Shedding gentle on AceCryptor and its operation

ESET researchers reveal particulars a few prevalent cryptor, working as a cryptor-as-a-service utilized by tens of malware households

On this blogpost we look at the operation of AceCryptor, initially documented by Avast. This cryptor has been round since 2016 and since – all through its existence – it has been used to pack tens of malware households, many technical elements of this malware have already been described. You may have already got examine this cryptor, which is variously often known as the DJVU obfuscation, SmokeLoader’s stage 1, RedLine stealer’s stage 1, 2 and 3, simple and popular packer, and so forth… Many (however not all) of the revealed blogposts don’t even acknowledge this cryptor as a separate malware household, so allow us to join all of the dots for you, offering not solely a technical evaluation of its variants but additionally an outline of the malware households that may be discovered packed by it and the way prevalent AceCryptor is within the wild.

For malware authors, defending their creations in opposition to detection is a difficult activity. Cryptors are the primary layer of protection for malware that will get distributed. Though menace actors can create and keep their very own customized cryptors, for crimeware menace actors it usually could also be a time-consuming or technically troublesome activity to keep up their cryptor in a so-called FUD (totally undetectable) state. Demand for such safety has created a number of cryptor-asa-service (CaaS) choices that pack malware. These cryptors can embody a number of anti-VM, anti-debugging ,and anti-analysis strategies mixed to realize concealment of the payload.

Key factors of this blogpost:

  • AceCryptor supplies packing providers to tens of very well-known malware households.
  • Samples of AceCryptor are very prevalent the world over as a result of a number of menace actors utilizing it actively unfold their packed malware in their very own campaigns.
  • AceCryptor is closely obfuscated and all through the years has included many strategies to keep away from detection.
  • AceCryptor has a number of variants which are described on this blogpost.
  • Though it’s potential to seek out technical analyses (largely the place this cryptor seems as a component/stage of different malware) completed by different researchers, ESET Analysis goals to supply not solely a complete overview of AceCryptor’s performance, but additionally its historical past and unfold.
  • Throughout 2021 and 2022, ESET protected greater than 80,000 clients who had been affected by malware packed by AceCryptor.

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 offered someplace as a CaaS. If we take into accounts the variety of distinctive information detected: although 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 may be seen in Determine 1, detection hits had been distributed fairly evenly all through these two years, which is to be anticipated from malware utilized by a lot of 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 wanting 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 should 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 varied 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 reveals an outline of the portions of samples belonging to a few of 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 akin to AceCryptor is useful for monitoring of malware that makes use of their providers. For instance, contemplate a RedLine Stealer that was first seen in Q1 2022. As may 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 recent rising threats, but additionally with monitoring the actions of menace actors.

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


As must be anticipated from the number of malware packed inside AceCryptor and the variety of pursuits of various malware authors, AceCryptor is seen in all places on this planet. 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 international locations with the very best numbers of detections throughout 2021 and 2022.

Determine 4. Heatmap of nations affected by AceCryptor in line with ESET telemetry

Throughout 2021 and 2022, ESET merchandise detected and blocked malware variants packed by AceCryptor on greater than 80,000 clients’ 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 reveals 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 price mentioning right here is that although the variety of distinctive samples of AceCryptor may be very excessive, the variety of distinctive samples packed inside is fewer than 7,000. This reveals 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 moderately than make investments their time and assets to implement their very own cryptor answer.


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

One other means 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 a few of the malware households protected by AceCryptor can even obtain new, extra malware.

Technical evaluation

Presently AceCryptor makes use of a multistage, three-layer structure. There are two recognized variations of the primary layer which are at present 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 activity 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

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

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

A very powerful 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 in some way randomized and obfuscated. It will trigger huge issues for somebody attempting to give you YARA guidelines or static detections.


The authors leverage loops for a number of obfuscations. The primary and most simple method is to make use of loops with junk code simply to make evaluation harder. We have now seen utilization of junk code since 2016 once 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 occurring, 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 vital elements of code

The second utilization of loops is to achieve delay. We have now noticed that some variations of AceCryptor launch Layer 2 nearly instantly, however others include loops which are so time demanding that it will probably 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 increase some flags. Even when not, some sandboxes like Cuckoo Sandbox implement sleep-skipping strategies to keep away from the delay and proceed to the attention-grabbing 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 determine which loops are junk loops and thus may be skipped.

A 3rd obfuscation method utilizing loops consists of hiding vital 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. Normally, 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 individual iteration of a loop doesn’t occur, the pattern will later crash. This, together with junk code, implies that to dynamically analyze the malware, one first has to research which loops or iterations of loops may be skipped, and which can not. Which means 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 comprises an operation vital for subsequent execution, and the opposite is simply filled with junk code. After all, this will 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 vital operations additionally include junk code.

Randomization – Thou shalt not YARA

One other vital a part of the primary layer is randomization. Junk code and the loops talked about beforehand are randomized in every pattern, in such a means 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 can even 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 should 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 is just not the one factor that’s randomized. The encrypted Layer 2 and its decryption key are at present often 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 at first of the decrypted knowledge, however there are samples the place you find yourself with a block of random knowledge at first and you could know the proper offset to seek 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.
  • Sources with random names and content material, as may be seen in Determine 9. The authors of AceCryptor fill samples with randomly generated assets containing randomly generated knowledge. We assume that that is completed to make samples much less suspicious and make finding the precise encrypted knowledge harder. Sources can include:
    • String tables
    • Menus
    • Bitmaps
    • Binary knowledge
  • Strings used within the code.
  • Icons – although 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 vital to code execution – they could 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

Through the years, the authors of AceCryptor received more adept at growing malware and the cryptor modified and developed. Though there have been many smaller adjustments, updates, and enhancements, a few of the attention-grabbing 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. Not like 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 peak, 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 straight from Layer 1. This layer serves as extra 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 info of Layer 3

Determine 11. AceCryptor’s Layer 2 construction

As step one, AceCryptor makes use of a typical method to acquire some API operate addresses. It resolves the GetProcAddress and LoadLibraryA capabilities through the use of the PEB_LDR_DATA to traverse by way of loaded modules, and by evaluating the hash values of their export names in opposition to 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 sooner.

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 data from its customized construction L2_INFO_STRUCT (proven in Determine 13), which may be discovered proper on the finish of the position-independent code, as may 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 about, 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 means 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 properly hidden, and since this isn’t the one trick right here, we assume that this isn’t one other obfuscation method, however moderately an undocumented anti-sandbox/anti-emulator trick in opposition to an unknown however particular sandbox/emulator that returns this worth.

If this system continues efficiently, there’s yet one more anti-sandbox/anti-emulator test. Now AceCryptor makes use of the API RegisterClassExA to register a category with the category identify saodkfnosa9uin. Then it tries to create a window with the identify mfoaskdfnoa utilizing the CreateWindowExA API. Within the final step of this test, AceCryptor tries to make use of the APIs PostMessageA and GetMessageA to go a message. As a result of these APIs should not used that regularly, this test 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 developed) it was moved to Layer 3.

Layer 3 – Reflective loader

The primary stephis layer, just 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 purpose, 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 price that’s on return tackle after one name. This worth is by default set to zero and later AceCryptor writes there an tackle of the entry level of the ultimate payload. If this system will get patched and the worth is about to a non-zero worth, this system will soar to the tackle 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 in opposition to Cuckoo sandbox, IDA Professional+Bochs, and Norman SandBox. In Determine 19 may 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 gained’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 if that’s the case, it makes use of LZO_1Z decompression. Much 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 last payload, containing data like compression flag, variety of sections of payload, (de)compressed measurement of payload, entry level tackle, addresses of some directories, picture relocation desk tackle, and so forth. AceCryptor makes use of this data (in contrast to 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.


AceCryptor is a long-lasting and prevalent cryptor-malware, distributed all world wide. We count on that it’s offered 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 in opposition to static detections.

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

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

For any inquiries about our analysis revealed on WeLiveSecurity, please contact us at [email protected].

ESET Analysis provides personal APT intelligence stories and knowledge feeds. For any inquiries about this service, go to the ESET Threat Intelligence web page.



Be aware: Listed information are an affordable collection of samples all through time, overlaying completely different variations of AceCryptor or packing completely different malware.

SHA-1 Filename ESET detection identify Description
0BE8F44F5351A6CBEF1A54A6DE7674E1219D65B6 N/A Win32/Kryptik.HPKJ TEA model of Layer 1, with SmokeLoader packed inside.
0BE56A8C0D0DE11E0E97B563CAE6D1EE164F3317 N/A Win32/Kryptik.GOFF LCG model of Layer 1, with SmokeLoader packed inside, anti-investigation trick on Layer 2.
1E3D4230655411CB5F7C6885D7F947072B8F9F0F N/A Win32/Emotet.AW RC4 model of Layer 1, with Emotet packed inside.
2FDD49A3F7D06FFFD32B40D35ABD69DEC851EB77 N/A Win32/Smokeloader.F TEA model of Layer 1, with SmokeLoader packed inside.
3AC205BE62806A90072524C193B731A1423D5DFD N/A Win32/Kryptik.GPCG TEA model of Layer 1, with SmokeLoader packed inside.
6ABF731B90C11FFBD3406AA6B89261CC9596FEFD N/A Win32/Kryptik.HRHP TEA model of Layer 1, with RedLine stealer packed inside.
8E99A5EC8C173033941F5E00A3FC38B7DEA9DCB3 N/A Win32/Kryptik.FKYH TEA model of Layer 1, with Filecoder.Q packed inside, subsequent layer in BMP picture.
15ADFFDA49C07946D4BD41AB44846EB673C22B2B N/A WinGo/RanumBot.B TEA model of Layer 1, with RanumBot packed inside, obfuscation – random PDB path.
47DB52AB94B9A303E85ED1AA1DD949605157417E N/A Win32/Smokeloader.A TEA model of Layer 1, with SmokeLoader packed inside, anti-emulator trick on Layer 1.
70BC8C2DC62CF894E765950DE60EC5BD2128D55B N/A Win32/Smokeloader.F TEA model of Layer 1, with SmokeLoader packed inside.
88B125DDA928462FDB00C459131B232A3CD21887 N/A Win32/Kryptik.GDTA TEA model of Layer 1, with Hermes packed inside, obfuscation – masking values.
90A443787B464877AD9EB57536F51556B5BA8117 N/A Win32/Kovter.C XTEA model of Layer 1, with Kovter packed inside.
249BED77C1349BE7EC1FC182AFCCB1234ADFACDF N/A Win32/Smokeloader.F TEA model of Layer 1, with SmokeLoader packed inside.
3101B17D73031384F555AE3ACD7139BBBAB3F525 N/A Win32/TrojanDownloader.Amadey.A TEA model of Layer 1, with Amadey packed inside.
8946E40255B57E95BAB041687A2F0F0E15F5FFCE N/A Win32/Kryptik.GKIN LCG model of Layer 1, with GandCrab packed inside, obfuscation – named sections.
946082F225C76F2FFBE92235F0FAF9FB9E33B784 N/A Win32/Filecoder.Locky.C LCG model of Layer 1, with Locky packed inside.
A8ACF307EA747B24D7C405DEEF70B50B2B3F2186 N/A MSIL/Spy.RedLine.B LCG model of Layer 1, with RedLine Stealer packed inside.
F8039D04FF310CEF9CA47AC03025BD38A3587D10 N/A Win32/Smokeloader.F TEA model of Layer 1, with SmokeLoader packed inside.

Named objects

Object Sort Object identify
Class saodkfnosa9uin
Window mfoaskdfnoa

MITRE ATT&CK strategies

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

Tactic ID Title Description
Execution T1106 Native API AceCryptor is ready to launch a course of utilizing the CreateProcessA API.
Protection Evasion T1497.003 Virtualization/Sandbox Evasion: Time Based mostly Evasion AceCryptor makes use of loops with arbitrary code to delay the execution of core performance.
T1497.001 Virtualization/Sandbox Evasion: System Checks AceCryptor makes use of a number of strategies to detect sandboxes and emulators.
T1140 Deobfuscate/Decode Information or Info AceCryptor makes use of TEA, LCG, XTEA, or RC4 encryption and LZO_1Z compression to extract position-independent code and payloads.
T1027 Obfuscated Information or Info AceCryptor masks values like size of payload, recognized constants of decryption algorithms, or decryption key.
T1055.012 Course of Injection: Course of Hollowing AceCryptor can create a brand new course of in a suspended state to unmap its reminiscence and exchange it with the hidden payload.
T1620 Reflective Code Loading AceCryptor can use a reflective loader to rewrite its picture and exchange it with a hidden payload (Home windows PE).