Touch Screen Lexicon Forensics (TextHarvester/WaitList.dat)
By Barnaby Skeggs
The text trainer stores Application Lexicon Blobs, and User Lexicon blobs. Both blobs can be used by the Handwriting Recogniser, and both blobs are updated when new data is received by the IPS, thereby continually improving handwriting recognition accuracy.
For more information on this process, please read:
https://msdn.microsoft.com/en-us/library/bb265252.aspx
The following files exist within the same directory as WaitList.dat:
%User%\AppData\Local\Microsoft\InputPersonalization\TextHarvester\TextHarvester.dat
%User%\AppData\Local\Microsoft\InputPersonalization\TrainedDataStore\en-AU\*
The 'DocID' (Offset 0x1C detailed in Data Structure below) appears to match entries within WaitList to values within TextHarvester.dat. This link will be investigated and detailed in a future blog post.
Whilst further research is definitely required it is possible that the 'Microsoft Windows Search Indexer' collects and stores user data in WaitList, following which TextHarvester acts as the 'Text Trainer', tuning the user data into TrainedDataStores (User Lexicon Blobs) for use by the 'Handwriting Recogniser'.
If you know more about these files please contact me at b2dfir@REMOVE.gmail.com.
Microsoft Outlook Email:
*
For more
information on MailItem objects, see:
https://msdn.microsoft.com/en-us/library/office/ff861332.aspx
---------------------------------------------------------------------------------------------------------------------
Preamble
Since the release of
Windows 8, and the ‘Metro’ interface, touch screen input has been implemented
in a rapidly rising number of Windows devices including Microsoft Surface
Pro/Book, 2-in-1s, convertible laptops and tablets. Microsoft has catered for
this trend, implementing conversion between touch/pen handwriting to computer
text in software such as OneNote. In this paper I will detail my research into the
forensic artefact ‘Waitlist.dat’, which I believe to be associated with this
functionality.
I identified the
‘WaitList.dat’ artefact while investigating a Windows 8.1 PC for the presence
of a known email. I was provided with a copy of this email, and part of the
investigation involved identifying whether or not this email ever existed on
the custodian’s computer. After processing the .PST and .OST mailbox archives
on the PC, I did not identify the existence of the email. I then processed
shadow copies, carved and processed for various mailbox stores and email files,
and still did not identify the email. As a final attempt, I ran a string search
for the email subject line across the whole forensic image. I received 1 hit
within ‘WaitList.dat’. Investigation
of this 140mb file identified metadata, and full body text of over 36’000
emails and documents, spanning back 3 years.
Acknowledgements
Shaun Bettridge – Peer review, contribution
to data structure analysis and being a sounding board for ideas throughout this
analysis.
Carl - Peer review.
Carl - Peer review.
WaitList.dat
‘WaitList.dat’ (WaitList)
is a data file which has been found to contain stripped text from email,
contact and document files. The population of data within WaitList is
associated with the ‘Microsoft Windows Search Indexer’ process. This process
locks the WaitList file on a live system.
WaitList is located in the following directory on Windows 8.1
and 10 systems (may exist on other OS versions, however I do not have systems
to test this):
C:\Users\%User%\AppData\Local\Microsoft\InputPersonalization\TextHarvester\WaitList.dat
I have only identified WaitList on PCs which have
utilized touch screen handwriting recognition features. My own touch screen laptop
did not contain this file, as I had not used the feature. In order to test its
creation, I setup and began using the handwriting recognition in OneNote, and WaitList
was soon automatically created. The following morning full text extracts of all
emails I had received overnight were populated within WaitList.
Registry comparison before and after my test showed the
following registry key modifications:
Key: HKEY_CURRENT_USER\SOFTWARE\Microsoft\InputPersonalization
Lexicon definition: the
vocabulary of a person, language, or branch of knowledge
The "App Lexicon Timestamp" key is a Windows 64 bit FILETIME (Big Endian) timestamp which matches (within ~10 seconds) the installation time of the COM Class Object 'UserLexiconManager'. This is not the date when this key was created, or the date from when WaitList population commenced. On my PC, this date was prior to my purchase of the laptop, likely associated with the initial Windows 10 installation.
Alternatively, these registry key values can be created by enabling 'Personalised Handwriting Recognition' for a supported language in the Control Panel.
Control Panel\Clock, Language and Region\Language\Language options
The "App Lexicon Timestamp" key is a Windows 64 bit FILETIME (Big Endian) timestamp which matches (within ~10 seconds) the installation time of the COM Class Object 'UserLexiconManager'. This is not the date when this key was created, or the date from when WaitList population commenced. On my PC, this date was prior to my purchase of the laptop, likely associated with the initial Windows 10 installation.
Alternatively, these registry key values can be created by enabling 'Personalised Handwriting Recognition' for a supported language in the Control Panel.
Control Panel\Clock, Language and Region\Language\Language options
Theory and Further Research
As of Windows Vista, Custom Dictionaries have been used to improve handwriting recognition results. This has worked by the Input Personalisation System (IPS) collecting user data, which a 'Text Trainer' 'tunes' and stores in 'lexicon blobs'.The text trainer stores Application Lexicon Blobs, and User Lexicon blobs. Both blobs can be used by the Handwriting Recogniser, and both blobs are updated when new data is received by the IPS, thereby continually improving handwriting recognition accuracy.
For more information on this process, please read:
https://msdn.microsoft.com/en-us/library/bb265252.aspx
Representation of the relationship between Ink Applications and the IPS
The following files exist within the same directory as WaitList.dat:
%User%\AppData\Local\Microsoft\InputPersonalization\TextHarvester\TextHarvester.dat
%User%\AppData\Local\Microsoft\InputPersonalization\TrainedDataStore\en-AU\*
The 'DocID' (Offset 0x1C detailed in Data Structure below) appears to match entries within WaitList to values within TextHarvester.dat. This link will be investigated and detailed in a future blog post.
Whilst further research is definitely required it is possible that the 'Microsoft Windows Search Indexer' collects and stores user data in WaitList, following which TextHarvester acts as the 'Text Trainer', tuning the user data into TrainedDataStores (User Lexicon Blobs) for use by the 'Handwriting Recogniser'.
If you know more about these files please contact me at b2dfir@REMOVE.gmail.com.
File Contents
The following data has been identified within WaitList.dat records.Microsoft Outlook Email:
·
Date/Time
·
Email subject
·
Sent flag
·
Type (Email/Document/Contact)
·
Recipients (Does not distinguish between ‘To’,
‘CC’ and ‘BCC’)
Note: Does not store ‘From’ value, however this can often be identified in email signatures)
Note: Does not store ‘From’ value, however this can often be identified in email signatures)
·
Meeting Location (only when email is a calendar
invite)
·
Body of file
Contact:
·
Address
·
City
·
State
·
Country
·
Full Name
·
Title
·
Contact Details (email/phone/url)
Note: Contacts added
from Skype/Lync may be recorded as a ‘sent’ email item, due to the way Outlook
imports/stores the contact.
Documents (.pdf, .xlsx, .txt, .doc and .docx files have been
tested):
·
Date/Time
·
DocumentID (use to compare document indexes over
time) – format unknown
·
Body of file
·
Company
It is likely that other values are stored in additional data
types, however this is the extent of data I have identified in my testing procedures.
Forensic Application
WaitList provides an additional source of evidence for
email and document discovery. In addition to the existence and content of a
document, WaitList will store multiple indexes for a single document over
time. This provides a forensic examiner the ability to view historical
iterations of a file, even when shadow copy is not enabled, or when the file
has been deleted/wiped from the hard drive.
The population of data within WaitList.dat is associated
with the ‘Microsoft Windows Search Indexer’ process. This process locks the
WaitList file on a live system. Existence of an index record within WaitList only indicates
the existence of the file on the computer. User interaction with the file can
only be inferred when the metadata stored within the record (e.g. ‘Sent flag’,
‘Recipient’) indicates a user action.
An email or document can be recorded in WaitList without
being read or opened by the user.
Limitations of the Microsoft Windows Search Indexer apply to
all records within WaitList. For example, files within an archive (.zip,
.rar etc.) or encrypted documents cannot be indexed with default 'Microsoft Windows Search
Indexer' settings, and therefore will not be stored within WaitList. Scanned
(non-text searchable) PDFs may appear as records, however the body text will be
empty.
For more information on the 'Windows Search Indexer' visit:
https://msdn.microsoft.com/en-us/library/ee805985(v=vs.85).aspx
https://msdn.microsoft.com/en-us/library/ee805985(v=vs.85).aspx
‘Microsoft Windows
Search Indexer’ will index emails and their attachments at a similar time. As a
result, these files will occur within close proximity of each other when they
are written to ‘WaitList.dat’. Whilst there does not appear to be a direct
parent to child relationship value, the attachment files will contain matching
‘Recipient’ values to their parent email. ‘Date/Time’ and ‘Recipient’ values
can be used to associate emails with their likely attachments.
Parsing WaitList.dat
WLrip.py (WLrip) is a python program I have written to
parse the contents of WaitList.dat, based on my understanding of the data
structure specified below. WLrip will extract the metadata and body text of
each record to a new .txt file, and produce a metadata report in .csv format.
Running WLrip with the ‘-x’ option will produce a .xlsx
report with hyperlinks to each .txt file created. This is the recommended method
to run WLrip, however it requires the Python ‘XLSXWriter’ module (https://github.com/jmcnamara/XlsxWriter).
Recommended execution of WLrip.py is as follows:
Wlrip.py -c -x -f <filename> -o <output
directory>
Arguments:
Argument
|
Description
|
-c
|
Removes various null characters, in an attempt to clean up the text
output.
|
-x
|
Produces a .xlsx report, as well as the default .csv report.
|
-k
|
Kills the ‘Microsoft Windows Search Indexer’ process, which will lock
the WaitList.dat file on a live system. Requires administrator privileges.
|
-f
|
Specify WaitList.dat file location for processing.
|
-o
|
Specifies an output directory. If not included, the report will be
generated within a new folder in the current directory.
|
I have done my best to write this program in a way that
allows it to capture new values (which I have not yet encountered) in the
‘other’ field. Values captured in the ‘other’ field will be appended with a
[type], to indicate the field value stored in the data structure. Please send
unknown values to me and I can implement them in future releases.
https://github.com/B2dfir/wlrip
I have also compiled WLrip into a portable Windows executable using pyinstaller.
https://github.com/B2dfir/wlripEXE
https://github.com/B2dfir/wlrip
I have also compiled WLrip into a portable Windows executable using pyinstaller.
https://github.com/B2dfir/wlripEXE
Data Structure Analysis
I have performed analysis on the data structure of
WaitList in order to understand how text and metadata are stored within
each record. All values are in little endian.
Data Structure (Hex)
Data Structure (Detail)
Offset
|
Hex
|
Decimal
|
Length
|
Field Name and
Description
|
0x00
|
6400000000
|
100
|
5 bytes
|
WaitList.dat File
Signature
|
0x05
|
03 0b 00 00
|
2819
|
4 bytes
|
Index Record Length
(bytes)
|
0x09
|
03 0b 00 00
|
2819
|
4 bytes
|
Index Record Length
(bytes) - repeated
|
0x0D
|
40 59 7B 44
58 F8 D1 01
|
-
|
8 bytes
|
Win 64bit FILETIME –
Indexed file’s last modification time/date
|
0x15
|
0F 00 00 00
|
15
|
4 bytes
|
Record ID (incremental
integer)
Note: Not included in WLrip
output
|
0x19
|
00
|
0
|
1 byte
|
Sent Flag
00 = sent email
01 = everything else
Note: Local files, and
email attachments will not contain the MailItem.Sent property*, and will
default to 00.
|
0x1A
|
00
|
0
|
1 byte
|
Unknown – always 00 in
currently tested files. Possibly a part of 'Sent Flag' (if 'Sent Flag' is a 2 byte int)
Note: Included in report for as Unkn for
community examination.
|
0x1B
|
01
|
1
|
1 byte
|
Type
00 = Not Email
01 = Email
|
0x1C
|
00 00 00 00
00 00 00 00
|
0
|
8 bytes
|
DocID – format unknown
Filter on this value
to view multiple indexes of a document over time.
Known information:
- Value for emails is
always 0s
- All documents
contain a value here
- Not a timestamp I
could identify
- Is not similar
between documents with similar timestamps
- Is the same for
duplicate documents
- Is the same for
multiple index records pertaining to the same document (e.g. when more text
has been saved to a report)
|
0x24
|
00
|
0
|
1 byte
|
More Metadata Flag
00 = More metadata
stored in this record (e.g. Blue data / Orange data structures)
01 = No more
metadata stored in this record prior to the body text.
Note: Not included in WLrip
output.
|
0x25
|
07 00 00 00
|
7
|
4 bytes
|
Index Record Metadata
Type Flag
04 00 00 00 = Recipient
Email Address
06 00 00 00 = Subject
07 00 00 00 =
Recipient Name
10 00 00 00 = Full
Name (contact)
11 00 00 00 = Title
(contact)
12 00 00 00 = Last
Name
21 00 00 00 = State
0B 00 00 00 = Address
(contact)
0C 00 00 00 = City
(contact)
0D 00 00 00 = Country
(contact)
0E 00 00 00 = Contact
details (contact)
0F 00 00 00 = First
Name (contact)
13 00 00 00 = Middle
Name (contact)
1B 00 00 00 = Location
(meetings)
|
0x29
|
00 00 00 00
|
0
|
4 bytes
|
Grammar Proofing Type
Note: See the
following registry key for available proofing types:
HKEY_CURRENT_USER\SOFTWARE\Microsoft\Shared Tools\Proofing
Tools\Grammar\MSGrammar
Note: Not included in
WLrip output.
|
0x2D
|
0c 00 00 00
|
12
|
4 bytes
|
Metadata Length
(characters)
Multiply integer value
by 2 for byte length
|
0x31
|
-
|
-
|
24 bytes
|
Metadata Text
(Recipient name in this example)
|
0x49
|
00
|
0
|
1 byte
|
Another Metadata Value
Flag
00 = Get another value
01 = No more values
|
0x4A
|
04 00 00 00
|
4
|
4 bytes
|
Same as blue offset
0x25
|
0x4E
|
00 00 00 00
|
0
|
4 bytes
|
Same as blue offset
0x29
|
0x52
|
13 00 00 00
|
19
|
4 bytes
|
Same as blue offset
0x2D
|
0x56
|
-
|
-
|
38 bytes
|
Metadata Text
(Recipient email address in this example)
|
0x7C
|
01
|
1
|
1 byte
|
Same as blue offset
0x49
|
0x7D
|
00 00 00 00
|
0
|
4 bytes
|
Current Body Text
Offset
Increases with each
length of indexed body text
|
0x81
|
05 00 00 00
|
5
|
4 bytes
|
Body Type Flag
05 00 00 00 = Email
Body
17 00 00 00 = Contact
1d 00 00 00 = Document
Body
|
0x85
|
09 0C 00 00
|
3081
|
4 bytes
|
Grammar Proofing Type
Refer to
‘HKCU\SOFTWARE\Microsoft\Shared Tools\Proofing Tools\Grammar’ for types
available on your system.
Note: Not included in WLrip
output.
|
0x89
|
81 02 00 00
|
641
|
4 bytes
|
Length of First
Section of Body
Multiply integer value
by 2 for byte length.
|
0x8D
|
-
|
-
|
1282 bytes
|
First Length of Body
Text
|
0x58F
|
01
|
1
|
1 byte
|
More Body Flag
01 = there is another
section of body
00 = body is complete
|
0x590
|
80 02 00 00
|
640
|
4 bytes
|
Same as red offset
0x7D
|
0x594
|
05 00 00 00
|
5
|
4 bytes
|
Same as red offset
0x81
|
0x598
|
09 04 00 00
|
1033
|
4 bytes
|
Same as red offset
0x85
|
0x59C
|
1C 00 00 00
|
28
|
4 bytes
|
Same as red offset
0x89
|
0x5A0
|
-
|
-
|
56 bytes
|
Second Length of Body
Text
|
0xAC9
|
0
|
0
|
1 byte
|
Same as red offset
0x58F
|
0xACA
|
06 00 00 00
|
4
|
4 bytes
|
Same as blue offset
0x25
|
0xACE
|
09 04 00 00
|
1033
|
4 bytes
|
Same as blue offset
0x29
|
0xAD2
|
1B 00 00 00
|
27
|
4 bytes
|
Same as blue offset
0x2D
|
0xAD6
|
-
|
-
|
54 bytes
|
Metadata Text (Email
subject in this example)
|
0xB0C
|
00
|
0
|
1 byte
|
Same as blue offset
0x49
Doesn’t necessarily
terminate on a 1 at the end of the record. WLrip has record length checks to
mitigate parsing errors.
|
https://msdn.microsoft.com/en-us/library/office/ff861332.aspx
Conclusion
WaitList is an additional source of email, contact and document evidence to add to our arsenal of forensic examination and e-discovery tools. Should you have any questions, recommendations or corrections for any of the detail in this blog, please post in the comments section below.---------------------------------------------------------------------------------------------------------------------
Disclaimer: The
information detailed within this report is based on my limited testing and
analysis of the ‘WaitList.dat’ file. I do not currently claim to have a complete
understanding of the structure or function of this file. Confirmation and testing of my
findings by the broader forensic community is required before this information
should be relied upon.
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It will be interesting to know your expert opinion about the “Touch Screen Lexicon Forensics” and the interesting analysis of TextHarvester/WaitList.dat. Approaching your findings of these data files helps portraying how touch input information can be utilised for investigative purposes in digital forensics. It’s mind boggling how every touch and scroll can capture traces that professionals can interpret. I was wondering if you have found any other pattern, which was quite unimaginable while navigating through the forensic analysis? Thanks for sharing the information – it is important and such a field is always changing but it is still so interesting.
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