Thursday, August 27, 2015

(Sys)Call Me Maybe: Exploring Malware Syscalls with PANDA

System calls are of great interest to researchers studying malware, because they are the only way that malware can have any effect on the world – writing files to the hard drive, manipulating the registry, sending network packets, and so on all must be done by making a call into the kernel.

In Windows, the system call interface is not publicly documented, but there have been lots of good reverse engineering efforts, and we now have full tables of the names of each system call; in addition, by using the Windows debug symbols, we can figure out how many arguments each system call takes (though not yet their actual types).

I recently ran 24,389 malware replays under PANDA and recorded all the system calls made, along with their arguments (just the top-level argument, without trying to descend into pointer types or dereference handle types). So for each replay, we now have a log file that looks like:

3f9b2340 NtGdiFlush
3f9b2340 NtUserGetMessage 0175feac 00000000 00000000 00000000
3f9b2120 NtCreateEvent 0058f8d8 001f0003 00000000 00000000 00000000
3f9b2120 NtWaitForMultipleObjects 00000002 0058f83c 00000001 00000000 00000000
3f9b2120 NtSetEvent 000002ec 00000000
3f9b2120 NtWaitForSingleObject 000002f0 00000000 0058f89c
3f9b2120 NtReleaseWorkerFactoryWorker 00000050
3f9b2120 NtReleaseMutant 00000098 00000000
3f9b2120 NtWaitForSingleObject 000005a4 00000000 00000000
3f9b2120 NtWaitForMultipleObjects 00000002 00dbf49c 00000001 00000000 00000000
3f9b2120 NtReleaseMutant 00000098 00000000
3f9b2120 NtWaitForMultipleObjects 00000002 00dbf4a8 00000001 00000000 00dbf4c8
3f9b2120 NtWaitForMultipleObjects 00000002 00dbf49c 00000001 00000000 00000000
3f9b2120 NtClearEvent 000002ec
3f9b2120 NtReleaseMutant 00000098 00000000
3f9b2120 NtWaitForMultipleObjects 00000002 00dbf49c 00000001 00000000 00000000
3f9b2120 NtReleaseMutant 000001e8 00000000
3f9b2120 NtWaitForMultipleObjects 00000002 00dbf3b8 00000001 00000000 00000000
3f9b2120 NtReleaseMutant 00000158 00000000
3f9b2120 NtCreateEvent 00dbeed4 001f0003 00000000 00000000 00000000
3f9b2120 NtDuplicateObject ffffffff fffffffe ffffffff 002edf50 00000000 00000000 00000002

3f9b2120 NtTestAlert
...

The first column identifies the process that made the call, using its address space as a unique identifier. The second gives the name of the call, and the remaining columns show the arguments passed to the function.

As usual, this data can be freely downloaded; the data set is 38GB. Each log file is compressed; you can use the showsc program (included in the tarball) to display an individual log file:

$ ./showsc 32 32bit/008d065f-7f5d-4a86-9995-970509ff3999_syscalls.dat.gz

You can download the data set here:

Interesting Malware System Calls

As a first pass, we can look at what the least commonly used system calls are. These may be interesting because rarely used system calls are more likely to contain bugs; in the context of malware, invoking a vulnerable system call can be a way to achieve privilege escalation.

Here are a few that came out from sorting the list of system calls in the malrec dataset and then searching Google for some of the least common:
  • NtUserMagControl (1 occurrence) One of many functions found by j00ru to cause crashes due to invalid pointer dereferences when called from the context of the CSRSS process
  • NtSetLdtEntries (2 occurrences) Used as an anti-debug trick by some malware
  • NtUserInitTask (3 occurrences) Used as part of an exploit for CVE-2012-2553
  • NtGdiGetNearestPaletteIndex (3 occurrences) Used in an exploit for MS07-017
  • NtQueueApcThreadEx (5 occurrences) Mentioned as a way to get attacker-controlled code into the kernel, allowing one to bypass SMEP
  • NtUserConvertMemHandle (5 occurrences) Used to replace a freed kernel object with attacker data in an exploit for CVE-2015-0058
  • NtGdiEnableEudc (9 occurrences) Used in a privilege escalation exploit where NtGdiEnableEudc assumes a certain registry key is of type REG_SZ without checking, allowing an attacker to overflow a stack buffer (I was unable to find anything about whether this has been patched – Update: Mark Wodrich points out that this is CVE-2010-4398 and it was patched in MS11-011)
  • NtAllocateReserveObject (11 occurrences) Used for a kernel pool spray
  • NtVdmControl (55 occurrences) Used for the famous CVE-2010-0232 bug; Tavis Ormandy won the Pwnie for Best Privilege Escalation Bug in 2010 for this.
Of course, we can't say for sure that the replays that execute these calls actually contain exploitation attempts. After all, there are benign ways to use each of the calls, or they wouldn't be in Windows in the first place :) But these are a few that may reward closer examination; if they are in fact exploit attempts, you can then use PANDA's record and replay facility to step through the exploit in as much detail as you like. You can even use PANDA's recently-fixed QEMU gdb stub to go through the exploit instruction by instruction.

You can peruse the full list of system calls and their frequencies here: 32-bit, 64-bit. Let me know if you find any other interesting calls in there :)

Updates 8/28/2015

If you want to know which log files have which system calls without processing all of them, I have created an index that lists the unique calls for each replay:
Also, Reddit user trevlix wondered whether the lack of pointer dereferencing was inherent to PANDA or something I'd just left out. My response:

Yes, it is possible to do that. I just wasn't able to because I didn't have access to full system call prototypes. E.g., to follow pointers for something like NtCreateFile, you need to know that its full prototype is
NTSTATUS NtCreateFile(
  _Out_    PHANDLE            FileHandle,
  _In_     ACCESS_MASK        DesiredAccess,
  _In_     POBJECT_ATTRIBUTES ObjectAttributes,
  _Out_    PIO_STATUS_BLOCK   IoStatusBlock,
  _In_opt_ PLARGE_INTEGER     AllocationSize,
  _In_     ULONG              FileAttributes,
  _In_     ULONG              ShareAccess,
  _In_     ULONG              CreateDisposition,
  _In_     ULONG              CreateOptions,
  _In_     PVOID              EaBuffer,
  _In_     ULONG              EaLength
);
You furthermore have to know how big an OBJECT_ATTRIBUTES struct is, so that when you dereference the pointer you know how many bytes to read and store in the log.
If you wanted to collect extra information about any of the logs posted, it's possible since they are full-system traces and can be replayed :) Supposing you have a syscall trace file like0a1a1a77-d4f1-43e0-bc14-4f34f7d96820_syscalls.dat.gz, you can use the UUID to find it on malrec and download the log file:
Then you'd just unpack that log (scripts/rrunpack.py in the PANDA directory) and replay it with a PANDA plugin that understands how to dereference the various pointers involved. For reference, you can see the PANDA plugin I originally used to gather the syscall traces:
And you can see on lines 108 and 119 where you'd have to add in code to read the dereferenced values.

Monday, August 24, 2015

One Weird Trick to Shrink Your PANDA Malware Logs by 84%

When I wrote about some of the lessons learned from PANDA Malrec's first 100 days of operation, one of the things I mentioned was that the storage requirements for the system were extremely high. In the four months since, the storage problem only got worse: as of last week, we were storing 24,000 recordings of malware, coming in at a whopping 2.4 terabytes of storage.

The amount of data involved poses problems not just for our own storage but also for others wanting to make use of the recordings for research. 2.4 terabytes is a lot, especially when it's spread out over 24,000 HTTP requests. If we want our data to be useful to researchers, it would be great if we could find better ways of compressing the recording logs.

As it turns out, we can! The key is to look closely at what makes up a PANDA recording:
  • The log of non-deterministic events (the -rr-nondet.log files)
  • The initial QEMU snapshot (the -rr-snp files)
The first of these is highly redundant and actually compresses quite well already – the xz compression used by PANDA's rrpack.py usually manages to get around a 5-6X reduction for the nondet log. The snapshots also compress pretty well, at around 4X.

So where can we find further savings? The trick is to notice that for the malware recordings, each run is started by first reverting the virtual machine to the same state. That means that the initial snapshot files for our recordings are almost all identical! In fact, if we do a byte-by-byte diff, the vast majority differ by only a few bytes – most likely a timer value that increments in the short time between when we revert to the snapshot and begin our recording.

With this observation in hand, we can instead store the malware recordings in a new format. The nondet log will still be compressed with xz, but now the snapshot for each will now instead be stored as a binary diff with respect to a reference snapshot. Because we have two separate recording platforms and have changed the initial environment used by Malrec a few times, the total number of reference snapshots we need is 8 – but this is a huge improvement over storing 24,000 snapshots! The binary diff for each recording then requires only a handful of bytes to specify.

The upshot of all of this is that a dataset of 24,189 PANDA malware recordings now takes up just 387 GB, a savings of 84%. This is pretty astonishing – the recordings in the archive contain 476 trillion instructions' worth of execution, meaning our storage rate is 1147.5 instructions per byte! As a point of comparison, one recent published instruction trace compression scheme achieved 2 bits per instruction; our compression is 0.007 bits per instruction – though this comparison is somewhat unfair since that paper can't assume a shared starting point.

You can download this data set as a single file from our MIT mirror; please share and mirror this as widely as you like! There is a README included in the archive that contains instructions for extracting and replaying any of the recordings. Click the link below to download:


Stay tuned, too – there's more cool stuff on the way. Next time, I'll be writing about one of the things you can do with a full-trace recording dataset like this: extracting system call traces with arguments. And of course that means I'll have a syscall dataset to share then as well :)