Monday, 21 August 2017

Monkey Unpacks Some Python

UNPACK-ing Python .. Now with added monkey!
Some forensic folks have suggested that a Python tutorial on how to read/print binary data types might be helpful to budding Python programmers in the community.
So in this post, we will simulate reverse engineering a fictional contact file format and then write a Python script to extract/print out the values.
For brevity, this post ass-umes the reader has a basic knowledge of Python (i.e. they can launch a script and know about functions/assigning variables etc.). There are plenty of introductory tutorials online - if you are a beginner, you might want to check out the Google Developer Python course before proceeding.

The script (unpack-tute.py) has been tested with both Python v2.7.12 and Python 3.4.1 on a Win7x64 PC.
Historically, Python 2 had more supported 3rd party libraries. Consequently, it was the first version of Python that this monkey learned and we are actually more familiar with Python 2. Python 2's End Of Life is currently scheduled for April 2020 so there's a few years left. However, as this script does not rely on 3rd party libraries, we have adapted it to run on both Python 2 and 3.
The main difference affecting this script was that Python 3 treats strings as Unicode by default so we had to add an encode('utf-8') call when searching through our data file.

There is more than one way to code a solution. We have tried to make this code easy to follow instead of making it "Pythonic" (whatever that even means) or by adding lots of error checking code (if you write a script, you should know how it to use it!).
The Python script (unpack-tute.py) and sample binary file (testctx.bin) will be posted to my brand-monkey-spanking-new GitHub Python Tutorials folder.

So, here's a screenshot of the "testctx.bin" file we want to read:
Screenshot of "testctx.bin" (brought to us courtesy of WinHex!)

Note: The first contact record is highlighted and offsets are listed in decimal. Curious George is ... curious?

Using some reverse engineering strategies that we previously wrote about here we can make a few observations regarding the structure of each Contact record ...

  • We can see there's a repeated "ctx!" string before each Contact record.
  • After each record's "ctx!" field, there is a Little Endian 2 byte field that seems to increase with each subsequent record (eg 0x0100 at decimal offset 68, 0x02FF at decimal offset 516, 0xFFFF at decimal offset 804). For initial classification, we will say its an index record number.
  • Each record has a UTF16LE (ie 2 bytes per character) string that contains a name (eg George).
  • Each record has a UTF8/ASCII (ie 1 byte per character) string that contains a phone number (eg 5551234).
  • Before each of the strings, there is a one byte integer corresponding to the string size in bytes.
  • The last field seems to be a 4 byte field. By observing which bytes vary and which bytes remain constant(ie the left most bytes change more rapidly than the rightmost bytes), we suspect the last field is a Little Endian timestamp field. Feeding in the first record's last 4 bytes (ie 0x26CDDB56) into DCode results in a valid date/time for a Unix 32 bit Little Endian timestamp
DCoding the Contact timestamp


So here's our contact record format:
Contact record data structure


And here's a summary of what we want the script to do:

1. Open "testctx.bin" file (read only)
2. Store file contents
3. Search file contents for ctx! markers
4. For each hit:
    4a. Print hit offset
    4b. Extract Index Number field and print
    4c. Extract Name Length field and print
    4d. Extract Name String (UTF16LE) field and print
    4e. Extract Phone Length field and print
    4f. Extract Phone String (UTF8) field and print
    4g. Extract Unix Timestamp field and print (in ISO format)

5. Close file

Simples!

The Script

OK now that we know what we want to do, here's how we implement each step in code ...

Steps 1 & 2 Open file and store file contents (See "unpack-tute.py" lines 25-33):
1. Open "testctx.bin" file (read only)
2. Store file contents


For step 1, we open the "textctx.bin" file in read-only binary mode (what the "rb" stands for):
    fb = open(filename, "rb")

We chose read-only mode because we don't want to change the file contents and we chose binary mode because we are interpreting the file as raw bytes (not text).
Then to read/store the file contents, we call:
    filecontent = fb.read()

So the "filecontent" variable will now contain every byte from the "testctx.bin" file and individual bytes can be accessed directly using the "slice" notation.
For example, filecontent[0:3] is 3 bytes long and includes the bytes at offsets 0, 1 and 2. It does NOT include the byte at offset 3.
If we replace the start/end locations of our slice example with a variable called startoffset, we get:
    filecontent[startoffset:(startoffset+3)]
This will include the 3 bytes at start, start+1, start+2 only.
The reader might want to remember that little notation nugget as monkey has the feeling it will be popping up again later ... (Hehe, Poo jokes are still floating around in 2017!)

Step 3: Search file contents for "ctx!" markers (See "unpack-tute.py" lines 35-49):
Knowing that "ctx!" encoded in ASCII/UTF8 is x63 x74 x78 x21, we can use a variable "searchstring" to represent our search term in hex:
    searchstring = "\x63\x74\x78\x21"

We now consider the "filecontent" variable as one big string of bytes ...
Python string types have a find() method which searches the parent string for a substring. The find() method returns -1 if the substring is not found otherwise, it returns the first offset where it found the substring. The find() method can also take an starting offset argument so we can use a while loop to repeatedly call find() with an incrementing starting offset until we get no more hits. Thus we can find an offset for each substring hit in the parent string, which we can then store in a Python list called "hitlist".
Here's the code:
    nexthit = filecontent.find(searchstring.encode('utf-8'), 0)
    hitlist = []
    while nexthit >= 0:
        hitlist.append(nexthit)
        nexthit = filecontent.find(searchstring.encode(), nexthit + 1)

We use searchstring.encode('utf-8') because of Python 3 compatibility issues. Python 3 treats all strings as Unicode by default, where as we need to search in UTF8 (ie byte by byte). So we have to encode the searchstring as UTF8 before running the search.
Default Python 2 strings are represented as sequences of raw bytes so calling searchstring.encode('utf-8') in Python 2 has no real effect - we could have used Python 2 lines such as:
    nexthit = filecontent.find(searchstring, 0)
and
    nexthit = filecontent.find(searchstring, nexthit + 1)
This was the only major script change required for Python2 and Python 3 compatibility.

Step 4: Looping through each hit (See "unpack-tute.py" lines 50-88):
Now we have our hitlist of offsets to "ctx!" markers and we know how each contact record is structured, so we can iterate through the filecontent variable using a for loop and extract/print the data we need using the slice notation we discussed previously.

4a. We print out each hit offset in both decimal and hexadecimal.
    print("\nHit found at offset: " + str(hit) + " decimal = " + hex(hit) + " hex")

We use the str() function to convert the "hit" offset variable into a decimal string for printing and the hex() function to convert the hit offset variable into a hexadecimal string.

4b. The first field ("Index Number") after the "ctx!" marker will start 4 bytes after the hit offset. To calculate the offset, we can use code like:
    indexnum_offset = hit + 4 
As we have already read the entire file into filecontent, we can access the 2 byte "Index Number" field and interpret it as a Little Endian 2 byte integer as follows:
    indexnum = struct.unpack("<H", filecontent[indexnum_offset:(indexnum_offset+2)])[0]

We are using the struct module's "unpack" function on the given filecontent slice to interpret the slice as a LE 2 byte integer and store it in the "indexnum" variable.
The "<H" argument tells unpack how to interpret the raw bytes i.e. "<" for Little Endian, "H" for unsigned 2 byte integer.
The unpack function returns a tuple (kinda like a sequence of variables) so we specify the "[0]" at the end to retrieve the first converted value. It seems a bit weird until you find out that you can chain types together in the same unpack call. For example, "<HH" specifies 2 consecutive LE unsigned 2 byte integers. Unfortunately, we cannot use chaining here due to the variable length of Name/Phone strings in the contact record.
There's a bunch of other unpack types defined in the Python help documentation (search for "pack unpack").

We can now print out our interpreted "indexnum" value but we need to use the str() function to convert our Index Number integer into a printable string. We can use code such as:
    print("indexnum = " + str(indexnum))


We can re-use a similar pattern of code for the remaining fields in the record.
That is, we calculate the offset of field X, interpret those slice bytes and then print.
Because we know the record field sizes (or can read them e.g. via "Name Length" size byte), calculating the offsets becomes an exercise in adding field sizes to previous field offsets to get to the next offset address.

4c. So for the second field ("Name Length") we can use:
    namelength_offset = indexnum_offset + 2
    print("namelength_offset = " + str(namelength_offset))
    namelength = struct.unpack("B", filecontent[namelength_offset:(namelength_offset+1)])[0]
    print("namelength = " + str(namelength))

For the "Name Length" field (one byte long), we use a starting offset ("namelength_offset") which is 2 bytes past the "Index Number" offset ("Index Number" field is 2 bytes long).
We use unpack with the "B" argument as we are interpreting the 1 byte at filecontent[name_length_offset:(namelength_offset+1)] as an unsigned 1 byte integer and storing it in the "namelength" variable.

4d. For the third field ("Name String") we can use:
    namestring_offset = namelength_offset + 1
    namestring = filecontent[namestring_offset:(namestring_offset+namelength)].decode('utf-16-le')
    print("namestring = " + namestring)

After calculating the "Name String" field offset (should be one byte past the "Name Length" field), we can use the string.decode('utf-16-le') method to interpret the filecontent[namestring_offset:(namestring_offset+namelength)] slice as a UTF16LE string and store it in the "namestring" variable.

4e. For the fourth field ("Phone Length") we can use:
    phonelength_offset = namestring_offset + namelength
    phonelength = struct.unpack("B", filecontent[phonelength_offset:(phonelength_offset+1)])[0]
    print("phonelength = " + str(phonelength))

After calculating the "Phone Length" field offset (should be "Name Length" bytes past the "Name String" offset), we use unpack with the "B" argument as we are interpreting the 1 byte at filecontent[phonelength_offset:(phonelength_offset+1)] as an unsigned 1 byte integer and storing it in the "phonelength" variable.

4f. For the fifth field ("Phone String") we can use:
    phonestring_offset = phonelength_offset + 1
    print("phonestring_offset = " + str(phonestring_offset))
    phonestring = filecontent[phonestring_offset:(phonestring_offset+phonelength)].decode('utf-8')
    print("phonestring = " + phonestring)

After calculating the "Phone String" field offset (should be one byte past the "Phone Length" field), we can use the string.decode('utf-8') method to interpret the filecontent[phonestring_offset:(phonestring_offset+phonelength)] slice as a UTF8 string and store it in the "phonestring" variable.

4g. For the sixth and last field ("Unix Timestamp") we can use:
    timestamp_offset = phonestring_offset + phonelength
    print("timestamp_offset = " + str(timestamp_offset))
    timestamp = struct.unpack("<I", filecontent[timestamp_offset:(timestamp_offset+4)])[0]
    print("raw timestamp decimal value = " + str(timestamp))
    timestring = datetime.datetime.utcfromtimestamp(timestamp).strftime("%Y-%m-%dT%H:%M:%S")
    print("timestring = " + timestring)

We calculate the timestamp offset as being "Phone Length" bytes past the "Phone String" field and print the timestamp offset to help with debugging.
We use unpack with the "<I" argument to interpret the 4 byte filecontent[timestamp_offset:(timestamp_offset+4)] slice as a LE unsigned 4 byte integer and then store the integer value in the "timestamp" variable.
eg interprets 0x26CDDB56 LE as 0x56DBCD26 BE = 1457245478 decimal = number of seconds since 1JAN1970.
We then call the datetime.datetime.utcfromtimestamp() method to create a Python "datetime" object using the number of seconds since 1JAN1970. The returned datetime object has a "strftime" method we can call to obtain a human readable ISO format string. The "%Y-%m-%dT%H:%M:%S" argument to strftime() specifies that we want a datetime string formatted as Year-Month-DayTHour:Minute:Second.

Step 5: After we process all of the "ctx!" hits, we close the file (See "unpack-tute.py" line 89):
    fb.close()

For shiggles, we also print out the number of hits in the hitlist on line 91 before the script finishes.
    print("\nProcessed " + str(len(hitlist)) + " ctx! hits. Exiting ...\n")

Running the script

For Python v2.7.12:
In a Win7x64 command terminal window with "unpack-tute.py" and "testctx.bin" copied to "c:\":

C:\>c:\Python27\python.exe unpack-tute.py
Running unpack-tute.py v2017-08-19


Hit found at offset: 64 decimal = 0x40 hex
indexnum = 1
namelength_offset = 70
namelength = 12
namestring = George
phonelength = 7
phonestring_offset = 84
phonestring = 5551234
timestamp_offset = 91
raw timestamp decimal value = 1457245478
timestring = 2016-03-06T06:24:38

Hit found at offset: 512 decimal = 0x200 hex
indexnum = 65282
namelength_offset = 518
namelength = 18
namestring = King Kong
phonelength = 9
phonestring_offset = 538
phonestring = +15554321
timestamp_offset = 547
raw timestamp decimal value = 1457245695
timestring = 2016-03-06T06:28:15

Hit found at offset: 800 decimal = 0x320 hex
indexnum = 65535
namelength_offset = 806
namelength = 30
namestring = Magilla Gorilla
phonelength = 10
phonestring_offset = 838
phonestring = +445552468
timestamp_offset = 848
raw timestamp decimal value = 1457258495
timestring = 2016-03-06T10:01:35

Processed 3 ctx! hits. Exiting ...


C:\>

For Python 3.4.1:
 In a Win7x64 command terminal window with "unpack-tute.py" and "testctx.bin" copied to "c:\":

C:\>c:\Python34\python.exe unpack-tute.py
Running unpack-tute.py v2017-08-19


Hit found at offset: 64 decimal = 0x40 hex
indexnum = 1
namelength_offset = 70
namelength = 12
namestring = George
phonelength = 7
phonestring_offset = 84
phonestring = 5551234
timestamp_offset = 91
raw timestamp decimal value = 1457245478
timestring = 2016-03-06T06:24:38

Hit found at offset: 512 decimal = 0x200 hex
indexnum = 65282
namelength_offset = 518
namelength = 18
namestring = King Kong
phonelength = 9
phonestring_offset = 538
phonestring = +15554321
timestamp_offset = 547
raw timestamp decimal value = 1457245695
timestring = 2016-03-06T06:28:15

Hit found at offset: 800 decimal = 0x320 hex
indexnum = 65535
namelength_offset = 806
namelength = 30
namestring = Magilla Gorilla
phonelength = 10
phonestring_offset = 838
phonestring = +445552468
timestamp_offset = 848
raw timestamp decimal value = 1457258495
timestring = 2016-03-06T10:01:35

Processed 3 ctx! hits. Exiting ...


C:\>

We can see that all of the name and phone strings are complete / as shown in the Hex view picture.
We also verified that each "timestring" value corresponded to it's raw LE hex value using Dcode.

Final Thoughts

After you know the basics of a language, programming is a skill best sharpened by working on actual projects (not reading books or blog posts).
Google and StackOverflow are your friends when researching how to code common tasks in Python.
Which makes print statements your No-BS-tell-it-like-it-is best friend when debugging (e.g. print offset addresses and/or values to debug). A well placed print statement can be the easiest way of finding out that your fifth cola/coffee didn't do you any favours.

The code in this script is intended for use with files that can fit into memory (ie 0 MB to *maybe* hundreds of MB).
Larger files may require breaking up the file into chunks before reading/processing.

In writing this script, we used Notepad++ (v6.7.9.2) with the Language set to Python to get the funky syntax highlighting (eg comments in green, auto-indenting). The TAB size was set to 4 spaces via the Settings, Preferences, Tab Settings menu. We disabled "Word Wrap" (under View menu) and enabled line numbers (under Settings, Preferences, Editing menu) so if/when you get a runtime error, you can find the relevant line more readily.

If you are in the forensic community and found this post helpful or you're in the forensic community and had some questions/thoughts about the code, please leave a comment or send me an email (No, I will not do your homework/assignment! But if its for a new artifact for a case, monkey might be convinced ;).


Wednesday, 4 January 2017

Monkey Plays (LAN) Turtle

OMG! Sooo Turtle-y!

The Hak5 LAN Turtle recently plodded across our desk so we decided to poke it with a stick and see how effective it is in capturing Windows (7) credentials.
From the LAN Turtle wiki:
The LAN Turtle is a covert Systems Administration and Penetration Testing tool providing stealth remote access, network intelligence gathering, and man-in-the-middle monitoring capabilities.
Housed within a generic "USB Ethernet Adapter" case, the LAN Turtle’s covert appearance allows it to blend into many IT environments.
It costs about U$50 and looks like this:




It consists of a System-On-Chip running an openwrt (Linux) based OS. Amongst other things, it can act like a network bridge/router between:
- a USB Ethernet interface which you plug into your target PC. This interface can also be ssh'd into via its static IP address 172.16.84.1 (for initial configuration and copying off creds).
- a 10/100 Mbps Ethernet port which you can use to connect the Turtle to the Internet (providing remote shell access and allowing the install of modules/updates from LANTurtle.com). It is not required to capture creds during normal operation.

It also has 16 MB on board Flash memory and can be configured to run a bunch of different modules via a Module Manager.

By using the Turtle's USB Ethernet interface to create a new network connection and then sending the appropriate responses, the Turtle is able to capture a logged in user's Windows credentials. Apparently Windows will send credentials over a network whether the screen is locked or not (a user must be logged in).

We will be using the QuickCreds module written by Darren Kitchen which was based on the research of Rob "Mubix" Fuller.
To send the appropriate network responses, QuickCreds calls Laurent Gaffie's Responder Python script and saves credentials (eg NTLMv2 for our Win 7 test case) to numbered directories in /root/loot. The amber Ethernet LED will blink rapidly while QuickCreds is running. When finished capturing (~30 secs to a few minutes), the amber LED is supposed to remain lit.

But wait - there's more! The turtle can also offer remote shell/netcat/meterpreter access, DNS spoofing, man-in-the-middle browser attacks, nmap scans and so much more via various downloadable modules. Alas, we only have enough time/sanity/Turtle food to look at the QuickCreds module.

Setup

We will be both configuring and testing the Turtle on a single laptop running Windows 7 Pro x64 with SP1. Realistically, you would configure it on one PC and then plug it into a separate target PC.
 
We begin setup by plugging the Turtle into the configuration PC and using PuTTY to ssh as root to 172.16.84.1. For proper menu display, be sure to adjust the PuTTY Configuration's Windows, Translation, Remote character set to "Latin-1, Western Eur".

The default root Turtle password is sh3llz. Upon first login, the user is then prompted to change the root password.
Ensure an Internet providing Ethernet cable is plugged in to the Turtle's Ethernet port to provide access to LANTurtle.com updates.

Note: The Turtle may also require Windows to install the "Realtek USB FE Family Controller" Network Adapter driver before you can communicate with it.

Upon entering/confirming the new root password, you should see something like:

LAN Turtle Main Menu via PuTTY session


Under Modules, Module Manager, go to Configure, then Directory to select the QuickCreds module for download. You can select/check a module for download via the arrow/spacebar keys.

Return back to Modules, select the QuickCreds module, then Configure (this will take a few minutes to download/install/configure the dependencies from the Internet). Remember to have an Internet providing Ethernet cable plugged into the Turtle.

Select the QuickCreds Enable option so QuickCreds is launched whenever the Turtle is plugged into a USB port.
(Optional) You can also select the Start option to start the QuickCreds module now and it should collect your current Windows login creds.

We are now ready to remove the Turtle from our config PC and place it into a target PC's USB port.

If you're having issues getting the Turtle working, try to manually reset the Turtle following the "Manually Upgrading" wiki procedure at the bottom of this page.

There's also a Hak5 Turtle/QuickCreds demo and explanation video by Darren Kitchen and Shannon Morse thats well worth a view.

Capturing Creds

Insert the Turtle into the (locked) target PC and wait for the creds to be captured. Our Turtle's amber Ethernet light followed this pattern on insertion:
- ON/OFF
- OFF (10 secs)
- Blinking at 1 Hz (15 secs)
- OFF (1-2 secs)
- Rapid Blinking > 1 Hz (indefinitely or until we launch PuTTY when it remains ON)

From testing, once we see the rapid blinking, the creds have been captured.

If you have an Internet cable plugged in to the Turtle when capturing creds, you can also remote SSH into the Turtle to retrieve the captured creds.This is not in the scope of this post however.

For our testing, we will keep it simple and use PuTTY's scp to retrieve the stored creds (eg capture creds, retrieve Turtle, take Turtle back to base for creds retrieval):
We remove the Turtle from the target PC and re-insert it into our config PC. For our testing on a single laptop this meant - we removed the Turtle, unlocked the laptop and then re-inserted the Turtle.
Note: Due to the auto enable, the Turtle will also capture the config PC's creds upon insertion.

Now PuTTY in to the Turtle, then choose Exit to get to the Turtle command prompt/shell (shell ... Get it? hyuk, hyuk).

To find the latest saved creds we can type something like:

ls -alt /root/loot

which shows us the latest creds (corresponding to our current config PC) is stored under /root/loot/12/

root@turtle:~# ls -alt /root/loot/
-rw-r--r--    1 root     root           319 Jan  2 11:14 responder.log
drwxr-xr-x    2 root     root             0 Jan  2 11:13 12
drwxr-xr-x   14 root     root             0 Jan  2 11:11 .
drwxr-xr-x    2 root     root             0 Jan  2 11:01 11
drwxr-xr-x    2 root     root             0 Jan  2 11:00 10
drwxr-xr-x    2 root     root             0 Jan  2 10:46 9
drwxr-xr-x    2 root     root             0 Jan  2 08:58 8
drwxr-xr-x    2 root     root             0 Jan  2 08:49 7
drwxr-xr-x    2 root     root             0 Jan  2 08:46 6
drwxr-xr-x    2 root     root             0 Jan  2 08:35 5
drwxr-xr-x    2 root     root             0 Jan  2 08:34 4
drwxr-xr-x    2 root     root             0 Jan  2 08:26 3
drwxr-xr-x    2 root     root             0 Jan  2 08:21 2
drwxr-xr-x    2 root     root             0 Jan  2 08:20 1
drwxr-xr-x    1 root     root             0 Jan  2 08:20 ..
root@turtle:~#

So looking further at /root/loot/11/ (ie the creds from when we plugged the Turtle into the locked laptop) shows us a few log files and a text file containing our captured creds (ie HTTP-NTLMv2-172.16.84.182.txt).

root@turtle:~# ls /root/loot/11/
Analyzer-Session.log           Poisoners-Session.log
Config-Responder.log           Responder-Session.log
HTTP-NTLMv2-172.16.84.182.txt
root@turtle:~#


Our creds should be stored in HTTP-NTLMv2-172.16.84.182.txt and we can use the following command to check that the file contents look OK:

more /root/loot/HTTP-NTLMv2-172.16.84.182.txt

which should return something like:

admin::N46iSNekpT:08ca45b7d7ea58ee:88dcbe4446168966a153a0064958dac6:5c7830315c7830310000000000000b45c67103d07d7b95acd12ffa11230e0000000052920b85f78d013c31cdb3b92f5d765c783030

Where admin is the login name and the second field (eg N46iSNekpT) corresponds to the domain.
Note: This is an NTLMv2 example sourced from hashcat.

Once we have found the appropriate file containing the creds we want, we can use PuTTY pscp.exe to copy the files from the Turtle to our config PC.
From our Windows config PC we can use something like:
pscp root@172.16.84.1:/root/loot/11/HTTP-NTLMv2-172.16.84.182.txt .

to copy out the creds file. Note the final . to copy the creds file into the current directory on the config PC.

We can then feed this (file or individual entries) into hashcat to crack the user password. This is an exercise left for the reader.

Turtle Artifacts?

Now that we have our creds, lets see if we can find any fresh Turtle scat er, artifacts.

Starting with the Turtle plugged in to an unlocked PC, we look under the Windows Device Manager and find the Network adapter driver for the Turtle - ie the "Realtek USB FE Family Controller"

Turtle Network Adapter Driver Properties


The Details Tab from the Properties screen yields a "Device Instance Path" of:
USB\VID_0BDA&PID_8152\00E04C36150A

Similarly, the "Hardware Ids" listed were "USB\VID_0BDA&PID_8152" and "USB\VID_0BDA&PID_8152&REV_2000".

The HardwareId string ("VID_0BDA&PID_8152") implies that the driver was communicating with a Realtek 8152 USB Ethernet controller. Note: 0BDA is the vendor id for Realtek Semiconductor (see https://usb-ids.gowdy.us/read/UD/0bda) and the Turtle Wiki specs confirm the Turtle uses a "USB Ethernet Port - Realtek RTL8152".

We then used FTK Imager (v3.4.2.2) to grab the Registry hives so we can check them for artifacts.

Searching the SYSTEM hive for part of the "Device Instance Path" string (ie "VID_0BDA&PID_8152") yields an entry in SYSTEM\ControlSet001\Enum\USB\VID_0BDA&PID_8152

Potential First Turtle Insertion Time

The Last Written Time appears to match the first time the Turtle was inserted into the PC (21DEC2016 @ 21:15:54 UTC).

Another hit occurs in SYSTEM\ControlSet001\Enum\USB\VID_0BDA&PID_8152\00E04C36150A

Potential Most Recent Turtle Insertion Time


The Last Written Time appears to match the most recent time the Turtle was inserted (2JAN2017 @ 11:45:01 UTC).


The Turtle's 172.16.84.1 address appears in the Windows SYSTEM Registry hive as a "DhcpServer" value under SYSTEM\ControlSet001\services\Tcpip\Parameters\Interfaces\{59C1F0C4-66A7-42C8-B25E-6007F3C40925}.

Turtle's DHCP Address and Timestamp

Additionally under that same key, we can see a "LeaseObtainedTime" value which appears to be in seconds since Unix epoch (1JAN1970).
Using DCode to translate gives us:

Turtle DHCP LeaseObtainedTime Conversion


ie 2 JAN 2017 @ 11:24:37
This time occurs between the first time the Turtle was inserted (21DEC2016) and the most recent time the Turtle was inserted (2JAN2017 @ 11:45:01). This is plausible as the Turtle was plugged in multiple times during testing on the 2 JAN 2017. It is estimated that the Turtle was first plugged in on 2 JAN 2017 around the same time as the "LeaseObtainedTime". 

These timestamps potentially enable us to give a timeframe for Turtle use. We say potentially because it is possible that another device using the "Realtek USB FE Family Controller" driver may have also been used. However, the specific IP address (172.16.84.1) can help us point the flipper at a rogue Turtle.

The "Realtek USB FE Family Controller" string also appears in the "Description" value under the SOFTWARE hive:
SOFTWARE\Microsoft\Windows NT\CurrentVersion\NetworkCards\17

NetworkCards entry potentially pointing to Turtle

Note: The NetworkCards number entry will vary (probably will not be 17 in all cases)

There are probably more artifacts to be found but these Registry entries were the ones that were the most obvious to find. The Windows Event logs did not seem to log anything Turtle-y definitive.

However, based on the artifacts above, we can only say that a Turtle was probably plugged in. We don't have enough (yet?) to state which modules (if any) were run.

Final Thoughts

Anecdotally from the Hak5 Turtle Forums, capturing Windows credentials with the LAN Turtle seems to be hit and miss.
From our testing, the Turtle QuickCreds module worked for a Win7 laptop but failed to capture creds for a Win10 VM running on the same laptop. Once the Turtle was plugged in to the laptop, it captured the creds for the host Win7 OS but upon connecting the Turtle to the Win10 VM via the "Removable Devices" VMware 12 Player menu, the amber LED remains solidly lit and the Win10 creds were not captured.
Interestingly, not all of the Win7 Registry artifacts listed previously were observed in the Win10 VM's Registry:
Both SYSTEM\ControlSet001\Enum\USB\VID_0BDA&PID_8152 and SYSTEM\ControlSet001\Enum\USB\VID_0BDA&PID_8152\00E04C36150A were present in the Win10 SYSTEM registry.
However, no hits were observed for "172.16.84.1" in SYSTEM.
There were various hits for "Realtek USB FE Family Controller" in SYSTEM.
The "Realtek USB FE Family Controller" string also appears in the "Description" value under the Win10 SOFTWARE hive:
SOFTWARE\Microsoft\Windows NT\CurrentVersion\NetworkCards\5
The lack of Win10 Registry DHCP artifacts probably indicates that while the Realtek USB Ethernet driver was installed, the Turtle was unable to assign the 172.16.84.1 IP address within the WIN10 VM (possibly because the Win7 still has it reserved?).

Fortunately, Jackk has recorded a helpful YouTube video demonstrating the LAN Turtle running QuickCreds successfully against a Win10 laptop (not VM). So it is possible on Win10 ... Jackk also shows how to use the Turtle's sshfs module to copy off the cred files via a FileZilla client (instead of using pscp).

Any comments/suggestions are turtle-y welcome in the comments section below.