How to Install and Uninstall analyzeMFT Package on openSUSE Leap
Last updated: November 23,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "analyzeMFT" package
Please follow the guidance below to install analyzeMFT on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
analyzeMFT
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2. Uninstall "analyzeMFT" package
Here is a brief guide to show you how to uninstall analyzeMFT on openSUSE Leap:
$
sudo zypper remove
analyzeMFT
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3. Information about the analyzeMFT package on openSUSE Leap
Information for package analyzeMFT:
-----------------------------------
Repository : Main Repository
Name : analyzeMFT
Version : 2.0.4-bp153.1.12
Arch : noarch
Vendor : openSUSE
Installed Size : 78,5 KiB
Installed : No
Status : not installed
Source package : analyzeMFT-2.0.4-bp153.1.12.src
Summary : A Python tool to deconstruct the Windows NTFS $MFT file
Description :
analyzeMFT.py is designed to fully parse the MFT file from an NTFS filesystem and present the results as accurately as possible in a format that allows further analysis with other tools. At present, it parses the attributes from a $MFT file to produce the following output:
Record Number
Good - if the entry is valid
Active - if the entry is active
Record type - the type of record
Record Sequence - the sequence number for the record
Parent Folder Record Number
Parent Folder Sequence Number
For the standard information attribute:
Creation date
Modification date
Access date
Entry date
For up to four file name records:
File name
Creation date
Modification date
Access date
Entry date
Object ID
Birth Volume ID
Birth Object ID
Birth Domain ID
And flags to show if each of the following attributes is present:
Standard Information, Attribute List, Filename, Object ID, Volume Name, Volume Info, Data, Index Root, Index Allocation, Bitmap, Reparse Point, EA Information, EA, Property Set, Logged Utility Stream
Notes/Log - Field used to log any significant events or observations relating to this record
std-fn-shift - Populated if anomaly detection is turned on. Y/N. Y indicates that the FN create date is later than the STD create date.
usec-zero - Populated if anomaly detection is turned on. Y/N. Y indicates that the STD create date's microsecond value is zero.
For each entry in the MFT a record is written to an output file in CSV format.
Major contributions from Matt Sabourin.
-----------------------------------
Repository : Main Repository
Name : analyzeMFT
Version : 2.0.4-bp153.1.12
Arch : noarch
Vendor : openSUSE
Installed Size : 78,5 KiB
Installed : No
Status : not installed
Source package : analyzeMFT-2.0.4-bp153.1.12.src
Summary : A Python tool to deconstruct the Windows NTFS $MFT file
Description :
analyzeMFT.py is designed to fully parse the MFT file from an NTFS filesystem and present the results as accurately as possible in a format that allows further analysis with other tools. At present, it parses the attributes from a $MFT file to produce the following output:
Record Number
Good - if the entry is valid
Active - if the entry is active
Record type - the type of record
Record Sequence - the sequence number for the record
Parent Folder Record Number
Parent Folder Sequence Number
For the standard information attribute:
Creation date
Modification date
Access date
Entry date
For up to four file name records:
File name
Creation date
Modification date
Access date
Entry date
Object ID
Birth Volume ID
Birth Object ID
Birth Domain ID
And flags to show if each of the following attributes is present:
Standard Information, Attribute List, Filename, Object ID, Volume Name, Volume Info, Data, Index Root, Index Allocation, Bitmap, Reparse Point, EA Information, EA, Property Set, Logged Utility Stream
Notes/Log - Field used to log any significant events or observations relating to this record
std-fn-shift - Populated if anomaly detection is turned on. Y/N. Y indicates that the FN create date is later than the STD create date.
usec-zero - Populated if anomaly detection is turned on. Y/N. Y indicates that the STD create date's microsecond value is zero.
For each entry in the MFT a record is written to an output file in CSV format.
Major contributions from Matt Sabourin.