Dear followers of this blog, I wish you a happy new year!
About a month ago, I have launched my latest project: Malpedia (slides here).
Since the launch, we have grown by about 350 users and have a stable average 10 proposals/contributions per day. I hope that Malpedia will become a really useful resource for malware research over time!
This blog shall serve as a demonstration for what you can use with this malware corpus.
Over the last couple days, I have taken all dumps for versions of Zeus-related families and created a similarity matrix for them, using IDA Pro and BinDiff.
It looks like this:
Screenshot of "The Big Zeus Family Similarity Showdown"
Because I want to update this document over time, I have descided to host it on a dedicated page over at pnx.tf instead of using this blog. Over there, you can find more info on the families included and the methodology I used in order to create it.
Here is a short post on what I found out about the "link" between Lazarus and WannaCry.
To me, the function referenced looks a lot like only a generator for a TLS 1.0 client hello.
On 2017-05-15 19:02 Neel Mehta tweeted the following:
Neel Mehta tweet, linking the samples of WannaCry and Lazarus / Contopee
Some more indicators for this claim that we look at Client Hellos is the usage in a function a bit up in the call chain:
Up the call stack, looking in which context the function / buffer is used.
Here our buffer generated by 0x402560 is send to localhost listening on typical TOR ports.
Maybe some part of the TOR communication capability (or adapter) was directly embedded in this earlier version of WannaCry?
Assessment:
While I agree that the compiled functions from both samples (A: WannaCry, B: Lazarus) originate very likely from the same source code and that they were compiled with similar tooling (there are some more indicators for this in how the generated code look likes, e.g. padding, thunks, ...), the exclusivity of the code defines the strength of the link.
This function provides a rather generic network-based
functionality (yet in a strongly specific way), so I would not be surprised if eventually the respective source code
appears as being publicly accessible in some corner of the wild and open Internet. In that case we could be looking at a super weird coincidence.
Hashes:
3e6de9e2baacf930949647c399818e7a2caea2626df6a468407854aaa515eed9 - WannaCry, February 2017
After hacking away for some days in the code chamber, I'm finally satisfied with the outcome and happy to announce the release of my new library: "ApiScout".
The main goal of ApiScout is to allow a faster migration from memory dumps to effective static analysis.
While reverse engineering "things" (especially malware), analysts often find themselves in a position where no API information is immediately available for use in IDA or other disassemblers.
This is pretty unfortunate, since API information is probably the single most useful feature for orientation in unknown binary code and a prime resource for recovery of meaning.
Usually, this information has to be recovered first: for example by rebuilding the PE ("clean unpacking", using ImpRec, Scylla, or similar) or by recording information about DLLs/APIs from the live process to be able to apply it later on (see Alex Hanel's blog post).
Both methods are potentially time-consuming and require manual effort to achieve their results. From my experience, clean unpacked files are often not even needed to conduct an efficient analysis of a target.
As I did a lot of dumping when reversing malware over the last years (and especially for malpedia - project outlook slides here), I craved for a more efficient solution.
Initially, I used a very hacky idapython script to "guess" imports in a given dump versus an offline DB - the limitations: 32bit and a single reference OS only.
After talking to some folks who liked the approach, I decided to refactor it properly and also integrate support for 64bit including ASLR.
To show the usefulness of this library, I have written both a command line tool and IDA plugin, which are explained in the remainder of this blog post.
First, let's have a look at a more or less common situation.
Executing it yields a very suspicious new svchost.exe process.
Running the Asprox sample results in a new suspicious scvhost.exe process.
Inspecting the memory of this new process reveals a not less suspicious memory section with RWX access rights and a decent size of 0x80000 bytes.
However, apparently the PE header got lost as can be seen on the left:
Looking closer at the process memory, we find a RWX segment @0x008D0000.
Luckily the import information is readily available:
Left (Hex view) /Right (Address view): Import Address Table (IAT) as found inside of the RWX segment.
With ImpRec or Scylla, we would now have to point to the correct IAT instead of using the handy IAT autosearch, because autosearch would identify the IAT of svchost.exe instead of Asprox' (see comparison left vs. right).
Left: Scylla IAT Autosearch gives IAT of svchost.exe, but we want ...
Right: IAT of Asprox - which we can't dump since PE header is missing.
But we now encounter another issue: Because there is no PE header available, Scylla fails to rebuild the binary and with that, the imports.
Granted, many injected memory sections will have more or less correct PE headers or we could write one from scratch...
But remember, I promised "painless" recovery in this blog post's title.
ApiScout: command-line mode
As I explained before, if we have all relevant API information available, we can directly locate IATs like the one of the above example.
So let's first build an API DB:
Running DatabaseBuilder.py to collect Windows API information from a running system.
While DatabaseBuilder.py is fully configurable, using Auto-Mode should yield good results already.
Next we can use the database to directly extract API information from our dump of memory section 0x008D0000:
Resultof running scout.py with the freshly build API DB against a memory dump of our injected Asprox.
Since this cmdline tool is just a demo for using the library, this should give you an idea of what can be achieved here.
For our example memory dump (76kb), I timed the full recovery (loading API DB, searching, shell output) on my system at about 0.3 seconds, so it's actually quite fast.
I am aware that this may occasionally lead to False Positives but there is also a filter option as a simple but effective measure: It requires that there is at least another identified API address within n bytes of neighbourhood - from my experience this is already enough to reduce the already very few FPs to an absolute minimum.
IDA ApiScout: fast-tracking import recovery
In this section, I want to showcase the beautified version of my old hacky script.
I assume it can be similarly adapted for others disassemblers like radare2, Hopper, or BinaryNinja.
Loading ida_scout.py as a script in IDA shows the following dialog in which an appropriate API DB can be selected.
Note that imports are not resolved as we loaded the memory as a binary (not PE) at fixed offset 0x008D0000:
ida_scout.py shows the available API DBs or can be used to load a DB from another place.
Executing the search with the WinXP profile from which Asprox was dumped, we now get a preview of the APIs that can be annotated:
Selection/Filter step of identified API candidates.
Aaaaand here we go, annotated API information:
Yay, annotated offsets in IDA as if we had a proper import table!
And yes, it's just as fast as it seems, clicking through both windows and having API information ready to go took less than 10 seconds.
That's what I call painless. :)
Dealing with ASLR
For simplicity's sake the above example was executed on WinXP 32bit, with no ASLR available.
However, it works just as fine for more recent versions (I use Windows 7 64bit), both for 64bit dumps or 32bit compatibility mode dumps.
In case you haven't disabled ASLR on your reference system, this section explains how ASLR offsets are obtained for all DLLs that are later stored in the DB.
I will skip explaining ASLR in detail, but feel free to read up on it, e.g. this report by Symantec.
The first step of DLL discovery is identical to non-ASLR systems and performed by DatabaseBuilder.py.
At the end of the crawling process (which involves collecting the ImageBase addresses as stated in the PE headers of all DLLs), we perform a heuristic check if ASLR is activated: We obtain a handle (which equals the in-memory BaseAddress) to three DLLs (user32.dll, kernel32.dll, and ntdll.dll) via GetModuleHandle() and check if the respective corresponding file as identified with GetModuleFileName() shows an identical ImageBase. If at least one DLL differs, we assume ASLR is active.
Since every DLL receives a individual ASLR offset, we will have to make sure that every DLL of interest has been loaded at least once.
For this purpose, I wrote a little helper binary "DllBaseChecker[32|64].exe" which simply performs a LoadLibrary() on a given DLL path and returns the load address.
Iterating through all DLLs identified in the discovery step, we are now able to determine each individual ASLR offset by subtracting file ImageBase and load address.
Closing Note
While this approach probably is certainly no magic or rocket science, I haven't seen it published in this form elsewhere yet. At least to me, it provides great convenience in several ways and I hope that one or the other can benefit from it as well.
For future use, I imagine it being used manually as shown in the post or potentially in automated analysis post-processing chains, where this functionality may come in handy.
I have to admit that I misjudged the effort to do code this in a nice way (by about a week of release-time) but I want to thank @herrcore for motivating me to rewrite and release it and @_jsoo_ for pushing me to address ASLR properly with the initial release version.
After some abstinence, I thought it might be a good idea to write something again. The perfect occasion came yesterday when I decided to build myself a new VM base image to be used for future malware analysis.
In that sense, this post is not immediately a tutorial for setting up a hardened virtual machine as there are so many other great resources for this already (see VM Creation). Maybe there is a good hint or two for you readers in here but it's mostly a write-up driven by my personal experience.
The main idea of this post is to outline some pitfalls I ran into yesterday, when relying on said resources. To have others avoid the same mistakes, I hope this post will fulfil its putpose.
In total I spent about 5 hours, 2 hours for setup and probably another 3 hours for testing but more about that later. This could have easily been only one hour or less if I knew everything I'll write down here beforehand. So here you go. :)
The remainder of this post is structured as follows:
Before starting out, it's good to know and plan where we are heading.
My Needs: I'm mostly interested in doing some rapid unpacking/dumping to feed my static analysis toolchain and then occasional do some debugging of malware to speed up my reasoning of selected code areas.
For this, I wanted a new base VM image that is able to run as much malware natively as possible, without me having to worry about Anti-Analysis methods.
Potentially, I want to deploy this image later as well for automation.
I don't aim for a perfect solution (perfection is the enemy of efficiency) but a reasonably good one.
OS choice: Windows 7 is still the most popular OS it seems, but since 64bit malware is getting more popular, we should take that into concern as well. So I go with Win7 x64 SP1 as base operating system.
Why not Win10: Well, I want a convenient way to disable ASLR and NX globbaly to allow my malware&exploits to flourish. Since I don't know if it's as easy in Win10 as it is in Win7, I stick with what I know for now.
Since I wanted to understand all the steps, I took VMCloak only for theoretical background. VBoxHardenedLoader is targeting a Win7 x64 as host system, however I use Ubuntu 16.04 with VirtualBox 5.0.24 so this wasn't immediately usable as well. But it's another excellent theoretical background resource.
Ultimately I ended up using antivmdetection as base for my endeavour.
Since I trial&error'd myself through the usage (in retrospect: I should do more RTFM and less fanatic doing), here's a summary of things you want to do before starting:
1) Download VolumeID (for x64)
2) Download DevManView (for x64)
3) # apt-get install acpidump (used by Python Script to fetch your system's parameters)
4) # apt-get install libcdio-utils (contains "cd-drive", used to read these params)
5) # apt-get install python-dmidecode (the pip-version of dmidecode is incompatible and useless for our purpose, so fetch the right one)
6) $ git clone https://github.com/nsmfoo/antivmdetection.git
7) $ cd antivmdetection :)
8) $ echo "some-username" > user.lst (with your desired in-VM username(s))
9) $ echo "some-computername" > computer.lst
First, I simply created a new empty Win7 x64 VM.
I used the following specs:
* CPU: 2 cores
* RAM: 4 GB
* HDD: 120 GB
* VT-x activated (needed for x64)
* GPU: 64 MB RAM (no acceleration)
* NIC: 1x Host-Only adapter (we don't want Internet connectivity right away or Windows may develop the idea of updating itself)
Important: Before mounting the Windows ISO, now is the time to use antivmdetection.py.
It will create 2 shell scripts:
1) <DmiSystemProduct>.sh <- Script to be used from outside the VM
2) <DmiSystemProduct>.ps1 <- Script to be used from inside the VM post installation
Run Antivmdetection (outside VM): For me <DmiSystemProduct> resulted in "AllSeries" because I run an ASUS board.
Okay, next step: execute <DmiSystemProduct>.sh - For me, this immediately resulted in a VM I could not start. Responsible for this were the 3 entries
1) DmiBIOSVersion
2) DmiBoardAssetTag
3) DmiBoardLocInChass
Which were set by <DmiSystemProduct>.sh to an integer value and VirtualBox was pretty unhappy with that fact, expecting a string. Changing these to random strings fixed the issue though. So this may be one of the pitfalls you may run into when using the tool. Setting the ACPI CustomTable however worked fine.
Now we have a fresh Windows 7 installation, time to mess it up.
Windows Configuration: Here are some steps to consider that may depend on personal taste.
1) Deactivate Windows Defender - Yes. Because. Malware.
2) Deactivate Windows Updates - We want to keep our system DLL versions fixed to be able to statically infer imported APIs later on.
3) Deactivate ASLR - We don't want our system DLL import addresses randomized later on. Basically, just create the following registry key (Credit to Ulbright's Blog):
[HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Session Manager\Memory Management] - “MoveImages”=dword:00000000
4) Deactivate NX - Whatever may help our malware to run... Basically, just run this in Windows command line (again Credit to Ulbright's Blog):
bcdedit.exe /set {current} nx AlwaysOff
5) Allow execution of powershell scripts - Enter a powershell and run:
> Set-ExecutionPolicy Unrestricted
Run Antivmdetection (in VM): Now we are good to execute the second script <DmiSystemProduct>.ps1.
Some of its benefits:
* ensure our registry looks clean
* remove the VirtualBox VGA device
* modify our ProductKey and VolumeID
* change the user and computer name
* create and delete a bunch of random files to make the system appear more "used".
* associate media files with Windows Media Player
* clean itself up and reboot.
I fiddled a bit with the powershell script to customize it further. Also, after reboot, I removed the file manipulation and reboot code itself to be able to run it whenever I need to after deploying my VM to new environments (additionally, this reduces the runtime from several minutes to <5sec).
Dependencies: Because malware and packers often require Visual C and NET runtimes, we install them as well. I used:
* MSVCRT 2005 x86 and x64
* MSVCRT 2008 x86 and x64
* MSVCRT 2010 x86 and x64
* MSVCRT 2012 x86 and x64
* MSVCRT 2013 x86 and x64
* MSVCRT 2015 x86 and x64
* MS.NET 4.5.2
Snapshot time! I decided to pack my VM now into an OVA to archive it and make it available for future use.
Now feel free to inflict further harm to your fresh VM.
Installing MS Office, Adobe Acrobat, Flash, Chrome, Firefox all come to mind.
Certainly DO NOT install VBoxGuestAdditions. The only benefits are better adaption of screen resolution and easy shared folders. For shared folders you can also just check out impacket's smbserver.py which gives you about the same utility with a one-liner from your host shell.
PAfish looking good:
Very good yet not perfect result. We happily ignore the VM exit technique.
This is no longer an issue when updating to VirtualBox version 5.1.4+, read below.
As initially mentioned, I spent another 3 hours with optimization and trying to get rid of the hypervisor detection.
Note that modifying the HostCPUID via VBoxManage does not fix the identity of VirtualBox which I basically learned the hard way.
Paravirtualization settings: VirtualBox allows you to choose a paravirtualization profile. They expose different combinations of hypervisor bit (HVB) and Hypervisor Vendor Leaf Name (HVN):
1) none (HVB=0, HVN="VBoxVBoxVBox")
2) default (HVB=1 HVN="VBoxVBoxVBox" but can be modified by patching /usr/lib/virtualbox/VBoxVMM.so as shown above, where we have "vbvbvbvbvbvb" instead)
3) legacy (HVB=0, HVN="VBoxVBoxVBox")
4) minimal (HVB=1, HVN="VBoxVBoxVBox")
5) Hyper-V (HVB=0, HVN="VBoxVBoxVBox" but this can also be modified like default mode)
6) KVM (HVB=0, HVN="KVMKVMKVMKVM")
I will probably spent some more time trying to figure out where the "VBoxVBoxVBox" string is exactly coming from (could not find it in other virtualbox binaries, nor in the src used by DKMS to build vboxdrv) and think it can be ultimately binary patched as well.
However, the issue itself is tied to my setup of VirtualBox, otherwise, I'm pretty sure that my VM itself is looking rather solid now in terms of anti-analysis detection, so we can conclude this write-up.
UPDATE 2017-02-06: nsmfoo suggested upgrading to VirtualBox 5.1.4+ to get rid of the hypervisor detection.
So I took his advice, moved up to VirtualBox version 5.1.14 (using this guide and this fix) and he was absolutely right:
This post ended up being a walkthrough of how I spent my last Saturday afternoon and evening.
I found nsmfoo's tool antivmdetection super useful but sadly ran into some initial trouble that cost me some time. Ultimately I ended up with a VM I am very happy with, although there remains an issue of VirtualBox's Hypervisor identification.
I wrote this post while listening through Infected Mushroom's new album "Return to the Sauce" which I can also heavily recommend. :)
In the other blog post on Fobber, I have demonstrated how to batch decrypt function code, which left us with IDA recognizing a fair amount of code opposed to only a handful of functions:
After function decryption, IDA recognizes some code already.
However, we can see that there is still a lot of "red" remaining, meaning that functions have not been recognized as nicely as we would like it.
The reason for this is that Fobber uses another technique which we might call "inline string decryption".
It looks like this:
Fobber inline calls at 0x950326 and 0x950345, pushing the crypted string address to the stack which is then consumed as argument by decryptString()
We can see two calls to decryptString(), and both of them are preceded by a collection of bytes prior to which a call happens that seemingly "jumps" over them.
The effect of a call is that it pushes its return address to the stack - in our case resulting in the absolute address of the encrypted string directly following this call being pushed to the stack. From a coder's perspective, this "calling over the encrypted string" is an elegant way to save a couple bytes, while from an analysts perspective, this really screws with IDA. :)
Let's look at how the strings are decrypted:
Fobber's string decryption function.
Again, the rather simple single-byte xor-loop jumps the eye.
However, the interesting part is how parameters are loaded.
Thus, let me explain the effects of instructions one-by-one:
[...] mov edi, [ebp+0Ch] | move pointer where decrypted string will be put to EDI mov esi, [ebp+8] | move pointer of encrypted string to ESI lodsw | load two bytes (word) from ESI movzx ecx, al | put the lower byte into ecx and zero extend -> this is our len lodsb | load another byte from ESI (first byte of encrypted string) xor al, ah | xor string byte with upper byte loaded by lodsw (our key) xor al, cl | xor string byte with number of remaining chars (CL) stosb | store decrypted byte loop loc_953878 | decrement ECX and repeat as long as >0. [...]
Running this as exmaple for the first encrypted string as shown in the first picture: crypted string len | key | | remaining len | | 07 06 05 04 03 02 01 07 B2 C0 C6 DB DB DE DE B3 xor key (B2) -- -- 72 74 69 69 6c 6c 01 xor remaining len -- -- 75 72 6c 6d 6f 6e 00 ASCII -- -- u r l m o n -- So the first decrypted string here resolves nicely to "urlmon". Let's automate for all strings again.
Decrypt All The Strings
First, we locate the string decryption function. This time we can use regex r"\xE8....\x55\x89\xe5\x60.{8,16}\x30.\x30" which again gives a unique hit. This time, we first locate all calls to this function, like in the post on function decryption. For this we can use the regex r"\xE8" again to find all potential "call rel_offset" instructions.
We apply the same address math and check if the call destination
(calculated as: image_base + call_origin + relative_call_offset + 5) is
equal to the address of our string decryption function.
In this case, we can store the call_origin as a candidate for string decryption.
Next, we run again over all calls and check if a call to one of these string decryption candidates happens - this is very likely one of the "calling over encrypted strings" locations as explained earlier. This could probably have been solved differently but it worked for me.
Next we extract and decrypt the string, then patch it again in the binary.
I also change the "call over encrypted string" to a jump (first byte 0xE8->0xE9) because IDA likes this more and will not create wrongly detected functions later on.
About two weeks ago I came across an interesting sample using an interesting anti-analysis pattern.
The anti-analysis technique can be best described as "runtime-only code decryption". This means prior to execution of a function, the code is decrypted, then executed and finally encrypted again, but with a different key.
Malwarebytes has already published an analysis on this family they called "Fobber".
However, in this blog post I wanted to share how to "unwrap" the sample's encrypted functions for easier analysis. There is also another blog post detailing how to work around the string encryption.
The sample and code related to this blog post can be found on bitbucket.
Fobber's Function Encryption Scheme
First off, let's have a look how Fobber looks in memory, visualized by IDA's function analysis:
IDA's first view on Fobber.
IDA only recognizes a handful of functions. Among these is the actual code decryption routine, as well as some code handling translating relevant addresses of the position independent code into absolute offsets.
Next, a closer look at how the on-demand decryption/encryption of functions works:
The Fobber-encrypted function sub_95112A, starting with call to decryptFunctionCode.
We can see that function sub_95112A starts with a call to what I renamed "decryptFunctionCode":
Fobber's on-demand decryption code for functions, revealing the parameter offsets neccessary for decryption.
This function does not make use of the stack, thus it is surrounded by a simple pushad/popad prologue/epilogue. We can see that some references are made relative to the return address (initially put into esi by copying from [esp+20h]):
Field [esi-7] contains a flag indicating whether or not the function is already decrypted.
Field [esi-8h] contains the single byte key for encryption, while
field [esi-Ah] contains the length of the encrypted function, stored xor'ed with 0x461F.
The actual cryptXorCode takes those values as parameters and then loops over the encrypted function body, xor'ing with the current key and then updating the key by rotating 3bit and adding 0x53.
Function for decrypting one function, given the neccessary parameters.
After decryption, our function makes a lot more sense and we can see the default function prologue (push ebp; mov ebp, esp) among other things.
The decrypted equivalent of function sub_95112A, revealing some "real" code.
Also note the parameters:
0x951125 - key: 0x7B
0x951126 - length: 0x4629^0x461F -> 0x36 bytes
0x951128 - encryption flag: 0x01
So far so good. Now let's decrypt all of those functions automatically.
Decrypt All The Things
First, we want to find our decryption function. For all Fobber samples I looked at, the regex r"\x60\x8B.\x24\x20\x66" was delivering unique results for locating the decryption function.
Next, we want to find all calls to this decryption function. For this we can use the regex r"\xE8" to find all potential "call rel_offset" instructions.
Then we just need to do some address math and check if the call destination (calculated as: image_base + call_origin + relative_call_offset + 5) is equal to the address of our decryption function.
Should this be the case, we can extract the parameters as described above and decrypt the code.
We then only need to exchange the respective bytes in our binary with the decrypted bytes. In the following code I also set the decryption flag and fix the function ending with a "retn" (0xC3) instruction to ease IDA's job of identifying functions afterwards. Otherwise, rinse/repeat until all functions are decrypted.
However, we are not quite done yet, as IDA still barfs on a couple of functions.
Conclusion
After decrypting all functions, we can already start analyzing the sample effectively.
But we are not quite done yet, and the second post looks closer at the inline usage of encrypted strings.
This blog post details how the more recent versions of Andromeda store their C&C URLs and RC4 key and how this information can be bruteforced from a memory dump.
Storage Format
The Andromeda configuration always starts with the value that is transferred as "bid" to the C&C server.
It is 4 bytes long and most likely resembles a builder / botnet ID. In some binaries I had a look at, this was likely a Y-M-D binary date as in the example shown below: 14-07-03.
After an arbitrary number of random bytes concatenated to the "bid", the binary RC4 key of length 16 bytes follows.
This key is both used to decrypt the configuration as well as to encrypt the C&C traffic.
Note that this key is stored in reversed order to decrypt the configuration buffer.
Next, more arbitrary random bytes are added, and then a linked list of encrypted C&C URLs follows.
The first byte of each list entry is the offset to the next list item; a zero byte pointer indicates the end of the list.
Each list entry is simply encrypted with the reversed RC4 key as described previously, resulting in the crypted C&C entries having identical substrings at the start, the crypted equivalent of "http" => "\x0D\x4C\xD8\xDB".
Andromeda config buffer and fake RC4 key
Concealment of the configuration on bot initialization
During its initialization, the Andromeda bot parses this configuration buffer and stores its parts on the heap. Each data blob is prefixed with an indicator (crc32 over part of host processes' header, or 0x706e6800, xor bot_id), allowing the malware to identify its fragments on the heap in a similar way to the technique known as egg hunting.
function used to handle the config and store rc4_key + C&C URLs on the heap
Afterwards, as a means of anti-analysis, the parsing routine is overwritten with a static 4 bytes (to kill the function prologue) and another function of the bot (in this case the function responsible for settings up hooking) in order to destroy the pointers to the RC4 key and C&C list.
top: function to destroy the parseConfig by overwriting with installHooks(), left: installHooks() right: resulting parseConfig
Extraction of RC4 key and C&C URLs
Although the exact offsets of RC4 key and C&C URL list are not available when examining a finally initialized Andromeda memory image in the injected process, it is possible to recover this information through guessing.
Finding the "bid"
Characteristic for all encountered versions of Andromeda is a format string similar to the following:
id:%lu|bid:%lu|os:%lu|la:%lu|rg:%lu
or more recently:
{"id":%lu,"bid":%lu,"os":%lu,"la":%lu,"rg":%lu}
As its fields are likely filled in with a *sprintf* function, we can identify the offset of the "bid" by statically examining parameters passed to said string format API call (this can e.g. be achieved with a carefully crafted regex).
reference to the botnet/builder id "bid" with a characteristic sequence of instructions
Treating the "bid" as start for the potential configuration buffer, we can assume its end by searching for a zero dword value starting at the offset of the "bid".
For the tested memory dumps, the resulting potential configuration buffer had a length of around 300 bytes.
Identifying crypted C&C URL candidates
As described above, the C&C URLs are stored as a linked list.
Randomly assuming that a server address will be somewhere between 0x8 and 0x30 characters long, we can extract all byte sequences from the potential configuration buffer that match this property (start bytes highlighted): 0000 14 07 03 00 d4 e2 04 63 53 03 86 e4 82 5d 97 1c .......cS....].. 0010 c6 f8 58 9c f0 8f 2c da 79 0b 6d 1c ce cb 9d ba ..X...,.y.m..... 0020 81 c5 c9 42 60 f1 63 48 87 45 00 c1 fe 34 8b bf ...B`.cH.E...4.. 0030 bb 84 93 0d b7 ca 47 dc 2f 8a 35 8a 2d 48 87 31 ......G./.5.-H.1 0040 33 b5 b1 3d 4f a8 2f 49 17 4d e4 58 93 11 a4 81 3..=O./I.M.X.... 0050 3b 4e 1e 8a 28 79 f7 8f 16 5a 85 2f0a 11 3e 4a ;N..(y...Z./..>J 0060 df 5b 70 06 57 9d 33 f0 80 ae ad 6a 13 d2 ed 95 .[p.W.3....j.... 0070 50 ce e7 24 0d 4c d8 db 84 4d 56 13 40 83 06 2d P..$.L...MV.@..- 0080 3c 13 f5 52 59 f3 34 1f 84 ac 5c 46 13 ec e8 12 <..RY.4....F.... 0090 c8 50 8d 87 8b 59 a8 d6 17 0d 4c d8 db 84 4d 56 .P...Y....L...MV 00a0 4e 52 c6 5c 3a 3b 54 f3 51 58 f1 39 58 90 a1 02 NR..:;T.QX.9X... 00b0 1f 0d 4c d8 db 84 4d 56 13 40 83 06 2d 3c 19 fb ..L...MV.@..-<.. 00c0 4b 55 ba 2f 13 94 e6 1b 4b 18 e4 bf 55 d6 5c 98 KU./....K...U... 00d0 1d 0d 4c d8 db 84 4d 56 0d 54 9e 15 24 21 19 ff ..L...MV.T..$!.. 00e0 11 53 e6 26 59 89 a7 16 40 04 af b7 13 d6 00 f0 .S.&Y...@....... 00f0 1b cb c7 a3 c5 68 48 ca b7 6a 91 bb 83 e9 07 ee .....hH..j...... 0100 d2 78 8b 88 85 78 28 6b 3f 39 72 36 6f 88 ff db .x...x(k?9r6o... 0110 63 6d b4 f5 f3 89 99 c5 68 8d 68 6b 7b 62 9d 05 cm......h.hk{b..
resulting in the following candidate sequences (offset, length, start bytes):
Next, we can try to decrypt these URL candidates by using all possible RC4 keys from the potential configuration buffer.
For this, we take every consecutive 16 bytes, hex encode them, reverse their order, and perform RC4 against all C&C URL candidates.
Example: candidate sequence at offset 0xd1, length: 0x1d bytes:
finally we hit a result of 687474703a2f2f which translates to "http://" and the whole URL decrypts to "hxxp://sunglobe.org/index.php" (defanged).
As soon as we decrypt the first sequence starting with "http" we have likely identified the correct RC4 key and can proceed to decrypt all other candidates to complete the list of C&C URLs.
RC4 key used for config: d31b5b33137884d2a853a8f2cd74ac7b
Actual traffic RC4 key: b7ca47dc2f8a358a2d48873133b5b13d
It's obvious that the above described method can be optimized here and there. But since it executes in less than a second on a given memdump and gave me good results on a collection of Andromeda dumps, I didn't bother to improve it further.
