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=========== STATUS This project was my passion and my vehicle for exploring digital forensics for many years as well as a means for giving back to a community that gave me so much. Unfortunately, I am no doing forensics on Windows filesystems and am not contributing to this project anymore. If someone else wishes to adopt it, please let me know. -David (02/02/2020) =========== Analyze MFT =========== analyzeMFT.py is designed to fully parse the MFT file from an NTFS filesystem and present the results as accurately as possible in multiple formats. Installation =========== You should now be able to install analyzeMFT with pip: pip install analyzeMFT Alternatively: git clone https://github.com/dkovar/analyzeMFT.git cd analyzeMFT python setup.py install (or, just run it from that directory) Usage =========== Usage: analyzeMFT.py [options] Options: -h, --help show this help message and exit -v, --version report version and exit File input options: -f FILE, --file=FILE read MFT from FILE File output options: -o FILE, --output=FILE write results to FILE -c FILE, --csvtimefile=FILE write CSV format timeline file -b FILE, --bodyfile=FILE write MAC information to bodyfile Options specific to body files: --bodystd Use STD_INFO timestamps for body file rather than FN timestamps --bodyfull Use full path name + filename rather than just filename Other options: -a, --anomaly turn on anomaly detection -l, --localtz report times using local timezone -e, --excel print date/time in Excel friendly format -d, --debug turn on debugging output -s, --saveinmemory Save a copy of the decoded MFT in memory. Do not use for very large MFTs -p, --progress Show systematic progress reports. -w, --windows-path Use windows path separator when constructing the filepath instead of linux Output ========= analyzeMFT can produce output in CSV or bodyfile format. CSV output --------- The output is currently written in CSV format. Due to the fact that Excel automatically determines the type of data in a column, it is recommended that you write the output to a file without the .csv extension, open it in Excel, and set all the columns to "Text" rather than "General" when the import wizard starts. Failure to do so will result in Excel formatting the columns in a way that misrepresents the data. I could pad the data in such a way that forces Excel to set the column type correctly but this might break other tools. GUI: You can turn off all the GUI dependencies by setting the noGUI flag to 'True'. This is for installations that don't want to install the tk/tcl libraries. Update History ============= [See CHANGES.txt] Version 2.0.4:Minor tweaks to support external programs Version 2.0.3:Restructured to support PyPi (pip) Version 2.0.2:De-OOP'd MFT record parsing to reduce memory consumption Version 2.0.1:Added L2T CSV and body file support back in, fixed some minor bugs along the way Made full file path calculation more efficient Version 2.0.0 Restructured layout to turn it into a module. Made it more OOP. Improved error handling and corrupt record detection ------ Version 1 history follows ------ Version 1.0: Initial release Version 1.1: Split parent folder reference and sequence into two fields. I'm still trying to figure out the significance of the parent folder sequence number, but I'm convinced that what some documentation refers to as the parent folder record number is really two values - the parent folder record number and the parent folder sequence number. Version 1.2: Fixed problem with non-printable characters in filenames. Any Unicode character is legal in a filename, including newlines. This presented some problems in my output. Characters that do not render well are now converted to hex and a note is added to the Notes column indicating this. (I've learned a lot about Unicode since I first wrote this.) Added "compile time" flag to turn off the inclusion of any GUI related modules and libraries for systems missing tk/tcl support. (Set noGUI to True in the code) Version 1.3: Added new column to hold log entries relating to each record. For example, a note stating that some characters in the filename were converted to hex as they could not be printed. Version 1.4: Credit: Spencer Lynch. I was misusing the flags field in the MFT header. The first bit is Active/Inactive. The second bit is File/Folder. Version 1.5: Fixed date/time reporting. I wasn't reporting useconds at all. Added anomaly detection. Adds two columns: std-fn-shift: If Y, entry's FN create time is after the STD create time usec-zero: If Y, entry's STD create time's usec value is zero Version 1.6: Various bug fixes Version 1.7: Bodyfile support, with thanks to Dave Hull Version 1.8: Added support for full path extraction, written by Kristinn Gudjonsson Version 1.9: Added support for csv timeline output Version 1.10: Just for Tom Version 1.11: Fixed TSK bodyfile output Version 1.12: Fix orphan file detection issue that caused recursion error (4/18/2013) Version 1.13: Changed from walking all sequence numbers to pulling sequence number from MFT. Previous approach did not handle gaps well Version 1.14: Made -o output optional if -b is specified. (Either/or) Version 1.15: Added file size (real, not allocated) to bodyfile. Added bodyfile option to include fullpath + filename rather than just filename Added bodyfile option to use STD_INFO timestamps rather than FN timestamps Version 2 history is in CHANGES.txt Inspiration =========== My original inspiration was a combination of MFT Ripper (thus the current output format) and the SANS 508.1 study guide. I couldn't bear to read about NTFS structures again, particularly since the information didn't "stick". I also wanted to learn Python so I figured that using it to tear apart the MFT file was a reasonably sized project. Many of the variable names are taken directly from Brian Carrier's The Sleuth Kit. His code, plus his book "File System Forensic Analysis", was very helpful in my efforts to write this code. The output format is almost identical to Mark Menz's MFT Ripper. His tool really inspired me to learn more about the structure of the MFT and to learn what additional information I could glean from the data. I also am getting much more interested in timeline analysis and figured that really understanding the the MFT and having a tool that could parse it might serve as a good foundation for further research in that area. Future work =========== 1) Figure out how to write the CSV file in a manner that forces Excel to interpret the date/time fields as text. If you add the .csv extension Excel will open the file without invoking the import wizard and the date fields are treated as "General" and the date is chopped leaving just the time. 2) Add version switch 3) Add "mftr" switch - produce MFT Ripper compatible output 4) Add "extract" switch - extract or work on live MFT file 5) Finish parsing all possible attributes 6) Look into doing more timeline analysis with the information 7) Improve the documentation so I can use the structures as a reference and reuse the code more effectively 8) Clean up the code and, in particular, follow standard naming conventions 9) There are two MFT entry flags that appear that I can't determine the significance of. These appear in the output as Unknown1 and Unknown2 10) Parse filename based on 'nspace' value in FN structure 11) Test it and ensure that it works on all major Windows OS versions 12) Output HTML as well as CSV 13) If you specify a bad input filename and a good output filename, you get an error about the output filename. Useful Documentation ==================== 1) http://dubeyko.com/development/FileSystems/NTFS/ntfsdoc.pdf