As phones become faster and smarter, they play increasingly important roles in our lives, functioning as our extended memory, our connection to the world at large, and often the primary interface for communication with friends, family, and wider communities. It is only natural that as part of this evolution, we’ve come to entrust our phones with our most private information, and in many ways treat them as extensions of our digital and physical identities.
This trust is paramount to the Android Security team. The team focuses on ensuring that Android devices respect the privacy and sensitivity of user data. A fundamental aspect of this work centers around the lockscreen, which acts as the proverbial front door to our devices. After all, the lockscreen ensures that only the intended user(s) of a device can access their private data.
This blog post outlines recent improvements around how users interact with the lockscreen on Android devices and more generally with authentication. In particular, we focus on two categories of authentication that present both immense potential as well as potentially immense risk if not designed well: biometrics and environmental modalities.
The tiered authentication model
Before getting into the details of lockscreen and authentication improvements, we first want to establish some context to help relate these improvements to each other. A good way to envision these changes is to fit them into the framework of the tiered authentication model, a conceptual classification of all the different authentication modalities on Android, how they relate to each other, and how they are constrained based on this classification.
The model itself is fairly simple, classifying authentication modalities into three buckets of decreasing levels of security and commensurately increasing constraints. The primary tier is the least constrained in the sense that users only need to re-enter a primary modality under certain situations (for example, after each boot or every 72 hours) in order to use its capability. The secondary and tertiary tiers are more constrained because they cannot be set up and used without having a primary modality enrolled first and they have more constraints further restricting their capabilities.
Primary Tier - Knowledge Factor: The first tier consists of modalities that rely on knowledge factors, or something the user knows, for example, a PIN, pattern, or password. Good high-entropy knowledge factors, such as complex passwords that are hard to guess, offer the highest potential guarantee of identity.
Knowledge factors are especially useful on Android becauses devices offer hardware backed brute-force protection with exponential-backoff, meaning Android devices prevent attackers from repeatedly guessing a PIN, pattern, or password by having hardware backed timeouts after every 5 incorrect attempts. Knowledge factors also confer additional benefits to all users that use them, such as File Based Encryption (FBE) and encrypted device backup.
Secondary Tier - Biometrics: The second tier consists primarily of biometrics, or something the user is. Face or fingerprint based authentications are examples of secondary authentication modalities. Biometrics offer a more convenient but potentially less secure way of confirming your identity with a device.
We will delve into Android biometrics in the next section.
The Tertiary Tier - Environmental: The last tier includes modalities that rely on something the user has. This could either be a physical token, such as with Smart Lock’s Trusted Devices where a phone can be unlocked when paired with a safelisted bluetooth device. Or it could be something inherent to the physical environment around the device, such as with Smart Lock’s Trusted Places where a phone can be unlocked when it is taken to a safelisted location.
Improvements to tertiary authentication
While both Trusted Places and Trusted Devices (and tertiary modalities in general) offer convenient ways to get access to the contents of your device, the fundamental issue they share is that they are ultimately a poor proxy for user identity. For example, an attacker could unlock a misplaced phone that uses Trusted Place simply by driving it past the user's home, or with moderate amount of effort, spoofing a GPS signal using off-the-shelf Software Defined Radios and some mild scripting. Similarly with Trusted Device, access to a safelisted bluetooth device also gives access to all data on the user’s phone.
Because of this, a major improvement has been made to the environmental tier in Android 10. The Tertiary tier was switched from an active unlock mechanism into an extending unlock mechanism instead. In this new mode, a tertiary tier modality can no longer unlock a locked device. Instead, if the device is first unlocked using either a primary or secondary modality, it can continue to keep it in the unlocked state for a maximum of four hours.
A closer look at Android biometrics
Biometric implementations come with a wide variety of security characteristics, so we rely on the following two key factors to determine the security of a particular implementation:
Architectural security: The resilience of a biometric pipeline against kernel or platform compromise. A pipeline is considered secure if kernel and platform compromises don’t grant the ability to either read raw biometric data, or inject synthetic data into the pipeline to influence an authentication decision.
Spoofability: Is measured using the Spoof Acceptance Rate (SAR). SAR is a metric first introduced in Android P, and is intended to measure how resilient a biometric is against a dedicated attacker. Read more about SAR and its measurement in Measuring Biometric Unlock Security.
We use these two factors to classify biometrics into one of three different classes in decreasing order of security:
Class 3 (formerly Strong)
Class 2 (formerly Weak)
Class 1 (formerly Convenience)
Each class comes with an associated set of constraints that aim to balance their ease of use with the level of security they offer.
These constraints reflect the length of time before a biometric falls back to primary authentication, and the allowed application integration. For example, a Class 3 biometric enjoys the longest timeouts and offers all integration options for apps, while a Class 1 biometric has the shortest timeouts and no options for app integration. You can see a summary of the details in the table below, or the full details in the Android Android Compatibility Definition Document (CDD).
1 App integration means exposing an API to apps (e.g., via integration with BiometricPrompt/BiometricManager, androidx.biometric, or FIDO2 APIs)
2 Keystore integration means integrating Keystore, e.g., to release app auth-bound keys
Benefits and caveats
Biometrics provide convenience to users while maintaining a high level of security. Because users need to set up a primary authentication modality in order to use biometrics, it helps boost the lockscreen adoption (we see an average of 20% higher lockscreen adoption on devices that offer biometrics versus those that do not). This allows more users to benefit from the security features that the lockscreen provides: gates unauthorized access to sensitive user data and also confers other advantages of a primary authentication modality to these users, such as encrypted backups. Finally, biometrics also help reduce shoulder surfing attacks in which an attacker tries to reproduce a PIN, pattern, or password after observing a user entering the credential.
However, it is important that users understand the trade-offs involved with the use of biometrics. Primary among these is that no biometric system is foolproof. This is true not just on Android, but across all operating systems, form-factors, and technologies. For example, a face biometric implementation might be fooled by family members who resemble the user or a 3D mask of the user. A fingerprint biometric implementation could potentially be bypassed by a spoof made from latent fingerprints of the user. Although anti-spoofing or Presentation Attack Detection (PAD) technologies have been actively developed to mitigate such spoofing attacks, they are mitigations, not preventions.
One effort that Android has made to mitigate the potential risk of using biometrics is the lockdown mode introduced in Android P. Android users can use this feature to temporarily disable biometrics, together with Smart Lock (for example, Trusted Places and Trusted Devices) as well as notifications on the lock screen, when they feel the need to do so.
To use the lockdown mode, users first need to set up a primary authentication modality and then enable it in settings. The exact setting where the lockdown mode can be enabled varies by device models, and on a Google Pixel 4 device it is under Settings > Display > Lock screen > Show lockdown option. Once enabled, users can trigger the lockdown mode by holding the power button and then clicking the Lockdown icon on the power menu. A device in lockdown mode will return to the non-lockdown state after a primary authentication modality (such as a PIN, pattern, or password) is used to unlock the device.
BiometricPrompt - New APIs
In order for developers to benefit from the security guarantee provided by Android biometrics and to easily integrate biometric authentication into their apps to better protect sensitive user data, we introduced the BiometricPrompt APIs in Android P.
There are several benefits of using the BiometricPrompt APIs. Most importantly, these APIs allow app developers to target biometrics in a modality-agnostic way across different Android devices (that is, BiometricPrompt can be used as a single integration point for various biometric modalities supported on devices), while controlling the security guarantees that the authentication needs to provide (such as requiring Class 3 or Class 2 biometrics, with device credential as a fallback). In this way, it helps protect app data with a second layer of defenses (in addition to the lockscreen) and in turn respects the sensitivity of user data. Furthermore, BiometricPrompt provides a persistent UI with customization options for certain information (for example, title and description), offering a consistent user experience across biometric modalities and across Android devices.
As shown in the following architecture diagram, apps can integrate with biometrics on Android devices through either the framework API or the support library (that is, androidx.biometric for backward compatibility). One thing to note is that FingerprintManager is deprecated because developers are encouraged to migrate to BiometricPrompt for modality-agnostic authentications.
Improvements to BiometricPrompt
Android 10 introduced the BiometricManager class that developers can use to query the availability of biometric authentication and included fingerprint and face authentication integration for BiometricPrompt.
In Android 11, we introduce new features such as the BiometricManager.Authenticators interface which allows developers to specify the authentication types accepted by their apps, as well as additional support for auth-per-use keys within the BiometricPrompt class.
Google’s Advanced Protection Program helps secure people at higher risk of targeted online attacks, like journalists, political organizations, and activists, with a set of constantly evolving safeguards that reflect today’s threat landscape. Chrome is always exploring new options to help all of our users better protect themselves against common online threats like malware. As a first step, today Chrome is expanding its download scanning options for users of Advanced Protection.
Now, in addition to this warning, Chrome is giving Advanced Protection users the ability to send risky files to be scanned by Google Safe Browsing’s full suite of malware detection technology before opening the file. We expect these cloud-hosted scans to significantly improve our ability to detect when these files are malicious.
When a user downloads a file, Safe Browsing will perform a quick check using metadata, such as hashes of the file, to evaluate whether it appears potentially suspicious. For any downloads that Safe Browsing deems risky, but not clearly unsafe, the user will be presented with a warning and the ability to send the file to be scanned. If the user chooses to send the file, Chrome will upload it to Google Safe Browsing, which will scan it using its static and dynamic analysis techniques in real time. After a short wait, if Safe Browsing determines the file is unsafe, Chrome will warn the user. As always, users can bypass the warning and open the file without scanning, if they are confident the file is safe. Safe Browsing deletes uploaded files a short time after scanning.
Online threats are constantly changing, and it's important that users’ security protections automatically evolve as well. With the US election fast approaching, for example, Advanced Protection could be useful to members of political campaigns whose accounts are now more likely to be targeted. If you’re a user at high-risk of attack, visit g.co/advancedprotection to enroll in the Advanced Protection Program.
Thanks to your work, we have identified more than 750 previously unknown product abuse risks, preventing abuse in Google products and protecting our users. Collaboration to address abuse is important, and we are committed to supporting research on this growing challenge. To take it one step further, and as of today, we are announcing increased reward amounts for reports focusing on potential attacks in the product abuse space.
The nature of product abuse is constantly changing. Why? The technology (product and protection) is changing, the actors are changing, and the field is growing. Within this dynamic environment, we are particularly interested in research that protects users' privacy, ensures the integrity of our technologies, as well as prevents financial fraud or other harms at scale.
Research in the product abuse space helps us deliver trusted and safe experiences to our users. Martin Vigo's research on Google Meet's dial-in feature is one great example of an 31337 report that allowed us to better protect users against bad actors. His research provided insight on how an attacker could attempt to find Meet Phone Numbers/Pin, which enabled us to launch further protections to ensure that Meet would provide a secure technology connecting us while we're apart.
New Reward Amounts for Abuse Risks
What’s new? Based on the great submissions that we received in the past as well as feedback from our Bug Hunters, we increased the highest reward by 166% from $5,000 to $13,337. Research with medium to high impact and probability will now be eligible for payment up to $5,000.
What did not change? Identification of new product abuse risks remains the primary goal of the program. Reports that qualify for a reward are those that will result in changes to the product code, as opposed to removal of individual pieces of abusive content. The final reward amount for a given abuse risk report also remains at the discretion of the reward panel. When evaluating the impact of an abuse risk, the panels look at both the severity of the issue as well as the number of impacted users.
What's next? We plan to expand the scope of Vulnerability Research Grants to support research preventing abuse risks. Stay tuned for more information!
Starting today the new rewards take effect. Any reports that were submitted before September 1, 2020 will be rewarded based on the previous rewards table.
We look forward to working closely together with the researcher community to prevent abuse of Google products and ensure user safety.
Follow