usnparser 2.0.0

Description

The NTFS USN journal is a volume-specific file which essentially logs changes to files and file metadata. As such, it can be a treasure trove of information during DFIR investigations. The change journal is located at $Extend$UsnJrnl:$J and can be easily extracted using Encase or FTK.

usn.py is a script written in Python which parses the journal - and has what I consider to be a couple of unique features.

Default Output

With no command-line options set, usn.py will produce USN journal records in the format below:

dev@computer:$ python usn.py -f usnjournal
2016-01-26 18:56:20.046268 | test.vbs | ARCHIVE  | DATA_OVERWRITE DATA_EXTEND

Command-Line Options

optional arguments:
  -h, --help            show this help message and exit
  -c, --csv             Return USN records in comma-separated format
  -f FILE, --file FILE  Parse the given USN journal file
  -g GREP, --grep GREP  'grep' for a specific file name in a USN record, and
                        only provide records which match
  -q, --quick           Parse a large journal file quickly
  -v, --verbose         Return all USN properties for each record (JSON)

–quick

Warning: This logic does make some assumptions abou the data in question and could use more testing. If you are experiencing issues using this functionality just switch back to using usn.py without the –quick flag. I am adjusting its logic every chance I can to make it more helpful/accurate.

Speaking of the USN Journal being a Sparse File - IMO, a major pain point when parsing a USN journal is its size on disk. These files can easily scale over 20GB, comprised of a large amount of leading x00 values. This means the script needs to ‘hunt’ for and find the first USN record before it can begin producing results.

Using an interpreted language such as Perl or Python to do this initial hunting can be extremely time consuming if an Analyst is working with a larger journal file. Applying the –quick / -q flag enables the script to perform this search much more quickly: by jumping ahead a gigabyte at a time looking for data. Jumping ahead one gigabyte at a time requires the journal in question to be at least one gigabyte in size. If it isn’t, the script will simply produce an error and exit:

dev@computer$ python usn.py -f usnjournal --quick
[ - ] This USN journal is not large enough for the --quick functionality
[ - ] Exitting...

Below is an example of the time it takes to find valid data in a large USN journal - 39GB in size. This example is not using the –quick functionality and takes over six minutes to even begin parsing data:

PS Dev:\Desktop> Measure-Command {C:\Python27\python.exe usn.py -f usnjournal}
Hours             : 0
Minutes           : 6
Seconds           : 3
Milliseconds      : 766
Ticks             : 3637662181
TotalDays         : 0.00421025715393519
TotalHours        : 0.101046171694444
TotalMinutes      : 6.06277030166667
TotalSeconds      : 363.7662181
TotalMilliseconds : 363766.2181

Now the same USN journal file, but with the –quick flag invoked. The time it takes to find data is cut down to just under three seconds:

PS Dev:\Desktop> Measure-Command {C:\Python27\python.exe usn.py -f usnjournal --quick}
Hours             : 0
Minutes           : 0
Seconds           : 2
Milliseconds      : 822
Ticks             : 28224455
TotalDays         : 3.2667193287037E-05
TotalHours        : 0.000784012638888889
TotalMinutes      : 0.0470407583333333
TotalSeconds      : 2.8224455
TotalMilliseconds : 2822.4455

–csv

Using the CSV flag will, as expected, provide results in CSV format. Using the –csv / -c option provides the same USN fields as default output:

• Timestamp

• Filename

• File attributes

• Reason

At this point the –csv flag cannot be combined with any other flag other than –quick. That should change soon, as I want –csv capability for any data returned. An example of what this looks like is below:

dev@computer:~$python usn.py -f usnjournal --csv
timestamp,filename,fileattr,reason
2015-10-09 21:37:58.836242,A75BFDE52F3DD8E6.dat,ARCHIVE NOT_CONTENT_INDEXED,DATA_EXTEND FILE_CREATE

–verbose

Returns all USN record properties with each entry, with the –verbose / -v flag. The result is a JSON object.

dev@computer:~$python usn.py -f usnjournal --verbose
{
    "recordlen": 88,
    "majversion": 2,
    "minversion": 0,
    "fileref": 281474976767661,
    "pfilerefef": 844424930233360,
    "usn": 419506120,
    "timestamp": "2015-10-09 21:38:52.160484",
    "reason": "CLOSE FILE_DELETE",
    "sourceinfo": 0,
    "sid": 0,
    "fileattr": "ARCHIVE",
    "filenamelen": 24,
    "filenameoffset": 60,
    "filename": "wmiutils.dll"
}

–grep / -g

Sometimes during a more targeted investigation, an Analyst is simply looking for additional supporting evidence to confirm what is believed or pile on to what is already known - and does not want to eyeball the entire journal for this evidence. By using the ‘–grep / -g’ command-line flag, an Analyst can return only USN records which match a given ‘filename’ attribute:

dev@computer:~$ python usn.py -f usnjournal --grep jernuhl.txt
{
    "recordlen": 88,
    "majversion": 2,
    "minversion": 0,
    "fileref": 5910974510924810,
    "pfilerefef": 1688849860348307,
    "usn": 461014088,
    "timestamp": "2015-10-28 01:59:56.233596",
    "reason": "FILE_CREATE",
    "sourceinfo": 0,
    "sid": 0,
    "fileattr": "ARCHIVE",
    "filenamelen": 22,
    "filenameoffset": 60,
    "filename": "jernuhl.txt"
}

Installation

Using setup.py:

python setup.py install

Using pip:

pip install usnparser

Python Requirements

• argparse

• collections

• datetime

• json

• os

• struct

• sys