The ransomware BlackMatter aims at stepping into the void, which was left by REvil’s and DarkSide’s (temporary) retreat. At this point in time this new ransomware seems to pose a serious threat. In this blogpost BlackMatter’s API hashing mechanism is described in detail and a Ghidra-script is supplied 1 to aid future analyses.
The API hashing algorithm: To calculate the API hashes for function names, each and every character is added up, while a binary rotation to the right by 13 bits is performed in each iteration. The hash of the housing module, which was calculated in the same manner before, serves as a seed value for the respective hash.
Storing addresses: Notably, BlackMatter does not store the function addresses in clear after resolving them. Instead it uses an array of “trampoline-pointers”, which point to small, dynamically allocated assembly blocks (12 bytes in size), which perform the XOR-decoding of the encoded version of the respective function address, that was placed in there during import resolution and call it afterwards.
A new ransomware gang named BlackMatter appeared in July 2021 and started to recruit affiliates at the underground forums Exploit and XSS2. They fill the void, which is left by DarkSide’s shutdown after the Colonial Pipeline attack3 and REvil’s disappearing in the mid of July after pwning Kaseya4.
On the 2nd of August 2021 an interview of D. Smilyanets (The Record) with the alleged threat actor behind BlackMatter was published5. Within this interview, the actor states, that he is neither the successor of DarkSide nor REvil, instead he proclaims, that BlackMatter tries to unify the best of the ransomwares LockBit, REvil and DarkSide, which all have their individual strengths in the opinion of the alleged actor behind “the new ransomware on the block”.
At this point in time it seems to be a valid assumption, that BlackMatter will keep the DFIR-community and the law enforcement agencies busy for the next few weeks, therefore initial analyses might be helpful to get to know the threat imposed by this probably rebranded actor.
For this analysis the BlackMatter-sample with SHA256
This blog post deals with the API hashing found in this sample and shows a way to defeat it with the help of Ghidra scripting. Resolving the hidden imports, is the main prerequisite for a static analysis of BlackMatter-binaries. However, further steps, like the decoding of its eventually available config data, are not in scope of this blog post.
Directly after the entry point of the executable, the function at address
00405e5c, which is responsible for initializing the import resolution is called, as the following figure of the decompiled code illustrates.
At l. 10 and l. 15 of this function the actual import resolution is started by calling another function at
resolveHashedImport in the figure above. In this function all the heavy lifting required to resolve symbols is performed, e.g. the loaded modules are traversed in memory by utilizing the doubly-linked list named
InLoadOrderModuleList of the
PEB_LDR_DATA-struct and so on.
The goal of those initial calls is to retrieve
HeapAlloc (l. 10 and 15) at first. This is only possible since the called function at
0040581d ensures that
GetProcAddress are loaded on the first invocation by recursive calls to itself, as it is shown in the following figure exemplary for
So how is the hash, which is passed to the function called at
00405844 calculated by BlackMatter?
For the calculation of the API hash each character is added up one by another. In each iteration a seeded ROR-13-operation is performed, as the following figure illustrates.
Because of the fact, that the hash of the module name is used as a seed, a two step process has to be employed to construct the final API hash for a single function.
First, the module name is hashed in a similar manner with a seed of 0. This happens in the function at
004010bb, which is not shown here. It is looped over the characters, which are transformed to lower case. In each iteration a rotation by 13 bits of the dword value resulting from the previous iteration is performed and the current character value is added. This leads to the following Python implementation:
def calc_mod_hash(modname): mask = 0xFFFFFFFF h = 0 for c in modname + "\x00": cc = ord(c) if (0x40 < cc and cc < 0x5b): cc = (cc | 0x20) & mask h = (h >> 0xd) | (h << 0x13) h = (h + cc) & mask return h
The resulting hash of the module name is then used as a seed for the similar but simpler function presented at fig. 3, which finally calculates the actual function hash.
The following Python code shows the logic found in this function at
def calc_func_hash(modhash, funcname): mask = 0xFFFFFFFF h = modhash for c in funcname + "\x00": cc = ord(c) h = (h >> 0xd) | (h << 0x13) h = (h + cc) & mask return h
Note: It is important to add the nullbyte, so that for a function name of n characters, n+1 ROR-operations are performed.7
In summary this leads to the following calculation of a function hash as it is used by BlackMatter:
def get_api_hash(modname, funcname): return calc_func_hash(calc_mod_hash(modname), funcname)
Let’s test it:
mn = "kernel32.dll" fn = "GetProcAddress" print(hex(get_api_hash(mn, fn))) mn = "kernel32.dll" fn = "LoadLibraryA" print(hex(get_api_hash(mn, fn)))
#+Result : 0xbb93705c : 0x27d05eb2
Indeed, both hashes can be found in the binary, as fig. 3 shows:
0x5d6015f ^ 0x22065fed, wich results in
0x27d05eb2 can be found, since all API hashes are stored XORed with
0x22065fed and are XORed again with this value before a comparison with the calculated hash.
After the a/m and absolutely required functions like
LoadLibraryA, etc. have been loaded. BlackMatter resolves blocks of hashed functions stored as dwords in global memory (2nd arg to function8) and stores pointers to dynamically allocated “structs” in global memory as well (1st arg to function9):
Line 18 in fig. 1 already showed this code in a decompiled representation.
Fig. 6 shows the decompilation of the called function beginning at
00405a86. Within there, it is looped over the array of function hashes until the value
0xCCCCCCCC is reached. This serves as an indicator of the end of the list of function hashes, so the loop stops in l. 19, when this value is read.
Line 29 ff. looks very interesting here.
To further complicate analysis, BlackMatter does not store the function address itself in the result array. Instead it stores a pointer to 12 bytes of dynamically allocated memory.
In these 12 bytes it does not store the function address in clear. Instead the results of XOR-operations (here XORed with
0x22065fed) are stored together with assembly instructions to decode the real function address on the fly, when the function is called as fig. 6 suggests.
So the global array of pointers which is passed as a buffer to hold the results of the import resolution (e.g. l. 18 ff. in fig. 1 and fig. 5) acts as trampoline, so that on each call, it is jumped to a 12 byte “function-struct”, which is comprised of the following opcode sequence on the heap, where the questionmarks resemble the XORed-function address in question:
B8 ?? ?? ?? ?? 35 ED 5F 06 22 E0 FF
Upon execution, these instructions load the XORed-function address into EAX and perform the XOR-operation again to reverse it and to finally call the decoded function address, so that the actual libary-call is performed without storing the function-addresses in memory.
Import resolution with Ghidra scripting
The labelling of the a/m “trampoline-pointers”, whose call ultimately leads to the execution of the a/m opcode-sequence should be automated with Ghidra’s scripting capabilities. To accomplish this, have a look at the following Java-code in my Gist:
Upon execution the script asks for the name of the resolving function (the one called in fig. 5), which takes the two pointers to global memory regions (here at
00405a86). In the next GUI-dialog, that pops up, the XOR-key has to be specified (here
0x22065fed). Afterwards you have to choose the file, containing the precomputed hashes, which should be used for name resolution. This list can be found at my Gist as well:
If you stumble upon a BlackMatter-sample, that uses the same ROR-13-hashing, this script might help to get you started quickly with the analysis.
This blog post detailed the API-hashing mechanism employed by the new ransomware BlackMatter.
To hash a function name, BlackMatter employs a seeded ROR13 in an iterative manner. That is a rotation of the dword by 13 bits to the right. The name of the housing module, hashed in the same way, but with an initial value of 0, is used as a seed for this trivial hashing algorithm.
It has to be noted, that due to the implementation with a do-while-loop, for a function name of length n (terminating zero-byte excluded) n+1 ROR-operations will be performed.
The API hashes are initially stored as dwords in global arrays XORed with
Interestingly, the imported function addresses are stored in a dynamically allocated memory region. To further complicate analysis, BlackMatter does not store the function address itself, but the result of an XOR-operation (here again XORed with
0x22065fed) together with assembly instructions to decode it on the fly, when the function is called by a pointer to this memory location housing these instructions.
During the import resolution-routine at
00405a86, which is called multiple times with different arrays of API hashes, pointers to those opcode-sequences are stored in a global array, which is then referenced for executing the single functions, when needed.
If you have any notes, errata, hints, feedback, etc., please send a mail to
ca473c19fd9b81c045094121827b3548 at digital-investigations.info.
Thanks to @sisoma2 for pointing this out in his implementation https://twitter.com/sisoma2/status/1422547399285870594