A password recovery program available from AccessData

Building a Secure Organization

John R. Mallery, in Computer and Information Security Handbook (Third Edition), 2013

Use Robust Passwords

With the increased processing power of our computers and password-cracking software such as the Passware products47 and AccessData's Password Recovery Toolkit,48 cracking passwords is fairly simple and straightforward. For this reason it is extremely important to create robust passwords. Complex passwords are hard for users to remember, though, so it is a challenge to create passwords that can be remembered without writing them down. One solution is to use the first letter of each word in a phrase, such as “I like to eat imported cheese from Holland.” This becomes IlteicfH, which is an eight-character password using upper- and lowercase letters. This can be made even more complex by substituting an exclamation point for the letter I and substituting the number 3 for the letter “e,” so that the password becomes !lt3icfH. This is a fairly robust password that can be remembered easily.

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URL: https://www.sciencedirect.com/science/article/pii/B9780128038437000028

Anti-forensics

John Sammons, in The Basics of Digital Forensics (Second Edition), 2015

Defragmentation as anti-forensic technique

Defragmentation, or defragging as it’s commonly called, is often done to improve computer performance. Defragging is the process of moving clusters as close together as possible to speed up the system. This procedure involves moving data from one location on the drive to another. Data can be overwritten in the process. These overwritten (destroyed) data may have had some evidentiary value.

The defragmentation process can occur in three ways—it can be user-scheduled, manually initiated by the user, or done automatically by the operating system (Casey, 2009).

There are a few different ways you can attempt to determine whether a drive has been recently defragmented. One way is to boot the drive image in Windows and look at the amount of file fragmentation. Drives in regular use normally show a significant amount of file fragmentation. Drives that show otherwise, without a plausible explanation, would be suspect.

Q & A with Nephi Allred, Cryptanalyst with AccessData, the Maker of Password Recovery Toolkit (PRTK)

By now it should be clear that encryption is a major concern to the digital forensics community. That means we must be prepared to deal with encrypted data. Decryption tools are one weapon we can bring to the fight. One of the premier decryption tools on the market is Password Recovery Toolkit (PRTK) from AccessData. PRTK is widely used worldwide by law enforcement, intelligence agencies, and private corporations such as large financial institutions. U.S. users include the FBI, CIA, and Secret Service, just to name a few. In this Q&A, we get a closer look inside PRTK and the encryption it aims to break.

[Q]

About how many passwords per second does PRTK guess on a “standard” machine?

[A]

We get this question a lot. It’s impossible to answer, as it stands because the question itself has an implicit assumption, which is wrong. Namely: All password schemes are not the same. It’s a bit like asking how fast animals can go. Which animal? Every program or application or other system that uses passwords does it differently. The way they do it makes all the difference in the world in how much computation is required to test a password.

For example, a “typical” machine might guess 2 million passwords per second trying to crack an Office 97 file, while the same machine might only guess 500 passwords per second in cracking an Office 2010 file.

And, of course, the answer also depends on what you mean by a “typical” machine (and that changes as time goes on, too).

[Q]

PRTK guesses passwords in a certain order to improve the speed and efficiency. Can you talk a little about how that works and why it’s important?

[A]

Not all passwords are created equal. In the space of all possible passwords, some are more likely to be used by humans than others. (For example, “Br1tn3y” is much more likely to be used than “H(i3}-aV.K = TyG7”). So, if you are trying to guess passwords, you will be faster and more successful on average if you guess the more probable passwords first.

Of course, which passwords are more probable is not always easy to determine, and certainly varies from person to person. PRTK defines a default ordering of passwords that we have tried to make as effective as possible, given what is known about how people tend to choose passwords. But an investigator often has specific knowledge about a suspect and can use that to make a password ordering more tailored to that individual. This is why PRTK gives its users a great deal of password space customization. For example, rather than going with the default, you can specify that a job first try all the passwords in a (possibly customized) dictionary, then all of those words in reverse order, then all of those words with “123,” “4eva,” or “asdf” appended. And lots more.

[Q]

I know that PRTK also relies on identified patterns of passwords (roots and appendages). What are those based on and how does that work?

[A]

Based on various password lists that we’ve obtained over the years (some from clients of ours, others freely available), we’ve tried to make password “rules” that generate passwords that people actually use in real life. At this point, this is still more an art than a science. That is, there is no deep statistical analysis going on (yet)—mostly we eyeball the lists and look for patterns. For example, a lot of passwords seem to end with 1. So one of our password rules is “Dictionary followed by common suffixes” and 1 is one of those common suffixes.

[Q]

Do you know just how effective PRTK is in breaking passwords?

[A]

Again, this varies widely over the kinds of files and suspects. I don’t have any numbers for you, unfortunately. You should probably talk to people who use PRTK (or DNA) on real cases.

It’s worth noting that not all attacks PRTK does are password-guessing attacks. Some crypto systems have flaws that allow their passwords to be recovered instantly, with no “guessing” involved. For example, PRTK can instantly recover the master password on the Whisper32 password manager. This was not uncommon in applications a decade ago, but these days, it’s becoming much more rare as software developers become more crypto-savvy.

[Q]

Is there anything that slows down the decryption process? Can you talk about that and why that is?

[A]

Yes, there is. These days, most developers of password using applications are aware of tools like PRTK, and they will use measures to slow down password-guessing attacks. As I explained in #1, the speed at which we can guess passwords all depends on how the application uses the password.

An application could deliberately choose a very slow password-to-key methodology. It might hash the password 10,000 times, for example, instead of just once, while transforming the password into a key. (This is a simplification, but you get the idea). This forces the password-guessing tool to also hash the password 10,000 times per password guessed, which leads to many fewer passwords per second.

[Q]

How is encryption changing? What do you see is the “next big thing” in cryptography? What challenges do you see ahead?

[A]

Cryptography is a big subject, and I’m hardly an expert in any of the cutting edges of new research. But in the arena of password-based encryption, things are changing.

It’s not exactly a new insight, but people are becoming more and more aware that passwords as a security device are often inadequate. What we’ll use instead of them (or, more likely, in addition to them) is not yet entirely clear, but encryption providers are trying new things.

For example, several applications, like TrueCrypt, allow users to enhance their password with “key files.” A key file can be any file, and it is used to scramble a password before use. This means that to run a successful password-guessing attack, PRTK needs to have any and all key files used. It may not be easy for the investigator to figure out what key files were used, if any.

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URL: https://www.sciencedirect.com/science/article/pii/B9780128016350000061

Forensics Team Requirements Members

Leighton R. JohnsonIII, in Computer Incident Response and Forensics Team Management, 2014

AccessData Certified Examiner

This is a certification offered industry-wide through AccessData, the developers of forensic software products, including Forensic Toolkit (FTK), to those qualified applicants completing the certification process. To learn more about the AccessData Certified Examiner (ACE) and AccessData, visit their web site at www.accessdata.com.

The ACE certification from AccessData Group, LLC validates an exam candidate’s proficiency with using AccessData’s FTK, Password Recovery Toolkit (PRTK), FTK Imager, and Registry Viewer products. FTK is one of the more recognized tools in computer forensics. AccessData recommends that anyone needing to demonstrate proficiency with FTK acquires the ACE certification.

The ACE exam is a 90-min, multiple choice exam that is free to take either online or at the conclusion of an AccessData training class. The exam contains both written and practical assignments based on a case that is created and processed from an image file provided to the exam candidate. ACE Credential Maintenance requires that a renewal exam be taken every 1 or 2 years.

There are free preparation videos and an exam study guide available on the AccessData web site. AccessData recommends that the certification be taken in conjunction with their AccessData Boot Camp and Windows Forensics courses, but it is not required. You can find out more about the ACE certification process at the AccessData web site.

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URL: https://www.sciencedirect.com/science/article/pii/B978159749996500011X

Forensic Analysis

Eoghan Casey, Curtis W. Rose, in Handbook of Digital Forensics and Investigation, 2010

Encryption and Steganography

Encryption can present a significant challenge for digital forensic practitioners, particularly full disk encryption (Casey & Stellatos, 2008). Even when full disk encryption is not used or can be circumvented, additional effort is required to salvage data from password protected or encrypted files (Casey, 2002). When dealing with individually protected files, it is sometimes possible to use a hexadecimal editor like WinHex to simply remove the password within a file. There are also specialized tools that can bypass or recover passwords of various files. Currently, the most powerful and versatile tools for salvaging password protected and encrypted data are PRTK and DNA from AccessData. The Password Recovery Toolkit can recover passwords from many file types and is useful for dealing with encrypted data. Also, it is possible for a DNA network to try every key in less time by combining the power of several computers. Distributed Network Attack (DNA) can brute-force 40-bit encryption of certain file types including Adobe Acrobat and Microsoft Word and Excel. Using a cluster of approximately 100 off-the-shelf desktop computers and the necessary software, it is possible to try every possible 40-bit key in five days. Rainbow tables can be used to accelerate the password guessing process. Some vendors also have hardware decryption platforms based on implementation of field programmable gate arrays that can increase the speed of brute force attacks.

When strong encryption is used such as BestCrypt, PGP, or Windows Encrypting File System, a brute-force approach to guessing the encryption key is generally infeasible. In such cases, it may be possible to locate unencrypted versions of data in unallocated space, swap files, and other areas of the system. For instance, printer spool files on Windows and UNIX systems can contain data from files that have been deleted or encrypted. Alternatively, it may be possible to obtain an alternate decryption key. For instance some encryption programs advise users to create a recovery disk in case they forget their password. When EFS is used, Windows automatically assigns an encryption recovery agent that can decrypt messages when the original encryption key is unavailable (Microsoft, 1999). In Windows 2000, the built-in administrator account is the default recovery agent (an organization can override the default by assigning a domainwide recovery agent provided the system is part of the organization's Windows 2000 domain).

Notably, prior to Windows XP, EFS private keys were weakly protected and it was possible to gain access to encrypted data by replacing the associated NT logon password with a known value using a tool like ntpasswd and logging into a bootable/virtualized clone of the system with the new password.

When investigating a child exploitation case, it is advisable to be on the lookout for other forms of data concealment such as steganography. Forensic analysts can make educated guesses to identify files containing hidden data—the presence of steganography software and uncharacteristically large files should motivate examiners to treat these as special files that require additional processing. In such cases, it may be possible to salvage the hidden data by opening the files using the steganography software and providing a password that was obtained during the investigation. More sophisticated techniques are available for detecting hidden data. Even if encryption or steganography cannot be bypassed, documenting which files are concealing data can help an investigator, attorney, or trier-of-fact determine the intent of the defendant.

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URL: https://www.sciencedirect.com/science/article/pii/B9780123742674000021

Microsoft SkyDrive Cloud Storage Forensic Analysis

Darren Quick, ... Kim-Kwang Raymond Choo, in Cloud Storage Forensics, 2014

Presentation

Analysis findings

In our case study, a variety of data remnants were located when a user used SkyDrive to store or access data. The focus (or scope) was to determine what data remnants were left to identify if SkyDrive had been used on a Windows 7 PC. Conducting a search for the term “skydrive” was shown to be inconclusive to demonstrate use, as it was shown that the term is present even when SkyDrive has not been accessed, as outlined in the analysis of the control Base-VMs. The SkyDrive username was able to be discerned from a variety of locations, such as cookie files, memory captures (searching for “&login=”), in pagefile.sys, from SQLite database files, and IEF output.

Surprisingly, the password for the SkyDrive account was able to be located unencrypted in the memory captures from the Upload-VMs. Passwords are commonly used in a variety of locations, and when conducting analysis to determine a password to view encrypted files, one practice is to build an index of data to use with password analysis tools such as AccessData Password Recovery Toolkit, Passware, or Elcomsoft password analysis tools. With the actual password in cleartext, this would vastly speed up the process of password discovery. Hence, memory capture and analysis should be a key consideration when determining the possible sources of data in step 3 of the framework (evidence source identification and preservation—see Figure 2.1) for indexing purposes. However, if the password is not located in memory or if memory capture is not possible, it is still possible to access a SkyDrive account using the forensic image of a hard drive where the SkyDrive client software has been used to access an account. This can be achieved by running the hard drive forensic image as a VM. When the VM starts up, it will automatically synchronize with the SkyDrive cloud service and update files in the local SkyDrive folder. Appropriate legal authority would be required to ensure that the account and information can be accessed and used for analysis.

Analysis to determine the method of access, whether the client software was used, a browser used to upload, access, or download, or a combination of both, is possible. When the client software was downloaded, there was a SkyDriveSetup.exe file downloaded to the local hard drive. Hash values for the client software can be calculated and searched across forensic image files, memory, and network captures. In addition, registry entries may indicate the use of the setup software or the client software, as will link files. Prefetch files were observed for the client software and also include the number of times run and associated dates and times. The file “CollectLogFiles.bat” appears to have a consistent hash value across SkyDrive client software releases and the hash value for this file can be used to conduct searches. Also, searching for the term “enabledogfood” may determine if the client software has been installed on a PC. A folder was observed with the client software version as the folder name in the AppData\local\ folder.

When a browser was used to access SkyDrive, there were many references in the output from IEF, but when access was undertaken with no downloading there were no references to the filenames in the IEF output. When bulk files were downloaded using the web account from the root folder, an uncompressed ZIP file was observed with the name “skydrive” and the date.

Filenames, dates, and times were observed in the “SyncDiagnostics.log” file and the “.dat” file with the OwnerID as the filename. Filenames were also observed in the Registry “RecentDocs” keys, $MFT entries, and Prefetch files such as DLLHost.pf, Wordpad.pf, and Notepad.pf. Link files and the IEF output also listed the filenames. The contents of the files were also recovered from temporary Internet files, thumbcache, memory captures, pagefile.sys, system volume restore points, and unallocated space. Eraser and CCleaner were not effective in removing all data remnants, and information was able to be determined from these VMs relating to the SkyDrive accounts, filenames, dates and times, and file contents (Table 3.14).

Table 3.14. Summary of Analysis Findings

Control (Base-VM) Data Artifacts Found
Username, Password, Software, URL, Enron Sample filenames or files Nil
KWS terms Nil
Nil
Matches to “skydrive” relating to icon files (Internet Explorer Base-VM)
Client Software (Upload-VM) Data Artifacts Found
Username Cookie files “[email protected]”, $MFT, and $LogFile. Memory capture files “&login=”
OwnerID OwnerID found in SkyDrive software installation .dat and .ini files
Password Located in RAM—search for &login= and &passwd=
Software SkyDriveSetup.exe file located when downloaded.
SkyDrive Software installation under User\AppData\Local\Microsoft
SyncDiagnostics.log file includes OwnerID and file information, dates and times
URL When software downloaded, URLs included https://skydrive.live.com and http://www.skydrive.com
Enron sample filenames Multiple locations, including Prefetch, Link files, $MFT, Registry. Filenames in Network PCAP files.
Enron sample files Located in Sync folder under User\SkyDrive.
KWS terms “EnableDogFood” found in SkyDrive client software files
Browser Access (Access-VM) Data Artifacts Found
Username FF and GC History; “formhistory.sqlite” and “Web Data.” Memory capture files “&login=”
OwnerID Observed in URL https://skydrive.live.com/?cid=XXXXXXXXXXXXXXXX# (FF and GC) +RAM
Password Nil
Software Nil
URL Multiple locations; cookie, history, icons, pagefile.sys, and unallocated
Enron sample filenames Sufficient to identify files accessed with references to the filenames in Registry and Browsing History
Enron sample files Full text in RAM and System Volume Information
KWS terms Multiple matches to KWS terms
Browser Download (Download-VM) Data Artifacts Found
Username FF and GC History; “formhistory.sqlite” and “Web Data.” Memory capture files “&login=”
OwnerID Observed in URL https://skydrive.live.com/?cid=XXXXXXXXXXXXXXXX# (FF and GC) +RAM
Password Nil
Software Nil
URL Multiple locations; cookie, history, icons, pagefile.sys, and unallocated
Enron sample filenames Sufficient to identify files accessed with references in $MFT, Link, Registry, and Prefetch files
Enron sample files Via uncompressed zip; “skydrive-YYYY-MM-DD.zip” or folder name “Documents.zip”
KWS terms Full text in RAM and System Volume Information
Eraser (Eraser-VM) Data Artifacts Found
Username FF and GC History; “formhistory.sqlite” and “Web Data” Memory capture files “&login=”
OwnerID Observed in URL https://skydrive.live.com/?cid=XXXXXXXXXXXXXXXX# (FF and GC)+RAM
Password Nil
Software Nil
URL Multiple locations; cookie, history, icons, pagefile.sys, and unallocated
Enron sample filenames Sufficient to identify files accessed with references to the filenames in $MFT, Link, and Prefetch files
Enron sample files Full text in RAM and System Volume Information
KWS terms Multiple matches to KWS terms
CCleaner (CCleaner-VM) Data Artifacts Found
Username FF and GC History; “formhistory.sqlite” and “Web Data” Memory capture files “&login=”
OwnerID Observed in URL https://skydrive.live.com/?cid=XXXXXXXXXXXXXXXX# (FF and GC) +RAM
Password Nil
Software Nil
URL Multiple locations; cookie, history, icons, pagefile.sys, and unallocated
Enron sample filenames Sufficient to identify files accessed with references to the filenames in $MFT, Link, and Prefetch files
Enron sample files Full text in RAM and System Volume Information
KWS terms Multiple matches to KWS terms
DBAN (DBAN-VM) Data Artifacts Found
Username
Password
Software
URL All data erased, no information located
Enron sample filenames
Enron sample files
KWS terms

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URL: https://www.sciencedirect.com/science/article/pii/B978012419970500003X

What is AccessData used for?

With our digital forensics expertise, AccessData gives you the tools to help you analyze computers, mobile devices and network communications. When you know more, you can do more.

What is AccessData Forensic Toolkit?

Product: Forensic Toolkit (FTK) AccessData solutions enable mobile data analysis alongside computer data, helping law enforcement complete investigations faster.

Which hashing algorithm is provided by WinHex?

WinHex can calculate several kinds of hash values of any file, disk, partition, or any part of a disk, even 256-bit digests, for the most suspicious ones. In particular, the MD5 message digest algorithm (128-bit) is incorporated, which produces commonly used unique numeric identifiers (hash values).

What is data recovery in cyber forensic?

Forensic data recovery is the extraction of data from damaged, corrupted or lost evidence sources i.e. damaged or formatted hard drives, removable media. The data are recovered in a manner that will make the resulting evidence admissible in the law court.