might be country codes.

We see the same picture with campaign names: quite a big amount of Slavic words and the same 9092* group.Β 


We analyzed webinjects and can confirm that they are targeting financial companies: banks, brokerage firms, insurance companies, payment services, cryptocurrency-related services etc.

Injected code is usually small: from dozens of bytes up to 20 kb. To perform its tasks, it loads JavaScript code from external domains, controlled by bad guys. Analysis of these domains allowed us to find connections between Zloader operators and other cybercrime gangs.

Download tasks

Zloader is able to download and execute arbitrary files by the commands from his C&Cs, but for a long time we haven’t seen these commands at all. Things changed on 24 November 2021, when botnet 9092ca received a command to download and execute the file from teamworks455[.]com. This domain was mentioned in [6].

Another two download tasks contained braves[.]fun and endoftheendi[.]com


During our tracking we have noticed links to other malware families we originally thought were unrelated.

Raccoon Stealer

Two out of three download tasks contained links to Raccoon Stealer. Downloaded samples have the following sha256 hashes:

  • 5da3db74eee74412c1290393a0a0487c63b2c022e57aebcd632f0c3caf23d8bc
  • 5b731854c58c2c1316633e570c9ec82474347e64b07ace48017d0be2b6331eed

Both of them have the same Raccoon configuration with Telegram channel kumchakl1.

Moreover, Raccoon was mentioned in [6] before we received commands from C&Cs with links to Raccoon. We are lost in conjecture why Zloader operators used Raccoon Stealer? You can read our dive into Racoon stealer here.


Ursnif, also known as Gozi and ISFB is another banking malware family with similar functions.

Digital Signatures

It was quite a big surprise when we found Zloader samples and Ursnif samples signed with the same digital signature!

As an example, consider a signature:
Thumbprint 46C79BD6482E287647B1D6700176A5F6F5AC6D57.

Zloader sample signed with it has a SHA256 hash:

Signed Ursnif sample has a SHA256 hash:

It is not the only digital signature, shared among Ursnif and Zloader samples.


As we mentioned before, the first observed download command contained a link to teamworks455[.]com. We checked the TLS certificate for this site and realized that it was for another site – dotxvcnjlvdajkwerwoh[.]com. We saw this hostname on 11 November 2021 in Ursnif webinjects, it was used to receive stolen data.

Another example – aerulonoured[.]su – host used by Zloader to receive stolen data at least from August 2021. It also appeared in Ursnif webinjects in November 2021.

Third example – qyfurihpsbhbuvitilgw[.]com which was found in Zeus configuration update, received from C&C on 20 October 2021. It must be added to a C&C list and then used by Zloader bots. The same domain was found in Ursnif webinjects on 1 November 2021

And, finally, 4th example – etjmejjcxjtwweitluuw[.]com This domain was generated using DGA from key 03d5ae30a0bd934a23b6a7f0756aa504 and date – 22 September 2021. We have very strong evidence that it was active on that date as a Zloader C&C. The same host was found in Ursnif WebInjects on 1 November 2021


We are proud we could be part of the investigation as we continue our mission to make the world a safer place for everybody. We hope for a successful takedown of the Zloader botnet and prosecution of people who created and operated it.

The post Zloader 2: The Silent Night appeared first on Avast Threat Labs.

Raccoon Stealer: β€œTrash panda” abuses Telegram

9 March 2022 at 13:48

We recently came across a stealer, called Raccoon Stealer, a name given to it by its author. Raccoon Stealer uses the Telegram infrastructure to store and update actual C&C addresses.Β 

Raccoon Stealer is a password stealer capable of stealing not just passwords, but various types of data, including:

  • Cookies, saved logins and forms data from browsers
  • Login credentials from email clients and messengers
  • Files from crypto wallets
  • Data from browser plugins and extension
  • Arbitrary files based on commands from C&C

In addition, it’s able to download and execute arbitrary files by command from its C&C. In combination with active development and promotion on underground forums, Raccoon Stealer is prevalent and dangerous.

The oldest samples of Raccoon Stealer we’ve seen have timestamps from the end of April 2019. Its authors have stated the same month as the start of selling the malware on underground forums. Since then, it has been updated many times. According to its authors, they fixed bugs, added features, and more.


We’ve seen Raccoon distributed via downloaders: Buer Loader and GCleaner. According to some samples, we believe it is also being distributed in the form of fake game cheats, patches for cracked software (including hacks and mods for Fortnite, Valorant, and NBA2K22), or other software. Taking into account that Raccoon Stealer is for sale, it’s distribution techniques are limited only by the imagination of the end buyers. Some samples are spread unpacked, while some are protected using Themida or malware packers. Worth noting is that some samples were packed more than five times in a row with the same packer!Β 

Technical details

Raccoon Stealer is written in C/C++ and built using Visual Studio. Samples have a size of about 580-600 kB. The code quality is below average, some strings are encrypted, some are not.

Once executed, Racoon Stealer starts checking for the default user locale set on the infected device and won’t work if it’s one of the following:

  • Russian
  • Ukrainian
  • Belarusian
  • Kazakh
  • Kyrgyz
  • Armenian
  • Tajik
  • Uzbek

C&C communications

The most interesting thing about this stealer is its communication with C&Cs. There are four values crucial for its C&C communication, which are hardcoded in every Raccoon Stealer sample:

  • MAIN_KEY. This value has been changed four times during the year.
  • URLs of Telegram gates with channel name. Gates are used not to implement a complicated Telegram protocol and not to store any credentials inside samples
  • BotID – hexadecimal string, sent to the C&C every time
  • TELEGRAM_KEY – a key to decrypt the C&C address obtained from Telegram Gate

Let’s look at an example to see how it works:
447c03cc63a420c07875132d35ef027adec98e7bd446cf4f7c9d45b6af40ea2b unpacked to:

  1. First of all, MAIN_KEY is decrypted. See the decryption code in the image below:

In this example, the MAIN_KEY is jY1aN3zZ2j. This key is used to decrypt Telegram Gates URLs and BotID.

  1. This example decodes and decrypts Telegram Gate URLs. It is stored in the sample as: Rf66cjXWSDBo1vlrnxFnlmWs5Hi29V1kU8o8g8VtcKby7dXlgh1EIweq4Q9e3PZJl3bZKVJok2GgpA90j35LVd34QAiXtpeV2UZQS5VrcO7UWo0E1JOzwI0Zqrdk9jzEGQIEzdvSl5HWSzlFRuIjBmOLmgH/V84PCRFevc40ZuTAZUq+q1JywL+G/1xzXQdYZiKWea8ODgaN+4B8cT3AqbHmY5+6MHEBWTqTsITPAxKdPMu3dC9nwdBF3nlvmX4/q/gSPflYF7aIU1wFhZxViWq2
    After decoding Base64 it has this form:

Decrypting this binary data with RC4 using MAIN_KEY gives us a string with Telegram Gates:

  1. The stealer has to get it’s real C&C. To do so, it requests a Telegram Gate, which returns an HTML-page:

Here you can see a Telegram channel name and its status in Base64: e74b2mD/ry6GYdwNuXl10SYoVBR7/tFgp2f-v32
The prefix (always five characters) and postfix (always six characters) are removed and it becomes mD/ry6GYdwNuXl10SYoVBR7/tFgp The Base64 is then decoded to obtain an encrypted C&C URL:

The TELEGRAM_KEY in this sample is a string 739b4887457d3ffa7b811ce0d03315ce and the Raccoon uses it as a key to RC4 algorithm to finally decrypt the C&C URL: http://91.219.236[.]18/

  1. Raccoon makes a query string with PC information (machine GUID and user name), and BotID
  2. Query string is encrypted with RC4 using a MAIN_KEY and then encoded with Base64.
  3. This data is sent using POST to the C&C, and the response is encoded with Base64 and encrypted with the MAIN_KEY. Actually, it’s a JSON with a lot of parameters and it looks like this:

Thus, the Telegram infrastructure is used to store and update actual C&C addresses. It looks quite convenient and reliable until Telegram decides to take action.Β 


The people behind Raccoon Stealer

Based on our analysis of seller messages on underground forums, we can deduce some information about the people behind the malware. Raccoon Stealer was developed by a team, some (or maybe all) members of the team are Russian native speakers. Messages on the forum are written in Russian, and we assume they are from former USSR countries because they try to prevent the Stealer from targeting users in these countries.

Possible names/nicknames of group members may be supposed based on the analysis of artifacts, found in samples:

  • C:\Users\a13xuiop1337\
  • C:\Users\David\Β 


Raccoon Stealer is quite prevalent: from March 3, 2021 - February 17, 2022 our systems detected more than 25,000 Raccoon-related samples. We identified more than 1,300 distinct configs during that period.

Here is a map, showing the number of systems Avast protected from Raccoon Stealer from March 3, 2021 - February 17, 2022. In this time frame, Avast protected nearly 600,000 Raccoon Stealer attacks.

The country where we have blocked the most attempts is Russia, which is interesting because the actors behind the malware don’t want to infect computers in Russia or Central Asia. We believe the attacks spray and pray, distributing the malware around the world. It’s not until it makes it onto a system that it begins checking for the default locale. If it is one of the language listed above, it won’t run. This explains why we detected so many attack attempts in Russia, we block the malware before it can run, ie. before it can even get to the stage where it checks for the device’s locale. If an unprotected device that comes across the malware with its locale set to English or any other language that is not on the exception list but is in Russia, it would stiIl become infected.Β 

Screenshot with claims about not working with CIS

Telegram Channels

From the more than 1,300 distinct configs we extracted, 429 of them are unique Telegram channels. Some of them were used only in a single config, others were used dozens of times. The most used channels were:

  • jdiamond13 – 122 times
  • jjbadb0y – 44 times
  • nixsmasterbaks2 – 31 times
  • hellobyegain – 25 times
  • h_smurf1kman_1Β  – 24 times

Thus, five of the most used channels were found in about 19% of configs.

Malware distributed by Raccoon

As was previously mentioned, Raccoon Stealer is able to download and execute arbitrary files from a command from C&C. We managed to collect some of these files. We collected 185 files, with a total size 265 Mb, and some of the groups are:

  • Downloaders – used to download and execute other files
  • Clipboard crypto stealers – change crypto wallet addresses in the clipboard – very popular (more than 10%)
  • WhiteBlackCrypt Ransomware

Servers used to download this software

We extracted unique links to other malware from Raccoon configs received from C&Cs, it was 196 unique URLs. Some analysis results:

  • 43% of URLs have HTTP scheme, 57% – HTTPS.
  • 83 domain names were used.
  • About 20% of malware were placed on Discord CDN
  • About 10% were served from aun3xk17k[.]space


We will continue to monitor Raccoon Stealer’s activity, keeping an eye on new C&Cs, Telegram channels, and downloaded samples. We predict it may be used wider by other cybercrime groups. We assume the group behind Raccoon Stealer will further develop new features, including new software to steal data from, for example, as well as bypass protection this software has in place.



The post Raccoon Stealer: β€œTrash panda” abuses Telegram appeared first on Avast Threat Labs.

Research shows over 10% of sampled Firebase instances open

1 September 2021 at 13:46

Firebase is Google’s mobile and web app development platform. Developers can use Firebase to facilitate developing mobile and web apps, especially for the Android mobile platform.

At the end of July 2021 we did research into open Firebase instances.

In that research, we found about 180,300 Firebase addresses in our systems and found approximately 19,300 of those Firebase DBs, 10.7% of the tested DBs were open, exposing the data to unauthenticated users, due to misconfiguration by the app developers. This is quite a large percentage.

These addresses were statically and dynamically extracted from different sources, mainly from Android apps.

We took these Firebase addresses and examined them to see how many were open. In our testing, we looked only for instances that were open for β€œRead” access without credentials. We didn’t test for write access for obvious reasons.

These open Firebase instances put the data stored and used by the apps developed using it at risk of theft, because apps can store and use a variety of information, some of it including personally identifiable information (PII) like names, birthdates, addresses, phone numbers, location information, service tokens and keys among other things. When developers use bad practices DBs can even contain plaintext passwords. This means that potentially the personal information of over 10% of users of Firebase-based apps can be at risk.

An example of β€œleaking” instance

Of course, our testing shows only a subset of all existing Firebase instances. However, we believe that this 10.7% number can be a reasonable representative sample of the total number of Firebase instances that are currently open.

We took our findings to Google and asked them to inform developers of the apps we identified as open as well as contacting some of the developers ourselves.. Google has several features to improve data protection in Firebase, including notifications and regular emails about potential misconfigurations.

While we appreciate Google’s actions based on our findings, we also believe it’s important to inform Firebase developers about potential risk of misconfigured DBs and follow the best practices that Google has provided at https://firebase.google.com. This also once again underscores the importance of making security and privacy a key part of the entire app development process, not just as a later β€œbolt on”.

Most importantly, we want to urgeΒ  all developers to check their databases and other storage for possible misconfigurations to protect users’ data and make our digital world safer.

The post Research shows over 10% of sampled Firebase instances open appeared first on Avast Threat Labs.