Digging Up the Past: Windows Registry Forensics Revisited
FireEye consultants frequently utilize Windows registry data when
performing forensic analysis of computer networks as part of incident
response and compromise assessment missions. This can be useful to
discover malicious activity and to determine what data may have been
stolen from a network. Many different types of data are present in the
registry that can provide evidence of program execution, application
settings, malware persistence, and other valuable artifacts.
Performing forensic analysis of past attacks can be particularly
challenging. Advanced persistent threat actors will frequently utilize
anti-forensic techniques to hide their tracks and make the jobs of
incident responders more difficult. To provide our consultants with
the best possible tools we revisited our existing registry forensic
techniques and identified new ways to recover historical and deleted
registry data. Our analysis focused on the following known sources of
historical registry data:
- Registry transaction logs
- Transactional registry transaction logs (.TxR)
- Deleted entries in registry hives
- Backup system hives
- Hives backed up with System Restore
Windows Registry Format
The Windows registry is stored in a collection of hive files. Hives
are binary files containing a simple filesystem with a set of cells
used to store keys, values, data, and related metadata. Registry hives
are read and written in 4KB pages (also called bins).
For a detailed description of the Windows registry hive format, see
paper and this href="https://github.com/msuhanov/regf/blob/master/Windows%20registry%20file%20format%20specification.md">GitHub page.
Registry Transaction Logs (.LOG)
To maximize registry reliability, Windows can use transaction logs
when performing writes to registry files. The logs act as journals
that store data being written to the registry before it is written to
hive files. Transaction logs are used when registry hives cannot
directly be written due to locking or corruption.
Transaction logs are written to files in the same directory as their
corresponding registry hives. They use the same filename as the hive
with a .LOG extension. Windows may use
multiple logs in which case .LOG1 and class="code">.LOG2 extensions will be used.
For more details about the transaction log format, see this href="https://github.com/msuhanov/regf/blob/master/Windows%20registry%20file%20format%20specification.md#format-of-transaction-log-files">GitHub page.
Registry transaction logs were first introduced in Windows 2000. In
the original transaction log format data is always written at the
start of the transaction log. A bitmap is used to indicate what pages
are present in the log, and pages follow in order. Because the start
of the file is frequently overwritten, it is very difficult to recover
old data from these logs. Since different amounts of data will be
written to the transaction log on each use, it is possible for old
pages to remain in the file across multiple uses. However, the
location of each page will have to be inferred by searching for
similar pages in the current hive, and the probability of consistent
data recovery is very small.
A new registry transaction log format was introduced with Windows
8.1. Although the new logs are used in the same fashion, they have a
different format. The new logs work like a ring buffer where the
oldest data in the log is overwritten by new data. Each entry in the
new log format includes a sequence number as well as registry offset
making it easy to determine the order of writes and where the pages
were written. Because of the changed log format, data is overwritten
much less frequently, and old transactions can often be recovered from
these log files.
The amount of data that can be recovered depends on registry
activity. A sampling of transaction logs from real world systems
showed a range of recoverable data from a few days to a few weeks.
Real world recoverability can vary considerably. Registry-heavy
operations, such as Windows Update, can significantly reduce the
Although the new log format contains more recoverable information,
turning a set of registry pages into useful data is quite tricky.
First, it requires keeping track of all pages in the registry and
determining what might have changed in a particular write. It also
requires determining if that change resulted in something that is not
present in later revisions of the hive to assess whether or not it
contains unique data.
Our current approach for processing registry transaction files uses
the following algorithm:
- Sort all writes by sequence number descending so that we
process the most recent writes first.
- Perform allocated and
unallocated cell parsing to find allocated and deleted entries.
- Compare entries against the original hive. Any entries that are
not present are marked as deleted and logged.
Transaction Log Example
In this example we create a registry value under the Run key that
starts malware.exe when the user logs in to the system.
Figure 1: A malicious actor creates a
value in the Run key
At a later point in time the malware is removed from the system. The
registry value is overwritten before being deleted.
Figure 2: The malicious value is
overwritten and deleted
Although the deleted value still exists in the hive, existing
forensic tools will not be able to recover the original data because
it was overwritten.
Figure 3: The overwritten value is
present in the registry hive
However, in this case the data is still present in the transaction
log and can be recovered.
Figure 4: The transaction log contains
the original value
Transactional Registry Transaction Logs (.TxR)
In addition to the transaction log journal there are also logs used
by the transactional registry subsystem. Applications can utilize the
transactional registry to perform compound registry operations
atomically. This is most commonly used by application installers as it
simplifies failed operation rollback.
Transactional registry logs use the Common Log File Sytstem (CLFS)
format. The logs are stored to files of the form class="code"><hive><GUID>.TxR.<number>.regtrans-ms.
For user hives these files are stored in the same directory as the
hive and are cleared on user logout. However, for system hives logs
are stored in class="code">%SystemRoot%\System32\config\TxR, and the logs are
not automatically cleared. As a result, it is typically possible to
recover historical data from system transactional logs.
The format of transactional logs is not well understood or
documented. Microsoft has provided a href="https://docs.microsoft.com/en-us/windows-hardware/drivers/kernel/introduction-to-the-common-log-file-system">general
overview of CLFS logs and API.
With some experimentation we were able to determine the basic record
format. We can identify records for registry key creation and deletion
as well as registry value writes and deletes. The relevant key path,
value name, data type, and data are present within log entries. See
the appendix for transaction log record format details.
Although most data present in registry transaction logs is not
particularly valuable for intrusion investigations, there are some
cases where the data can prove useful. In particular, we found that
scheduled task creation and deletion use registry transactions. By
parsing registry transaction logs we were able to find evidence of
attacker created scheduled tasks on live systems. This data was not
available in any other location.
The task scheduler has been observed using transactional registry
operations on Windows Vista through Windows 8.1; the task scheduler on
Windows 10 does not exhibit this behavior. It is not known why Windows
10 behaves differently.
Transactional Registry Example
In this example we create a scheduled task. The scheduled task
periodically runs malware.
Figure 5: Creating a scheduled task to
Information about the scheduled task is stored to the registry.
Figure 6: A registry entry created by the
Because the scheduled task was written to the registry using
transacted registry operations, a copy of the data is available in the
transactional registry transaction log. The data can remain in the log
well after the scheduled task has been removed from the system.
Figure 7: The malicious scheduled task in
the TxR log
Deleted Entry Recovery
In addition to transaction logs, we also examined methods for the
recovery of deleted entries from registry hive files. We started with
an in-depth analysis of some common techniques used by forensic tools
today in the hopes of identifying a more accurate approach.
Deleted entry recovery requires parsing registry cells in hive
files. This is relatively straightforward. FireEye has a number of
tools that can read raw registry hive files and parse relevant keys,
values, and data from cells. Recovering deleted data is more complex
because some information is lost when elements are deleted. A more
sophisticated approach is required to deal with the resulting ambiguity.
When parsing cells there is only one common field: the cell size.
Some cell types contain magic number identifiers, which can help
determine their type. However, other cell types, such as data and
value lists, do not have identifiers; their types must be inferred by
following references from other cells. Additionally, the size of data
within a cell can differ from the cell size. Depending on the cell
type it may be necessary to leverage information from referencing
cells to determine the data size.
When a registry element is deleted its cells are marked as
unallocated. Because the cells are not immediately overwritten,
deleted elements can often be recovered from registry hives. However,
unallocated cells may be coalesced with adjacent unallocated cells to
maximize traversal efficiency. This makes deleted cell recovery more
complex because cell sizes may be modified. As a result, original cell
boundaries are not well defined and must be determined implicitly by
examining cell contents.
Existing Approaches for Recovering Deleted Entries
A review of public literature and source code revealed existing
methods for recovery of deleted elements from registry hive files.
Variations of the following algorithm were commonly found:
- Search through all unallocated cells looking for deleted key
- Find referenced deleted values from deleted keys.
- Search through all remaining unallocated cells looking for
unreferenced deleted value cells.
- Find referenced data
cells from all deleted values.
We implemented a similar algorithm to experiment with its efficacy.
Although this simple algorithm was able to recover many deleted
registry elements, it had a number of significant shortcomings. One
major issue was the inability to validate any references from deleted
cells. Because referenced cells may have already been overwritten or
reused multiple times, our program frequently made mistakes in
identifying values and data resulting in false positives and invalid output.
We also compared program output to popular registry forensic tools.
Although our program produced much of the same output, it was evident
that existing registry forensic tools were able to recover more data.
In particular, existing tools were able to recover deleted elements
from slack space of allocated cells that had not yet been overwritten.
Additionally, we found that orphaned allocated cells are also
considered deleted. It is not known how unreferenced allocated cells
could exist in a registry hive as all related cells should be
unallocated simultaneously on deletion. It is possible that certain
types of failures could result in deleted cells not becoming
Through experimentation we discovered that existing registry tools
were able to perform better validation resulting in fewer false
positives. However, we also identified many cases where existing tools
made incorrect deleted value associations and output invalid data.
This likely occurs when cells are reused multiple times resulting in
references that could appear valid if not carefully scrutinized.
A New Approach for Recovering Deleted Entries
Given the potential for improving our algorithm, we undertook a
major redesign to recover deleted registry elements with maximum
accuracy and efficiency. After many rounds of experimentation and
refinement we ended up with a new algorithm that can accurately
recover deleted registry elements while maximizing performance. This
was achieved by discovering and keeping track of all cells in registry
hives to perform better validation, by processing cell slack space,
and by discovering orphaned keys and values. Testing results closely
matched existing registry forensics tools but with better validation
and fewer false positives.
The following is a summary of the improved algorithm:
- Perform basic parsing for all allocated and unallocated cells.
Determine cell type and data size where possible.
all allocated cells and do the following:
- For allocated keys
find referenced value lists, class names, and security records.
Populate data size of referenced cells. Validate key ancestors
to determine if the key has been orphaned.
allocated values find referenced data and populate data
- Define all allocated cell slack space
as unallocated cells.
- Enumerate allocated keys and attempt
to find deleted values present in the values list. Also attempt to
find old deleted value references in the value list slack
- Enumerate unallocated cells and attempt to find
deleted key cells.
- Enumerate unallocated keys and attempt
to define referenced class names, security records, and values.
- Enumerate unallocated cells and attempt to find unreferenced
deleted value cells.
- Enumerate unallocated values and
attempt to find referenced data cells.
Deleted Recovery Example
The following example demonstrates how our deleted entry recovery
algorithm can perform more accurate data recovery and avoid false
positives. Figure 8 shows an example of a data recovery error by a
popular registry forensics tool:
Figure 8: Incorrectly recovered registry data
Note that the ProviderName recovered from this key was jumbled
because it referred to a location that had been overwritten. When our
deleted registry recovery tool is run over the same hive, it
recognizes that the data has been overwritten and does not output
garbled text. The data_present field in
Figure 9 with a value of 0 indicates that the deleted data could not
be recovered from the hive.
Value: ProviderName Type: REG_SZ (value_offset=0x137FE40)
Figure 9: Properly validated registry data
Windows includes a simple mechanism to backup system registry hives
periodically. The hives are backed up with a scheduled task called
RegIdleBackup, which is scheduled to run every 10 days by default.
Backed up hives are stored to class="code">%SystemRoot%\System32\config\RegBack. Only the
most recent backup is stored in this location. This can be useful for
investigating recent activity on a system.
The RegIdleBackup feature was first included with Windows Vista. It
is present in all versions of Windows since then, but it does not run
by default on Windows 10 systems, and even when it is manually run no
backups are created. It is not known why RegIdleBackup was removed
from Windows 10.
In addition to RegBack, registry data is backed up with System
Restore. By default, System Restore snapshots are created whenever
software is installed or uninstalled, including Windows Updates. As a
result, System Restore snapshots are usually created on at least a
monthly basis if not more frequently. Although some advanced
persistent threat groups have been known to manipulate System Restore
snapshots, evidence of historical attacker activity can usually be
found if a snapshot was taken at a time when the attacker was active.
System Restore snapshots contain all registry hives including system
and user hives.
Wikipedia has some good information about href="https://en.wikipedia.org/wiki/System_Restore">System Restore.
Processing hives in System Restore snapshots can be challenging as
there may be many snapshots present on a system resulting in a large
amount of data to be processed, and often there will only be minor
changes in hives between snapshots. One strategy to handle the large
number of snapshots is to build a structure representing the cells of
the registry hive, then repeat the process for each snapshot. Anything
not in the previous structure can be considered deleted and logged appropriately.
The registry can provide a wealth of data for a forensic
investigator. With numerous sources of deleted and historical data, a
more complete picture of attacker activity can be assembled during an
investigation. As attackers continue to gain sophistication and
improve their tradecraft, investigators will have to adapt to discover
and defend against them.
Appendix - Transactional Registry Transaction Log (.TxR) Record Format
Registry transaction logs contain records with the following format:
Magic number (0x280000)
| width="67" valign="top">|
Record type (1)
Registry operation type
| width="67" valign="top">|
Key path size
Key path size repeated
| width="67" valign="top">|
The magic number is always 0x280000.
The record size includes
The record type is always 1.
Operation type 1 is key creation.
Operation type 2 is key
Operation types 3-8 are value write or delete. It is
not known what the different types signify.
The key path size is at offset 40 and repeated at offset 42. This is
present for all registry operation types.
For registry key write and delete operations, the key path is at
For registry value write and delete operations, the following data
Value name size
Value name size repeated
| width="63" valign="top">|
The data for value records starts at offset 88. It contains the key
path followed by the value name optionally followed by data. If data
size is nonzero, the record is a value write operation; otherwise it
is a value delete operation.
Source: Digging Up the Past: Windows Registry Forensics Revisited