Babadeda Crypter Targeting Crypto, NFT, and DeFi Communities

The cryptocurrency market is now worth more than $2.5 trillion. Unfortunately, this fact is not lost on threat actors. As well as using cryptocurrency themselves to extract ransoms, cybercriminals are now also tailoring malware to exploit the booming market for NFTs and crypto games. In a discovery of critical importance to anyone familiar with this space, Morphisec Labs has encountered a new campaign of malware targeting cryptocurrency enthusiasts through Discord. 

Crucially, the crypter that this campaign deploys, which we have termed Babadeda (a Russian language placeholder used by the crypter itself which translates to “Grandma-Grandpa”), is able to bypass signature-based antivirus solutions. Although some variants of this crypter have been noted by other vendors, Morphisec is the first to fully disclose how it works.

For victims, this makes infections highly likely — and dangerous. We know that this malware installer has been used in a variety of recent campaigns to deliver information stealers, RATs, and even LockBit ransomware. Fortunately, however, even as the threat level for cryptocurrency users rises, we also know that Morphisec’s Moving Target Defense technology is capable of both seeing and stopping Babadeda. 

In this blog post, we will explore how Babadeda is being delivered, what an in-depth technical analysis of this malware tells us about it, and how it can be stopped.

Crypto and NFT Communities Are Prime Targets

Since May 2021, we have observed several malware distribution campaigns. However, many of the recent infections we have seen appear to be related to a sophisticated campaign that exclusively targets the Crypto, NFT, and DeFi communities. It is precisely for this reason, as well as the fact that NFTs are rising in popularity, that we have decided to take a look at this particular campaign distribution in more detail. 

For those who are not familiar with NFTs (Non-fungible tokens): the term refers to unique tokens that provide proof of ownership on data that is stored on the blockchain technology. In recent years, NFTs have exploded in popularity, and are now starting to enter the mainstream consciousness. Naturally, this growing trend in the crypto space has opened up a new vector for threat actors to exploit.  

The Delivery Chain

The vast majority of today's NFT and crypto communities are based on Discord (a group chatting platform) channels. Discord channels are publicly accessible and allow users to send private messages to one another within a channel. 

In the campaign that we observed, a threat actor took advantage of these features in order to phish victims. The threat actor sent users a private message inviting them to download a related application that would supposedly grant the user access to new features and/or additional benefits. Because the actor created a Discord bot account on the official company discord channel, they were able to successfully impersonate the channel’s official account.

Below is an example of a phishing message that targeted users of “Mines of Dalarna”, a PC game built on the blockchain.

Figure 1: Fake message on the discord channel.

If a user clicks on the URL within the message, it will direct them to a decoy site. There, the user will be encouraged to download a malicious installer that embeds the Crypter with the payload.

Figure 2: Original and decoy sites comparison

As you can see from the example above, the threat actor took extended measures to ensure that the delivery chain looks legitimate even to technical users. Typically:

• Cybersquatting - the domain names of the decoy sites look a lot like the domain names of the original sites  Threat actors will usually remove/add a letter from/to the domain name or change the top-level domain.
• The domains are signed with a certificate (via LetsEncrypt), which enables an HTTPS connection.
• The UI of the decoy pages is very similar to the UI of the original pages.
• Upon clicking “Download APP”, the site will generally navigate to /downland.php, which will redirect the download request to a different domain (this makes it less likely that someone will detect a decoy site).

Interestingly, on one of these decoy sites, we noticed an HTML object written in Russian. This suggests that the threat actor's origins may be in a Russian-speaking country since they most likely forgot to translate the HTML object from their native language into English. 

Figure 3: Lost in translation?

Decoy Site Examples

The following table shows a few examples of the decoy sites used in the campaigns we have observed.

We have identified at least 82 domains created between July 24, 2021, and November 17, 2021, with the following registration time distribution (credit to @msuiche).

The Payloads

The following table tracks the RATs used by this specific campaign’s threat actor:

Technical Analysis of the Babadeda Crypter

Figure 4: Execution flow diagram

During our research, we found different variants of the same Crypter — all of which contain the same main execution flow (denoted by the figure above). While investigating the Crypter, we saw how important it was for the threat actor to hide its malicious intentions inside legitimate applications in order to avoid detection. The following figure emphasizes the complexity of the evasive techniques that are implemented in the Crypter.

Figure 5: Low detection rate on VT

The Installer

Once downloaded and executed, the malicious installer copies its compressed files into a newly created folder with a legitimate-looking name  (i.e., IIS Application Health Monitor) in one of the following directory paths:

C:\Users\<user>\AppData\Roaming\
C:\Users\<user>\AppData\Local\

The malicious files are copied along with many other open-source or free application-related files. At first glance, the files within the directory may seem legitimate. However, looking at these files carefully it becomes apparent that some of them are suspicious and should be inspected, as shown by the figure below. 

Figure 6: The compressed files (malware files selected with stage numbers)

Crypter Execution

After dropping the mentioned files, the Installer starts execution via the main executable (number 1 in the figure above). 

We have noticed that at this point, some variants display a fake error message that stops the execution until the user interacts with the message. This fake message might be used as a security solutions evasion technique. Alternatively, its role may be to deceive the user into thinking that the application has failed to execute, even as it silently continues the malicious execution in the background.

Figure 7: Fake error message

By analyzing the two different variants, we can see the implementation of this message box:

Figure 8: Comparison between variants

As we can see in the figure below, the function’s code is much longer compared to the actual DLL loading code. That’s because the actor has implanted its actions within a legitimate application code in order to confuse analysts, obfuscate its real intentions, and make it harder for antivirus solutions to detect.

Figure 9: Left - the full function. Right - the DLL loading code

The Shellcode's Loader DLL

The threat actor generally embeds the next stages of the execution inside an additional file, usually an XML or a PDF file. Nonetheless, we have also observed additional file types such as JavaScript, Text, and PNG.

Here, just like before, the actor embeds the malicious code inside different legitimate codes. We have extracted the relevant sections to clearly demonstrate the malware’s activity:

Figure 10: Exported function logic

The malicious logic starts by reading the additional file (in this case an XML file) and calling kernel32!Sleep for 35 seconds (the duration changes between variants). Next, it loads this entire file to memory and starts its parsing task. 

The first piece that is parsed from the file is a shellcode located in a pre-calculated offset (in this case, 0x88D8C and overwrites the executable at offset 0x1600).

Figure 11: The shellcode bytes inside the XML file

The executable .text section’s characteristics are configured to RWE (Read-Write-Execute) -- that way the actor doesn't need to use VirtualAlloc or VirtualProtect in order to copy the shellcode and transfer the execution. This helps with evasion since those functions are highly monitored by security solutions. Once the shellcode is copied to the executable, the DLL calls to the shellcode’s entry point (shellcode_address).

Persistency Implementation

If the crypter is configured to install persistence, the loader DLL will execute a new thread that loads another DLL (from the compressed files) that will handle this task.

Figure 12: New thread creation for calling the persistent mechanism

The newly loaded DLL will either use one of the following logics or both of them to implement the persistency:

• Write a.lnk file in the startup folder that executes the Crypter’s main executable.

Figure 13: .lnk file persistence implementation

• Write a registry Run key that executes the Crypter’s main executable.

Figure 14: registry run key persistence implementation

The Decryption Shellcode

The XML file (or any other file type used by the crypter) contains the following components:

1. The first shellcode (referred to in this section).
2. An encrypted additional shellcode (referred to in the next section, the Loader shellcode)
3. An encrypted payload.

The Decryption shellcode has three main tasks: first, it extracts the Loader shellcode and the payload, then it decrypts them, and finally, it transfers the execution to the decrypted Loader shellcode.

Figure 15: Decryption shellcode execution flow

The Decryption shellcode begins with dynamically locating the configuration structure by searching for a sequence of six or more identical bytes. This configuration holds pointers to the loader shellcode and the final payload; these are encrypted and split inside the XML.

Figure 16: Configuration and XML file’s structures

Based on this, we can identify the configuration inside the XML file:

Figure 17: Configuration structure

Using this configuration the malware iterates over each chunk copies it, and decrypts it using the denoted decryption key (the configuration changes between samples).

Then, the shellcode searches for two DWORD placeholders, 0xBABADEDA and 0xDEADBEAF. It replaces the first placeholder with the address of the decrypted payload and the latter with the size of the payload. This data is used in the next stage, the Loader shellcode.

The Loader Shellcode

The purpose of the Loader shellcode is to inject the decrypted payload within the currently running process (itself). 

We can divide the loading mechanism into three stages: initialization, injection, and correction.

Initialization

This stage is responsible for setting the relevant data that will be used during the injection and correction stages. 

Figure 18: Extracting the data for injection and correction stages

To start initializing, the Loader first saves the decrypted payload address and payload size according to the placeholder’s addresses. Next, it parses the PE headers of the payload to extract the image size and the entry point according to the current executable’s base address. The Loader parses the _PEB structure in order to find the base address of the current executable and the LDR_DATA_TABLE_ENTRY which will be used later. Finally, it dynamically loads the VirtualProtect function using a pre-calculated hash value (0xF1C25B45 in our case).

Injection

This stage is pretty straightforward. Within it, the Loader overwrites the current PE with the final payload’s PE. It does so by copying the PE headers and each section according to the current executable’s base address.

Figure 19: Change headers protection and clear memory bytes for the new PE

Once previous bytes have been cleared, the Loader copies the new PE headers to the base address and each section to the relevant location according to the IMAGE_SECTION_HEADER.

Correction

The final stage is responsible for fixing the import address table and relocation table of the newly injected PE.

Figure 20: Fix tables and remove altering evidence

• mw_construct_IAT 
• Load GetModuleHandleA, LoadLibraryA and GetProcAddress functions by hash (0x9FE4FCE1, 0x85557334 and 0xF23B576D respectively).
• Iterate over the IAT of the new PE.
• Load each function and update its address.
• mw_construct_RELOC 
• Calculate the delta between the previous image base and the current one.
• Iterate over each entry in the relocation table.
• Add the delta to the entry value.

In addition to fixing the import address and relocation tables, the Loader removes evidence of injection by using the following methods:

1. Update the LDR data table entry to match the injected PE.
2. Remove the injected PE headers from memory.

These steps attempt to evade memory scanners that seek mismatching LDR data and in-memory PEs.

Finally, the malware jumps to the entry point of the newly injected PE with the original command-line arguments.

Conclusion

As demonstrated above, Babadeda is a highly dangerous crypter. Targeting cryptocurrency users through trusted attack vectors gives its distributors a fast-growing selection of potential victims. Once on a victim's machine, masquerading as a known application with a complex obfuscation also means that anyone relying on signature-based malware effectively has no way of knowing Babadeda is on their machine — or of stopping it from executing.

Mitigating the threat posed by Babadeda requires securing the device memory it targets. Morphisec does this through Moving Target Defense, a technology that morphs process memory trapping crypters like Babadeda before they are able to deploy. 

IOCs

The sample used in the blog post:

YARA Rule

rule BABADEDA_Crypter

{

       meta:

                description = "Detects BABADEDA Crypter"

                author = "Morphisec labs"

                reference = "https://blog.morphisec.com/the-babadeda-crypter-targeting-crypto-nft--defi-communities"

       strings:

                $entry_shellcode = {55 8B EC 83 EC 58 53 E8 F8 03 00 00 89 45 FC 8B 45 FC 83 C0 11 89 45 CC 8B 45 FC 8B 40 09 8B 4D CC 8D 04}

          $placeholder_1 = {8138DADEBABA} 

          $placeholder_2 = {8138AFBEADDE}

       condition:

       $entry_shellcode and all of ($placeholder_*)

}

Decoy Domains

aave-v3[.]com
abracodabra[.]net
alchemixfi[.]com
apeswaps[.]net
app.sushi-v3[.]com
arbitrums[.]com
artblocks[.]us
astar-network[.]com
avalanche-network[.]com
avax-bridge[.]com
avax-bridge[.]net
avax-network[.]net
avax.wallet-bridge[.]net
avax.wallet-network[.]net
avax.wallet-network[.]org
babydogescoin[.]com
boredpeyachtclub[.]com
bridge-avax[.]com
bridge-avax[.]net
bridge-avax[.]us
c-nft[.]net
casper-network[.]com
compoundfinance[.]net
cryptoblade[.]net
decentralands[.]net
diviprojects[.]com
dydxexchange[.]net
galagamesapp[.]com
hedera[.]run
illuviums[.]com
keep-network[.]net
klimadao[.]net
larva-labs[.]net
larvaslab[.]com
looprings[.]net
luckybuddhaluckyclub[.]com
mangomarkets[.]net
mineofdalarnia[.]net
monstasinfinite[.]net
moonebeam[.]com
near-protocol[.]com
network-avax[.]net
network-avax[.]org
nft-opensee[.]com
olympusdao[.]fund
openseaio[.]net
openseea[.]net
optinism[.]net
polkadot-network[.]com
projectseeds[.]net
projectsserum[.]net
rareble[.]net
rocketspool[.]net
secretswaps[.]net
sia-tech[.]net
solanarts[.]com
solsoulnft[.]com
sushi-app[.]com
sushi-v3[.]com
sushi-v3app[.]com
terra-money[.]net
thetatokenfund[.]com
wallet-avalanche[.]com
wallet-avalanche[.]net
wallet-avalanche[.]org
wallet-avax[.]com
wallet-avax[.]info
wallet-avax[.]net
wallet-bridge[.]net
wallet-network[.]net
wallet-network[.]org
wa let.bridge-avax[.]us
wallet.network-avax[.]org
wonderlaned[.]com
zed-run[.]net

Hashes

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Crypter hashes

amadey stealer

4d02224a7dadfc2d8a1343fdc51e4634a98bd073f867bfd091e667efd112108a
384292cad1c05552ccbd691de48865ce75375f7e601db66b3f5cad0f8f294d6c
5dd0e9ef811c199a06758d65b66d051d3b0057971b021df0928ede727fe17371
e312af68203fd80a2dd86a69460941ce29709424310abffd66fd7323a2b8ef6e

Cryptbot

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75837a43d3df5f8ec3117279edcfc255c69be9aaf2eed9d0d3cc98bf3b06ae01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lockbit
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ursnif

04595c3111276f02b6dc2ece0778cb5829c086484aeafa24e0aac3d8479deb4b
e2c83783d6ab57ac91d99bfb9d607d0b5537e305661406bbf2347c3af92d3464
676a540a91b9ffb4a18af0f4355561f3579ee4cbbf0740a80e482af92e8cdc07
716ce7fe411f352686b4071074aa96e1456ab7a67445b3cf1c475e18a4e5ac25
ceba6a7f9a2c25a35090470c6209aefed808786c47194a18415a7898390c20cb
e203345d8120bd6d29e667bbceb92083ebb55e36b21cd22d669aa2f91830a656

smokeloader

79ae89733257378139cf3bdce3a30802818ca1a12bb2343e0b9d0f51f8af1f10
1ae5c809ea8fabce9c699c87416d73ba5ab619accef6deeb26c2c38f39323181
ee8f0ff6b0ee6072a30d45c135228108d4c032807810006ec77f2bf72856e04a

fickerstealer

bd8d1264a88d5cdd701a4ee909b70beaec39d216c988b33bfb30f25aee3540ee
1f53d6f4fb02c8663b9d377570953d07c56df297674b7c3847d1697f0e5f8165
cf88923b7d0287884870af999a8d64f90c7deeb4c4d09feed406472ff259b30d

Metasploit Reverse HTTP

b8990f204ca595e23562aa8063fd163651771626ba4acf45890f25315616fc1e

quasarrat

e8a8581cd3594a3937762f90d20ab889e7868bb88e9249f96222bd48643d7dea