Posted by Andrew Ahn, Product Manager, Google Play
[Cross-posted from the Android Developers Blog]

Google Play is committed to providing a secure and safe platform for billions of Android users on their journey discovering and experiencing the apps they love and enjoy. To deliver against this commitment, we worked last year to improve our abuse detection technologies and systems, and significantly increased our team of product managers, engineers, policy experts, and operations leaders to fight against bad actors.
In 2018, we introduced a series of new policies to protect users from new abuse trends, detected and removed malicious developers faster, and stopped more malicious apps from entering the Google Play Store than ever before. The number of rejected app submissions increased by more than 55 percent, and we increased app suspensions by more than 66 percent. These increases can be attributed to our continued efforts to tighten policies to reduce the number of harmful apps on the Play Store, as well as our investments in automated protections and human review processes that play critical roles in identifying and enforcing on bad apps.
In addition to identifying and stopping bad apps from entering the Play Store, our Google Play Protect system now scans over 50 billion apps on users' devices each day to make sure apps installed on the device aren't behaving in harmful ways. With such protection, apps from Google Play are eight times less likely to harm a user's device than Android apps from other sources.
Here are some areas we've been focusing on in the last year and that will continue to be a priority for us in 2019:

Protecting User Privacy

Protecting users' data and privacy is a critical factor in building user trust. We've long required developers to limit their device permission requests to what's necessary to provide the features of an app. Also, to help users understand how their data is being used, we've required developers to provide prominent disclosures about the collection and use of sensitive user data. Last year, we rejected or removed tens of thousands of apps that weren't in compliance with Play's policies related to user data and privacy.
In October 2018, we announced a new policy restricting the use of the SMS and Call Log permissions to a limited number of cases, such as where an app has been selected as the user's default app for making calls or sending text messages. We've recently started to remove apps from Google Play that violate this policy. We plan to introduce additional policies for device permissions and user data throughout 2019.

Developer integrity

We find that over 80% of severe policy violations are conducted by repeat offenders and abusive developer networks. When malicious developers are banned, they often create new accounts or buy developer accounts on the black market in order to come back to Google Play. We've further enhanced our clustering and account matching technologies, and by combining these technologies with the expertise of our human reviewers, we've made it more difficult for spammy developer networks to gain installs by blocking their apps from being published in the first place.

Harmful app contents and behaviors

As mentioned in last year's blog post, we fought against hundreds of thousands of impersonators, apps with inappropriate content, and Potentially Harmful Applications (PHAs). In a continued fight against these types of apps, not only do we apply advanced machine learning models to spot suspicious apps, we also conduct static and dynamic analyses, intelligently use user engagement and feedback data, and leverage skilled human reviews, which have helped in finding more bad apps with higher accuracy and efficiency.
Despite our enhanced and added layers of defense against bad apps, we know bad actors will continue to try to evade our systems by changing their tactics and cloaking bad behaviors. We will continue to enhance our capabilities to counter such adversarial behavior, and work relentlessly to provide our users with a secure and safe app store.
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Posted by Paul Crowley and Eric Biggers, Android Security & Privacy Team

Storage encryption protects your data if your phone falls into someone else's hands. Adiantum is an innovation in cryptography designed to make storage encryption more efficient for devices without cryptographic acceleration, to ensure that all devices can be encrypted.
Today, Android offers storage encryption using the Advanced Encryption Standard (AES). Most new Android devices have hardware support for AES via the ARMv8 Cryptography Extensions. However, Android runs on a wide range of devices. This includes not just the latest flagship and mid-range phones, but also entry-level Android Go phones sold primarily in developing countries, along with smart watches and TVs. In order to offer low cost options, device manufacturers sometimes use low-end processors such as the ARM Cortex-A7, which does not have hardware support for AES. On these devices, AES is so slow that it would result in a poor user experience; apps would take much longer to launch, and the device would generally feel much slower. So while storage encryption has been required for most devices since Android 6.0 in 2015, devices with poor AES performance (50 MiB/s and below) are exempt. We've been working to change this because we believe that encryption is for everyone.
In HTTPS encryption, this is a solved problem. The ChaCha20 stream cipher is much faster than AES when hardware acceleration is unavailable, while also being extremely secure. It is fast because it exclusively relies on operations that all CPUs natively support: additions, rotations, and XORs. For this reason, in 2014 Google selected ChaCha20 along with the Poly1305 authenticator, which is also fast in software, for a new TLS cipher suite to secure HTTPS internet connections. ChaCha20-Poly1305 has been standardized as RFC7539, and it greatly improves HTTPS performance on devices that lack AES instructions.
However, disk and file encryption present a special challenge. Data on storage devices is organized into "sectors" which today are typically 4096 bytes. When the filesystem makes a request to the device to read or write a sector, the encryption layer intercepts that request and converts between plaintext and ciphertext. This means that we must convert between a 4096-byte plaintext and a 4096-byte ciphertext. But to use RFC7539, the ciphertext must be slightly larger than the plaintext; a little space is needed for the cryptographic nonce and message integrity information. There are software techniques for finding places to store this extra information, but they reduce efficiency and can impose significant complexity on filesystem design.
Where AES is used, the conventional solution for disk encryption is to use the XTS or CBC-ESSIV modes of operation, which are length-preserving. Currently Android supports AES-128-CBC-ESSIV for full-disk encryption and AES-256-XTS for file-based encryption. However, when AES performance is insufficient there is no widely accepted alternative that has sufficient performance on lower-end ARM processors.
To solve this problem, we have designed a new encryption mode called Adiantum. Adiantum allows us to use the ChaCha stream cipher in a length-preserving mode, by adapting ideas from AES-based proposals for length-preserving encryption such as HCTR and HCH. On ARM Cortex-A7, Adiantum encryption and decryption on 4096-byte sectors is about 10.6 cycles per byte, around 5x faster than AES-256-XTS.
Unlike modes such as XTS or CBC-ESSIV, Adiantum is a true wide-block mode: changing any bit anywhere in the plaintext will unrecognizably change all of the ciphertext, and vice versa. It works by first hashing almost the entire plaintext using a keyed hash based on Poly1305 and another very fast keyed hashing function called NH. We also hash a value called the "tweak" which is used to ensure that different sectors are encrypted differently. This hash is then used to generate a nonce for the ChaCha encryption. After encryption, we hash again, so that we have the same strength in the decryption direction as the encryption direction. This is arranged in a configuration known as a Feistel network, so that we can decrypt what we've encrypted. A single AES-256 invocation on a 16-byte block is also required, but for 4096-byte inputs this part is not performance-critical.
Cryptographic primitives like ChaCha are organized in "rounds", with each round increasing our confidence in security at a cost in speed. To make disk encryption fast enough on the widest range of devices, we've opted to use the 12-round variant of ChaCha rather than the more widely used 20-round variant. Each round vastly increases the difficulty of attack; the 7-round variant was broken in 2008, and though many papers have improved on this attack, no attack on 8 rounds is known today. This ratio of rounds used to rounds broken today is actually better for ChaCha12 than it is for AES-256.
Even though Adiantum is very new, we are in a position to have high confidence in its security. In our paper, we prove that it has good security properties, under the assumption that ChaCha12 and AES-256 are secure. This is standard practice in cryptography; from "primitives" like ChaCha and AES, we build "constructions" like XTS, GCM, or Adiantum. Very often we can offer strong arguments but not a proof that the primitives are secure, while we can prove that if the primitives are secure, the constructions we build from them are too. We don't have to make assumptions about NH or the Poly1305 hash function; these are proven to have the cryptographic property ("ε-almost-∆-universality") we rely on.
Adiantum is named after the genus of the maidenhair fern, which in the Victorian language of flowers (floriography) represents sincerity and discretion.

Additional resources

The full details of our design, and the proof of security, are in our paper Adiantum: length-preserving encryption for entry-level processors in IACR Transactions on Symmetric Cryptology; this will be presented at the Fast Software Encryption conference (FSE 2019) in March.
Generic and ARM-optimized implementations of Adiantum are available in the Android common kernels v4.9 and higher, and in the mainline Linux kernel v5.0 and higher. Reference code, test vectors, and a benchmarking suite are available at https://github.com/google/adiantum.
Android device manufacturers can enable Adiantum for either full-disk or file-based encryption on devices with AES performance <= 50 MiB/sec and launching with Android Pie. Where hardware support for AES exists, AES is faster than Adiantum; AES must still be used where its performance is above 50 MiB/s. In Android Q, Adiantum will be part of the Android platform, and we intend to update the Android Compatibility Definition Document (CDD) to require that all new Android devices be encrypted using one of the allowed encryption algorithms.

Acknowledgements: This post leveraged contributions from Greg Kaiser and Luke Haviland. Adiantum was designed by Paul Crowley and Eric Biggers, implemented in Android by Eric Biggers and Greg Kaiser, and named by Danielle Roberts.

Posted Lukasz Siewierski, Android Security & Privacy Team


Google Play Protect detects Potentially Harmful Applications (PHAs) which Google Play Protect defines as any mobile app that poses a potential security risk to users or to user data—commonly referred to as "malware." in a variety of ways, such as static analysis, dynamic analysis, and machine learning. While our systems are great at automatically detecting and protecting against PHAs, we believe the best security comes from the combination of automated scanning and skilled human review.
With this blog series we will be sharing our research analysis with the research and broader security community, starting with the PHA family, Zen. Zen uses root permissions on a device to automatically enable a service that creates fake Google accounts. These accounts are created by abusing accessibility services. Zen apps gain access to root permissions from a rooting trojan in its infection chain. In this blog post, we do not differentiate between the rooting component and the component that abuses root: we refer to them interchangeably as Zen. We also describe apps that we think are coming from the same author or a group of authors. All of the PHAs that are mentioned in this blog post were detected and removed by Google Play Protect.

Background

Uncovering PHAs takes a lot of detective work and unraveling the mystery of how they're possibly connected to other apps takes even more. PHA authors usually try to hide their tracks, so attribution is difficult. Sometimes, we can attribute different apps to the same author based on small, unique pieces of evidence that suggest similarity, such as a repetition of an exceptionally rare code snippet, asset, or a particular string in the debug logs. Every once in a while, authors leave behind a trace that allows us to attribute not only similar apps, but also multiple different PHA families to the same group or person.
However, the actual timeline of the creation of different variants is unclear. In April 2013, we saw the first sample, which made heavy use of dynamic code loading (i.e., fetching executable code from remote sources after the initial app is installed). Dynamic code loading makes it impossible to state what kind of PHA it was. This sample displayed ads from various sources. More recent variants blend rooting capabilities and click fraud. As rooting exploits on Android become less prevalent and lucrative, PHA authors adapt their abuse or monetization strategy to focus on tactics like click fraud.
This post doesn't follow the chronological evolution of Zen, but instead covers relevant samples from least to most complex.

Apps with a custom-made advertisement SDK

The simplest PHA from the author's portfolio used a specially crafted advertisement SDK to create a proxy for all ads-related network traffic. By proxying all requests through a custom server, the real source of ads is opaque. This example shows one possible implementation of this technique.
This approach allows the authors to combine ads from third-party advertising networks with ads they created for their own apps. It may even allow them to sell ad space directly to application developers. The advertisement SDK also collects statistics about clicks and impressions to make it easier to track revenue. Selling the ad traffic directly or displaying ads from other sources in a very large volume can provide direct profit to the app author from the advertisers.
We have seen two types of apps that use this custom-made SDK. The first are games of very low quality that mimic the experience of popular mobile games. While the counterfeit games claim to provide similar functionality to the popular apps, they are simply used to display ads through a custom advertisement SDK.
The second type of apps reveals an evolution in the author's tactics. Instead of implementing very basic gameplay, the authors pirated and repackaged the original game in their app and bundled with it their advertisement SDK. The only noticeable difference is the game has more ads, including ads on the very first screen.
In all cases, the ads are used to convince users to install other apps from different developer accounts, but written by the same group. Those apps use the same techniques to monetize their actions.

Click fraud apps

The authors' tactics evolved from advertisement spam to real PHA (Click Fraud). Click fraud PHAs simulate user clicks on ads instead of simply displaying ads and waiting for users to click them. This allows the PHA authors to monetize their apps more effectively than through regular advertising. This behavior negatively impacts advertisement networks and their clients because advertising budget is spent without acquiring real customers, and impacts user experience by consuming their data plan resources.
The click fraud PHA requests a URL to the advertising network directly instead of proxying it through an additional SDK. The command & control server (C&C server) returns the URL to click along with a very long list of additional parameters in JSON format. After rendering the ad on the screen, the app tries to identify the part of the advertisement website to click. If that part is found, the app loads Javascript snippets from the JSON parameters to click a button or other HTML element, simulating a real user click. Because a user interacting with an ad often leads to a higher chance of the user purchasing something, ad networks often "pay per click" to developers who host their ads. Therefore, by simulating fraudulent clicks, these developers are making money without requiring a user to click on an advertisement.
This example code shows a JSON reply returned by the C&C server. It has been shortened for brevity.

{
 "data": [{
  "id": "107",
  "url": "<ayud_url>",
  "click_type": "2",
  "keywords_js": [{
   "keyword": "<a class=\"show_hide btnnext\"",
   "js": "javascript:window:document.getElementsByClassName(\"show_hide btnnext\")[0].click();",
  {
   "keyword": "value=\"Subscribe\" id=\"sub-click\"",
   "js": "javascript:window:document.getElementById(\"sub-click\").click();"

Based on this JSON reply, the app looks for an HTML snippet that corresponds to the active element (show_hide btnnext) and, if found, the Javascript snippet tries to perform a click() method on it.

Rooting trojans

The Zen authors have also created a rooting trojan. Using a publicly available rooting framework, the PHA attempts to root devices and gain persistence on them by reinstalling itself on the system partition of rooted device. Installing apps on the system partition makes it harder for the user to remove the app.
This technique only works for unpatched devices running Android 4.3 or lower. Devices running Android 4.4 and higher are protected by Verified Boot.
Zen's rooting trojan apps target a specific device model with a very specific system image. After achieving root access the app tries to replace the framework.jar file on the system partition. Replicating framework.jar allows the app to intercept and modify the behavior of the Android standard API. In particular, these apps try to add an additional method called statistics() into the Activity class. When inserted, this method runs every time any Activity object in any Android app is created. This happens all the time in regular Android apps, as Activity is one of the fundamental Android UI elements. The only purpose of this method is to connect to the C&C server.

The Zen trojan

After achieving persistence, the trojan downloads additional payloads, including another trojan called Zen. Zen requires root to work correctly on the Android operating system.
The Zen trojan uses its root privileges to turn on accessibility service (a service used to allow Android users with disabilities to use their devices) for itself by writing to a system-wide setting value enabled_accessibility_services. Zen doesn't even check for the root privilege: it just assumes it has it. This leads us to believe that Zen is just part of a larger infection chain. The trojan implements three accessibility services directed at different Android API levels and uses these accessibility services, chosen by checking the operating system version, to create new Google accounts. This is done by opening the Google account creation process and parsing the current view. The app then clicks the appropriate buttons, scrollbars, and other UI elements to go through account sign-up without user intervention.
During the account sign-up process, Google may flag the account creation attempt as suspicious and prompt the app to solve a CAPTCHA. To get around this, the app then uses its root privilege to inject code into the Setup Wizard, extract the CAPTCHA image, and sends it to a remote server to try to solve the CAPTCHA. It is unclear if the remote server is capable of solving the CAPTCHA image automatically or if this is done manually by a human in the background. After the server returns the solution, the app enters it into the appropriate text field to complete the CAPTCHA challenge.
The Zen trojan does not implement any kind of obfuscation except for one string that is encoded using Base64 encoding. It's one of the strings - "How you'll sign in" - that it looks for during the account creation process. The code snippet below shows part of the screen parsing process.

if (!title.containsKey("Enter the code")) { 
  if (!title.containsKey("Basic information")) { 
    if (!title.containsKey(new String(android.util.Base64.decode("SG93IHlvdeKAmWxsIHNpZ24gaW4=".getBytes(), 0)))) { 
      if (!title.containsKey("Create password")) { 
        if (!title.containsKey("Add phone number")) {

Apart from injecting code to read the CAPTCHA, the app also injects its own code into the system_server process, which requires root privileges. This indicates that the app tries to hide itself from any anti-PHA systems that look for a specific app process name or does not have the ability to scan the memory of the system_server process.
The app also creates hooks to prevent the phone from rebooting, going to sleep or allowing the user from pressing hardware buttons during the account creation process. These hooks are created using the root access and a custom native code called Lmt_INJECT, although the algorithm for this is well known.
First, the app has to turn off SELinux protection. Then the app finds a process id value for the process it wants to inject with code. This is done using a series of syscalls as outlined below. The "source process" refers to the Zen trojan running as root, while the "target process" refers to the process to which the code is injected and [pid] refers to the target process pid value.

1. The source process checks the mapping between a process id and a process name. This is done by reading the /proc/[pid]/cmdline file.
   This very first step fails in Android 7.0 and higher, even with a root permission. The /proc filesystem is now mounted with a hidepid=2 parameter, which means that the process cannot access other process /proc/[pid] directory.
2. A ptrace_attach syscall is called. This allows the source process to trace the target.
3. The source process looks at its own memory to calculate the offset between the beginning of the libc library and the mmap address.
4. The source process reads /proc/[pid]/maps to find where libc is located in the target process memory. By adding the previously calculated offset, it can get the address of the mmap function in the target process memory.
5. The source process tries to determine the location of dlopen, dlsym, and dlclose functions in the target process. It uses the same technique as it used to determine the offset to the mmap function.
6. The source process writes the native shellcode into the memory region allocated by mmap. Additionally, it also writes addresses of dlopen, dlsym, and dlclose into the same region, so that they can be used by the shellcode. Shellcode simply uses dlopen to open a .so file within the target process and then dlsym to find a symbol in that file and run it.
7. The source process changes the registers in the target process so that PC register points directly to the shellcode. This is done using the ptrace syscall.

This diagram illustrates the whole process.

Summary

PHA authors go to great lengths to come up with increasingly clever ways to monetize their apps.
Zen family PHA authors exhibit a wide range of techniques, from simply inserting an advertising SDK to a sophisticated trojan. The app that resulted in the largest number of affected users was the click fraud version, which was installed over 170,000 times at its peak in February 2018. The most affected countries were India, Brazil, and Indonesia. In most cases, these click fraud apps were uninstalled by the users, probably due to the low quality of the apps.
If Google Play Protect detects one of these apps, Google Play Protect will show a warning to users.
We are constantly on the lookout for new threats and we are expanding our protections. Every device with Google Play includes Google Play Protect and all apps on Google Play are automatically and periodically scanned by our solutions.

You can check the status of Google Play Protect on your device:

1. Open your Android device's Google Play Store app.
2. Tap Menu>Play Protect.
3. Look for information about the status of your device.
   
   

   Hashes of samples

   Type	Package name	SHA256 digest
   Custom ads	com.targetshoot.zombieapocalypse.sniper.zombieshootinggame	5d98d8a7a012a858f0fa4cf8d2ed3d5a82937b1a98ea2703d440307c63c6c928
   Click fraud	com.counterterrorist.cs.elite.combat.shootinggame	84672fb2f228ec749d3c3c1cb168a1c31f544970fd29136bea2a5b2cefac6d04
   Rooting trojan	com.android.world.news	bd233c1f5c477b0cc15d7f84392dab3a7a598243efa3154304327ff4580ae213
   Zen trojan	com.lmt.register	eb12cd65589cbc6f9d3563576c304273cb6a78072b0c20a155a0951370476d8d

Posted by Billy Lau and René Mayrhofer, Android Security & Privacy Team

Customization is one of Android's greatest strengths. Android's open source nature has enabled thousands of device types that cover a variety of use cases. In addition to adding features to the Android Open Source Project, researchers, developers, service providers, and device and chipset manufacturers can make updates to improve Android security. Investing and engaging in academic research advances the state-of-the-art security techniques, contributes to science, and delivers cutting edge security and privacy features into the hands of end users. To foster more cooperative applied research between the Android Security and Privacy team and the wider academic and industrial community, we're launching ASPIRE (Android Security and PrIvacy REsearch).

ASPIRE's goal is encouraging the development of new security and privacy technology that impacts the Android ecosystem in the next 2 to 5 years, but isn't planned for mainline Android development. This timeframe extends beyond the next annual Android release to allow adequate time to analyze, develop, and stabilize research into features before including in the platform. To collaborate with security researchers, we're hosting events and creating more channels to contribute research.

On October 25th 2018, we invited top security and privacy researchers from around the world to present at Android Security Local Research Day (ASLR-D). At this event, external researchers and Android Security and Privacy team members discussed current issues and strategies that impact the future direction of security research—for Android and the entire industry.

We can't always get everyone in the same room and good ideas come from everywhere. So we're inviting all academic researchers to help us protect billions of users. Research collaborations with Android should be as straightforward as collaborating with the research lab next door. To get involved you can:

1. Submit an Android security / privacy research idea or proposal to the Google Faculty Research Awards (FRA) program.
2. Apply for a research internship as a student pursuing an advanced degree.
3. Apply to become a Visiting Researcher at Google.
4. If you have any security or privacy questions that may help with your research, reach out to us.
5. Co-author publications with Android team members, outside the terms of FRA.
6. Collaborate with Android team members to make changes to the Android Open Source Project.

Let’s work together to make Android the most secure platform—now and in the future.