Shedding mild on AceCryptor and its operation

Statistics and packed households overview

Because the first recognized appearances of AceCryptor again in 2016, many malware authors have used the providers of this cryptor, even the best-known crimeware like Emotet, again when it didn’t use its personal cryptor. Throughout 2021– 2022 ESET detected greater than 80,000 distinctive samples of AceCryptor. Due to the excessive variety of completely different malware households packed inside, we assume that AceCryptor is bought someplace as a CaaS. If we consider the variety of distinctive recordsdata detected: regardless that we don’t know the precise pricing of this service, we assume that the positive factors to the AceCryptor authors aren’t negligible.

Due to the excessive quantity of samples over previous years, the next stats are primarily based solely on samples detected throughout 2021 and 2022. As could be seen in Determine 1, detection hits have been distributed fairly evenly all through these two years, which is to be anticipated from malware utilized by numerous menace actors who don’t synchronize their campaigns.

Determine 1. Variety of AceCryptor detections throughout the years 2021 and 2022 (7-day transferring common)

After trying on the malware packed by AceCryptor, we discovered over 200 ESET detection names. Now, in fact one malware household could have a number of detection names throughout the person variants, due to updates or adjustments in obfuscation – e.g., MSIL/Spy.RedLine.A and MSIL/Spy.RedLine.B are each detections for the RedLine Stealer malware. Detection names for another malware usually are not by household, however by class (e.g., ClipBanker or Agent), as a result of a variety of unpacked malware samples are generic clipboard stealers, trojans, and so forth that aren’t that widespread and/or are simply barely modified variants of different recognized malware revealed in numerous public repositories. After grouping, we are able to conclude that after unpacking, among the many malware households discovered are SmokeLoader, RedLine Stealer, RanumBot, Raccoon Stealer, STOP ransomware, Amadey, Fareit, Pitou, Tofsee, Taurus, Phobos, Formbook, Danabot, Warzone, and plenty of extra… Determine 2 exhibits an summary of the portions of samples belonging to among the well-known and prevalent malware households packed by  AceCryptor.

Determine 2. Malware households packed inside AceCryptor throughout 2021 and 2022

Monitoring actions of CaaS suppliers equivalent to AceCryptor is useful for monitoring of malware that makes use of their providers. For example, contemplate a RedLine Stealer that was first seen in Q1 2022. As could be seen in Determine 3, RedLine Stealer distributors used AceCryptor because the starting of RedLine Stealer’s existence and nonetheless proceed to take action. Thus, having the ability to reliably detect AceCryptor (and different CaaS) not solely helps us with visibility of latest rising threats, but additionally with monitoring the actions of menace actors.

Determine 3. Incidents of RedLine Stealer in AceCryptor samples (7-day averages)

Victimology

As needs to be anticipated from the number of malware packed inside AceCryptor and the variety of pursuits of various malware authors, AceCryptor is seen in every single place on the earth. Throughout 2021 and 2022, ESET telemetry detected over 240,000 detection hits of this malware, which quantities to over 10,000 hits each month. In Determine 4 you’ll be able to see the nations with the best numbers of detections throughout 2021 and 2022.

Determine 4. Heatmap of nations affected by AceCryptor in response to ESET telemetry

Throughout 2021 and 2022, ESET merchandise detected and blocked malware variants packed by AceCryptor on greater than 80,000 prospects’ computer systems. We additionally found over 80,000 distinctive samples of AceCryptor. Now, in fact that any pattern might be detected at a number of computer systems or one laptop was protected a number of instances by ESET software program, however the variety of distinctive hashes simply exhibits how actively the authors of AceCryptor work on its obfuscation and detection evasion. We’ll dive deeper into the technical particulars of AceCryptor’s obfuscations within the Technical evaluation a part of this blogpost.

What’s value mentioning right here is that regardless that the variety of distinctive samples of AceCryptor may be very excessive, the variety of distinctive samples packed inside is fewer than 7,000. This exhibits the diploma to which many malware authors depend on the providers of a cryptor and the way handy it’s for them to pay for this sort of service slightly than make investments their time and assets to implement their very own cryptor resolution.

Distribution

As a result of AceCryptor is utilized by a number of menace actors, malware packed by additionally it is distributed in a number of alternative ways. In line with ESET telemetry, units have been uncovered to AceCryptor-packed malware primarily by way of trojanized installers of pirated software program, or spam emails containing malicious attachments.

One other method that somebody could also be uncovered to AceCryptor-packed malware is by way of different malware that downloaded new malware protected by AceCryptor. An instance is the Amadey botnet, which we have now noticed downloading an AceCryptor-packed RedLine Stealer.

We’d like to notice that this works each methods and among the malware households protected by AceCryptor may also obtain new, further malware.

Technical evaluation

At present AceCryptor makes use of a multistage, three-layer structure. There are two recognized variations of the primary layer which are presently in use – a model that makes use of TEA (Tiny Encryption Algorithm) to decrypt the second layer and a model that makes use of a linear congruential generator (LCG) from Microsoft Visible/Fast/C++ to decrypt the second layer. The second layer is shellcode that performs defensive methods, then decrypts and launches the third layer. Lastly, the third layer is extra shellcode that additionally performs some anti-investigation methods, and its job is to launch the payload. There are two recognized variations of the third layer: one model performs course of hollowing, whereas the opposite makes use of a reflective loader and overwrites its personal picture with the PE of the ultimate payload.

Determine 5. Structure of AceCryptor

Layer 1

Regardless that there are two variations of Layer 1, they work very equally. Their foremost duties could be summarized as follows:

1. Load encrypted Layer 2 into allotted reminiscence.
2. Decrypt Layer 2.
3. Name or leap to Layer 2.

Crucial a part of this stage is the obfuscations. All through the years, new obfuscations have been added – to the purpose the place nearly each a part of the binary is one way or the other randomized and obfuscated. It will trigger massive issues for somebody making an attempt to provide you with YARA guidelines or static detections.

Loops

The authors leverage loops for a number of obfuscations. The primary and most easy method is to make use of loops with junk code simply to make evaluation harder. Now we have seen utilization of junk code since 2016 after we registered the primary samples of AceCryptor. These loops are crammed with many API calls that not solely decelerate analysts who don’t know what is going on, but additionally overwhelm the logs of sandboxes that hook API calls, thereby making them ineffective. The loops could include many MOV directions and math operations, once more simply to confuse analysts and thereby lengthen the time of research.

Determine 6. AceCryptor’s obfuscations with loops and hiding essential elements of code

The second utilization of loops is to achieve delay. Now we have noticed that some variations of AceCryptor launch Layer 2 nearly instantly, however others include loops which are so time demanding that it may decelerate the execution even for tens of minutes: delaying the execution of some elements of malware is a recognized method, however utilization of API calls like Sleep could already elevate some flags. Even when not, some sandboxes like Cuckoo Sandbox implement sleep-skipping strategies to keep away from the delay and proceed to the fascinating elements. Implementing delays by way of loops and execution of junk code can also be a complication throughout dynamic evaluation, as a result of the analyst has to establish which loops are junk loops and thus could be skipped.

A 3rd obfuscation method utilizing loops consists of hiding essential operations in them. Among the many junk loops, there are some that look ahead to a sure iteration and simply throughout that iteration one thing occurs. Often, an API is loaded utilizing GetProcAddress, which is later used or some fixed just like the offset of the encrypted knowledge is unmasked. If that exact iteration of a loop doesn’t occur, the pattern will later crash. This, together with junk code, signifies that to dynamically analyze the malware, one first has to investigate which loops or iterations of loops could be skipped, and which can’t. Because of this the analyst can both spend time analyzing junk code or ready till all of the junk code is executed. In Determine 6 you’ll be able to see two loops the place the primary accommodates an operation essential for subsequent execution, and the opposite is simply filled with junk code. After all, this might not be (and it isn’t within the majority of the samples) that simply seen amongst all of the loops, particularly if the loops with the essential operations additionally include junk code.

Randomization – Thou shalt not YARA

One other essential a part of the primary layer is randomization. Junk code and the loops talked about beforehand are randomized in every pattern, in such a method that:

• the variety of iterations adjustments,
• API calls change,
• the variety of API calls change, and
• junk arithmetic or MOV directions change.

All this randomization may also fairly complicate identification of the decryption algorithm and keys. In Determine 7 and Determine 8 you’ll be able to see the unique, unobfuscated and the obfuscated model of the TEA algorithm. Within the obfuscated model there usually are not solely junk arithmetic directions, but additionally some elements of the algorithm are outlined into subroutines and recognized constants (sum and delta in Determine 7) are masked, simply to make appropriate identification of the algorithm unlikely or definitely harder.

Determine 7. TEA decryption operate – not obfuscated

Determine 8. TEA decryption operate – obfuscated

Code will not be the one factor that’s randomized. The encrypted Layer 2 and its decryption key are presently normally saved within the .textual content or .knowledge part, however they’re hidden utilizing some offsets that change between the samples. Additionally, after efficiently decrypting Layer 2: in some samples the code of Layer 2 is in the beginning of the decrypted knowledge, however there are samples the place you find yourself with a block of random knowledge in the beginning and you’ll want to know the proper offset to search out the start of Layer 2’s code.

AceCryptor authors additionally randomize the next traits:

• The PDB path at all times begins with C:, however the remainder of the trail is random.
• Assets with random names and content material, as could be seen in Determine 9. The authors of AceCryptor fill samples with randomly generated assets containing randomly generated knowledge. We assume that that is executed to make samples much less suspicious and make finding the precise encrypted knowledge harder. Assets can include:
  • String tables
  • Menus
  • Bitmaps
  • Binary knowledge
• Strings used within the code.
• Icons – regardless that icons which are utilized in many samples look related, they’re simply barely modified/randomized to be distinctive.
• Random dummy part names.
• Reminiscence allocation capabilities for Layer 2 knowledge – GlobalAlloc, LocalAlloc, and VirtualAlloc.
• Utilization of some APIs essential to code execution – they might be statically imported or obtained by way of GetModuleHandleA and GetProcAddress.

Determine 9. AceCryptor’s assets are randomly generated with randomly generated contents to make samples much less suspicious

Determine 10. AceCryptor’s random strings in assets

Earlier variations

Over time, the authors of AceCryptor received more adept at growing malware and the cryptor modified and advanced. Regardless that there have been many smaller adjustments, updates, and enhancements, among the fascinating options of the older variations of Layer 1 included the next:

• Throughout 2016 AceCryptor used a model of Layer 1 with XTEA encryption algorithm.
• Throughout 2017–2018 AceCryptor used another Layer 1 model, the place the encryption algorithm used was RC4.
• The primary (X)TEA and LCG variations of Layer 1 appeared in 2016. In contrast to the LCG model, the XTEA model shortly fell into disuse and was changed with the TEA model.
• In older variations, the encrypted Layer 2 was within the assets hidden in a BMP picture. This picture was randomly generated with random width and top, and the center of the picture was minimize out and changed with encrypted knowledge. Knowledge needed to be discovered on the appropriate offset.

Layer 2

Layer 2 of AceCryptor appeared in 2019. Till then, AceCryptor launched Layer 3 immediately from Layer 1. This layer serves as further encryption and safety of Layer 3 and, as Determine 11 illustrates, consists of three elements:

• position-independent code,
• a customized construction that we named L2_INFO_STRUCT, containing details about Layer 3, and
• the information of Layer 3

Determine 11. AceCryptor’s Layer 2 construction

As step one, AceCryptor makes use of a standard method to acquire some API operate addresses. It resolves the GetProcAddress and LoadLibraryA capabilities by utilizing the PEB_LDR_DATA to traverse by way of loaded modules, and by evaluating the hash values of their export names towards hardcoded values. As a checksum operate, AceCryptor makes use of a shl1_add operate, already applied in hashDb, which might make identification of resolved APIs quicker.

Determine 12. shl1_add hash implemented in Python

Then AceCryptor obtains a deal with for kernel32.dll utilizing LoadLibraryA and makes use of that and GetProcAddress to resolve extra APIs.

For the following steps, AceCryptor makes use of info from its customized construction L2_INFO_STRUCT (proven in Determine 13), which could be discovered proper on the finish of the position-independent code, as could be seen in Determine 11.

Determine 13. Overview of the L2_INFO_STRUCT from Layer 2

Within the subsequent steps, AceCryptor decrypts Layer 3, which is encrypted utilizing LCG from Microsoft Visible/QuickC/C++. Decryption occurs in place. If the compressionFlag is ready, AceCryptor allocates reminiscence with the VirtualAlloc API and decompresses the decrypted knowledge with the LZO_1Z decompression algorithm. After this, execution jumps into the decrypted and optionally decompressed Layer 3.

Layer 3 – Course of hollowing

As step one, AceCryptor obtains the addresses of LoadLibraryA and GetProcAddress APIs the identical method as in ` 2 – traverse loaded modules, traverse exports, and use shl1_add checksums. Then AceCryptor obtains a number of API operate addresses and DLL handles.

Determine 14. Construction of AceCryptor’s Layer 3 – course of hollowing

Within the subsequent step, AceCryptor makes use of the API GetFileAttributesA and checks for file system attributes of a file referred to as apfHQ. Attributes are in comparison with a non-existing combination of flags 0x637ADF and if they’re equal, this system will find yourself in an infinite loop. As a result of that is used within the final layer, which is already nicely hidden, and since this isn’t the one trick right here, we assume that this isn’t one other obfuscation method, however slightly an undocumented anti-sandbox/anti-emulator trick towards an unknown however particular sandbox/emulator that returns this worth.

If this system continues efficiently, there may be one more anti-sandbox/anti-emulator verify. Now AceCryptor makes use of the API RegisterClassExA to register a category with the category title saodkfnosa9uin. Then it tries to create a window with the title mfoaskdfnoa utilizing the CreateWindowExA API. Within the final step of this verify, AceCryptor tries to make use of the APIs PostMessageA and GetMessageA to go a message. As a result of these APIs usually are not used that often, this verify helps to dodge sandboxes/emulators that haven’t applied these APIs or the place the emulated APIs don’t operate correctly.

Determine 15. Anti-VM/anti-emulator trick

After passing these checks efficiently, AceCryptor makes use of the process hollowing technique the place it creates a brand new occasion of the present course of (GetCommandLineA, CreateProcessA), maps the ultimate payload into the newly created course of, and launches it.

Earlier variations

Anti-investigation trick utilizing RegisterClassExA, CreateWindowExA, PostMessageA, GetMessageA was in earlier variations (e.g., SHA-1: 01906C1B73ECFFD72F98E729D8EDEDD8A716B7E3) seen used at Layer 1 and later (when it was examined out and the structure of the cryptor advanced) it was moved to Layer 3.

Layer 3 – Reflective loader

The primary stephis layer, much like Layer 2 and Layer 3 – Course of hollowing, obtains addresses of the GetProcAddress and LoadLibraryA API capabilities. The distinction is that this time, for some cause, the authors didn’t use the shl1_add checksum operate, however they receive first the GetProcAddress by way of traversing loaded modules, traversing exports, and evaluating strings. Then utilizing GetProcAddress they receive the LoadLibraryA operate. Utilizing these two APIs, AceCryptor hundreds addresses of some extra API capabilities and a deal with to kernel32.dll.

Determine 16. Construction of the Layer 3 reflective loader

Within the code, there’s a trick (proven in Determine 17) the place AceCryptor mixes code with knowledge. AceCryptor controls a worth that’s on return handle after one name. This worth is by default set to zero and later AceCryptor writes there an handle of the entry level of the ultimate payload. If this system will get patched and the worth is ready to a non-zero worth, this system will leap to the handle pointed to by that worth and crash.

Determine 17. Mixing code with knowledge

Within the subsequent step, AceCryptor performs a recognized anti-VM check aimed towards Cuckoo sandbox, IDA Professional+Bochs, and Norman SandBox. In Determine 19 could be seen that flag SEM_NOALIGNMENTFAULTEXCEPT with the worth 0x04 at all times will get set by the Cuckoo sandbox, and due to that, the second name of SetErrorMode within the code from Determine 18 received’t return the identical worth because the one which was set by the earlier name.

Determine 18. Anti-VM trick

Determine 19. code from Cuckoo Sandbox

Within the final steps, AceCryptor first checks if the ultimate payload has been compressed (once more) and in that case, it makes use of LZO_1Z decompression. Just like Layer 2, the Layer 3 reflective loader makes use of a customized construction, which we named ENCRYPTED_DATA_INFO_STRUCT (Determine 16), that may be discovered proper between the position-independent code and ultimate payload, containing info like compression flag, variety of sections of payload, (de)compressed measurement of payload, entry level handle, addresses of some directories, picture relocation desk handle, and so forth. AceCryptor makes use of this info (not like Layer 3 – Course of hollowing, which parses the PE of the ultimate payload) to do a reflective code loading method the place it remaps (map sections, rebase picture, …) its personal picture with the picture of the ultimate payload and launches the payload by calling its entry level.

Conclusion

AceCryptor is a long-lasting and prevalent cryptor-malware, distributed all all over the world. We count on that it’s bought someplace on darkish net/underground boards as a CaaS. Companies of this malware have been utilized by tens of various malware households and plenty of of them depend on this cryptor as their foremost safety towards static detections.

Because the malware is utilized by many menace actors, anybody could be affected. Due to the variety of packed malware, it’s tough to estimate how extreme the results are for a compromised sufferer. AceCryptor could have been dropped by different malware, already operating on a sufferer’s machine, or if sufferer received immediately stricken by, for instance, opening a malicious electronic mail attachment, any malware inside might need downloaded further malware; thus it might be very tough to scrub the compromised machine.

Regardless that for now an attribution of AceCryptor to a selected menace actor will not be potential and we count on that AceCryptor will proceed to be broadly used, nearer monitoring will assist with prevention and discovery of latest campaigns of malware households filled with this cryptor.

IOCs

Information

Observe: Listed recordsdata are an inexpensive choice of samples all through time, protecting completely different variations of AceCryptor or packing completely different malware.

Named objects

MITRE ATT&CK strategies

This desk was constructed utilizing version 12 of the MITRE ATT&CK enterprise strategies.