Table 1, below, outlines the number of individual users and business entities for each of the password managers we examine in this paper.
Table 1. With the proliferation of online services, password use has gone from about 25 passwords per user in  to in and is projected to grow to in . This, combined with a userbase of 60 million across password managers we examine in this paper, creates a target rich environment in which adversaries can carefully craft methods to extract an increasingly growing and valuable trove of secrets and credentials. An example in which a password manager appears to have been specifically targeted is an attack that led to the loss of units of Ethereum ETH , a cryptocurrency valued at the time of 1.
The attack was carried out against a cryptocurrency trading assistant platform, Taylor . Taylor issued a statement that indicated a device which was using 1Password for secrets management was compromised .
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It remains unclear, whether the attacker found a security issue in 1Password itself or simply discovered the master password in some other way, or whether the compromise had nothing to do with password managers. Given the combination of an increasing number of credentials held in password managers, the value of those secrets and the emerging threats specifically targeting password managers it is important for us to examine the increased risk a user or organization faces in terms of secrets exposure when using a password manager.
Our approach for this was to survey popular password managers to determine common defenses they employ against secrets exfiltration. We incorporate the best security features of each into a hypothetical, best possible password manager, that provides a minimum set of guarantees outlined in the next section. Then we compare the password managers studied against those security guarantees. All password managers studied work in the same basic way. Users enter or generate passwords in the software and add any pertinent metadata e. This information is encrypted and then decrypted only when it is needed for display, for passing to a browser add-on that fills the password into a website, or for copying to the clipboard for use.
Throughout this paper we will refer to password managers in three states of existence: not running, unlocked and running , and locked and running; this state assumes the password manager was previously unlocked. We assume that the user does not have additional layers of encryption such as full disk encryption or per process virtualization. We define the three states below:. The user may have displayed, copied to clipboard, or otherwise accessed some of the passwords in the password manager.
Knowing usability constraints that affect password managers, we concede that:. Since a locked password manager still exists as a process in virtual memory, this requires additional guarantees:. In addition to these explicit security guarantees, we expect password managers to incorporate additional hardening measures where possible, and to have these hardening measures enabled by default. For example, password managers should attempt to block software keystroke loggers from accessing the master password as it is typed, attempt to limit the exposure of unencrypted passwords left on the clipboard, and take reasonable steps to detect and block modification or patching of the password manager and its supporting libraries that might expose passwords.
In this paper we will examine the inner workings as they relate to secrets retrieval and storage of 1Password, Dashlane, KeePass and LastPass on the Windows 10 platform Version Build We examine susceptibility of a password manager to secrets exfiltration via examination of the password database on disk; memory forensics; and finally, keylogging, clipboard monitoring, and binary modification.
Each password manager is examined in its default configuration after install with no advanced configuration steps performed. The focus on our evaluation of password managers is limited to the Windows platform. Our findings can be extrapolated to password manager implementations in other operating systems to guide research to areas of interest that are discussed in this paper. We first consider the security of password managers when they are not running. We focus on the attack vector of compromising passwords from disk.
Here, we examine which algorithm each password manager uses to transform the master password into an encryption key, and whether the algorithm and number of iterations is severely lacking in its ability to resist contemporary cracking attacks. We concluded that the password managers were secure against compromising passwords from disk as the software is not running, and that brute forcing the encrypted password entries on disk would be computationally prohibitive, although not impossible if given enough computing resources.
Given this, we moved on to the attack surface of passwords stored in memory while the password managers are running. Table 2. Each password managers default key expansion algorithm and number of iterations. We expected and found that all password managers reviewed sufficiently protect the master password and individual passwords while they are not running. The remaining bulk of our assessment of password managers in the running state was focused on the effectiveness of the locked state and whether the unlocked state left the minimum possible amount of sensitive information in memory.
The following sections outline violations of our proposed security guarantees of password managers in a running locked and unlocked state. We assessed the security of 1Password4 while running and found reasonable protections against exposure of individual passwords in the unlocked state; unfortunately, this was overshadowed by its handling of the master password and several broken implementation details when transitioning from the unlocked to the locked state.
On the positive side, we found that as a user accesses different entries in 1Password4, the software is careful to clear the previous unencrypted password from memory before loading another. This means that only one unencrypted password can be in memory at once. On the negative side, the master password remains in memory when unlocked albeit in obfuscated form and the software fails to scrub the obfuscated password memory region sufficiently when transitioning from the unlocked to the locked state. We also found a bug where, under certain user actions, the master password can be left in memory in cleartext even while locked.
It is possible to recover and deobfuscate the master password from 1Password4 since it is not scrubbed from memory after placing the password manager in a locked state. Given a scenario where a user has unlocked 1Password4 and then placed it back into a locked state, 1Password4 will prompt for the master password again as shown in Figure 1below. Figure 2. Encoded master password present in memory while 1Password4 is in a locked state.
We can use this information to intercept normal workflows in which 1Password4 calls RtlRunEncodeUnicodeString and RtlRunDecodeUnicodeString to obfuscate the master password to instead reveal the already present, but encoded master password into cleartext Figure 3.
Figure 3. Only entries that are actively being interacted with exist in memory as plaintext. Figure 4is an example of an entry in memory as its being interacted with. Once 1Password4 is locked, the memory region is deallocated. Note that the deallocated region is not first scrubbed, however the Windows memory manager will zero out any freed pages of memory before making them available for re-allocation by the Windows memory manager. After assessing the legacy 1Password4, we moved on to 1Password7, the current release.
Surprisingly, we found that it is less secure in the running state compared to 1Password4. Compounding this, we found that 1Password7 scrubs neither the individual passwords, the master password, nor the secret key an extra field introduced in 1Password6 that combines with the master password to derive the encryption key from memory when transitioning from unlocked to locked.
Interestingly, this is not the case. This technology protects secrets inside secure memory enclaves so that other processes and even higher privileged components such as the kernel cannot access them. Were SGX to be implemented correctly, 1Password7 would have been the most secure password manager in our research by far.
Unfortunately, SGX was only supported as a beta feature in 1Password6 and early versions of 1Password7, and was dropped for later versions. This was only evident from gathering the details about it on a 1Password support forum . As stated before, all secrets are exposed by 1Password7 when in an unlocked and locked state. The proof of concept applications ran in the existing user context which was an ordinary non-administrative user. Show below is 1Password7 in a locked state, Figure 5 having previously been unlocked but then again locked awaiting password entry to unlock it.
Figure 7 shows the extraction of the secret key that is needed along with the master password to unlock an encrypted database, and Figure 8shows the automated extraction of secret entries. During our evaluation of 1Password7, we encountered a system stop error kernel mode exception on our Windows 10 workstation, from an unrelated hardware issue, that created a full memory debug dump to disk. While examining this memory dump file, we came across our secrets that 1Password7 held cleartext, in memory, in a locked state when the stop error occurred Figure 9. Figure 9. Windows 10 crash dump file contained secrets 1Password7 held in memory in a locked state.
Moreover, some companies have a policy to image workstations that have had malware encounters as part of the incident response procedure.
A user that happened to be running 1Password7 while this procedure was initiated should assume that all secrets have been compromis. In our Dashlane evaluation, we noted workflows that indicate focus was placed on concealing secrets in memory to reduce their likelihood of extraction.
Similar to 1Password4, Dashlane exposes only the active entry a user is interacting with. So, at most, the last active entry is exposed in memory while Dashlane is in an unlocked and locked state. Password entries in Dashlane are stored in an XML object. Upon interacting with any entry this XML object becomes exposed in cleartext and can be easily extracted in both locked and unlocked states. Figure 10, below, is an example of a portion of this XML data structure. Figure Excerpt of a fully decrypted Dashlane XML password database in an unlocked and locked state.
Knowing that this data structure exists in a locked state, we then created a proof of concept application to extract it from a locked instance of Dashlane.
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Figure 11, below, is a locked instance of Dashlane prompting for the master password to unlock it. In this locked state, we then run our proof of concept to extract all stored secrets Figure However, even though we are able to extract secrets from a locked state of Dashlane, the memory region they reside in has been dereferenced and freed.
So, over time portions of the XML data structure may be overwritten. Throughout our examination, we noticed that secrets may reside for a few minutes. In some instances, we have observed them still resident in memory more than 24 hours. Dashlane is also unique compared to the other password managers in our examination in that it does not allow you to exit the process via GUI components, such as clicking the close program [x] in the upper right or pressing the ALT-F4 key combination.
Doing so causes Dashlane to minimize into the task tray, leaving it susceptible to secrets extraction for extended periods of time. Unlike the other password managers, KeePass is an open source project. Similar to 1Password4, KeePass decrypts entries as they are interacted with, however, they all remain in memory since they are not individually scrubbed after each interaction. The master password is scrubbed from memory and not recoverable.
However, while KeePass attempts to keep secrets secure by scrubbing them from memory, there are obviously errors in these workflows as we have discovered that while even in a locked state, we were able to extract entries that had been interacted with. KeePass claims to use several defenses in depth memory protection mechanisms as stated in an excerpt from their site below Figure Entries that have been interacted with remain exposed in memory even after KeePass has been placed into a locked state.
Figure 14, below, is an example of a locked instance of KeePass prompting for the master password before it can be unlocked. Secrets are scattered in memory with no references. However, performing a simple strings dump from the process memory of KeePass reveals a list of entries that have been interacted with Figure Using the above information, we can then search for a username to an entry and locate its corresponding password field entry, in the below image Figure16 we locate the bitcoin private key which was stored in the password field.
The above methodology can be used to extract any entries that have been interacted with before placing KeePass into a locked state. Similar to 1Password4, LastPass obfuscates the master password as its being typed into the unlock field. Master password overwritten once the master password has been used in a PBKDF2 key expansion routine. Once LastPass enters an unlocked state, database entries are decrypted into memory only upon user interaction. However, these entries persist in memory even after LastPass has been placed back into a locked state. During a workflow to derive the decryption key, the master password is leaked into a string buffer in memory and never scrubbed, even when LastPass is placed into a locked state.