MalBus: Popular South Korean Bus App Series in Google Play Found Dropping Malware After 5 Years of Development

McAfee’s Mobile Research team recently learned of a new malicious Android application masquerading as a plugin for a transportation application series developed by a South Korean developer. The series provides a range of information for each region of South Korea, such as bus stop locations, bus arrival times and so on. There are a total of four apps in the series, with three of them available from Google Play since 2013 and the other from around 2017. Currently, all four apps have been removed from Google Play while the fake plugin itself was never uploaded to the store. While analyzing the fake plugin, we were looking for initial downloaders and additional payloads – we discovered one specific version of each app in the series (uploaded at the same date) which was dropping malware onto the devices on which they were installed, explaining their removal from Google Play after 5 years of development.

Figure 1. Cached Google Play page of Daegu Bus application, one of the apps in series

When the malicious transportation app is installed, it downloads an additional payload from hacked web servers which includes the fake plugin we originally acquired. After the fake plugin is downloaded and installed, it does something completely different – it acts as a plugin of the transportation application and installs a trojan on the device, trying to phish users to input their Google account password and completely take control of the device. What is interesting is that the malware uses the native library to take over the device and also deletes the library to hide from detection. It uses names of popular South Korean services like Naver, KakaoTalk, Daum and SKT. According to our telemetry data, the number of infected devices was quite low, suggesting that the final payload was installed to only a small group of targets.

The Campaign

The following diagram explains the overall flow from malware distribution to device infection.

Figure 2. Device infection process

When the malicious version of the transportation app is installed, it checks whether the fake plugin is already installed and, if not, downloads from the server and installs it. After that, it downloads and executes an additional native trojan binary which is similar to the trojan which is dropped by the fake plugin. After everything is done, it connects with the C2 servers and handles received commands.

Initial Downloader

The following table shows information about the malicious version of each transportation app in the series. As the Google Play number of install stats shows, these apps have been downloaded on many devices.

Unlike the clean version of the app, the malicious version contains a native library named “libAudio3.0.so”.

Figure 3. Transportation app version with malicious native library embedded

In the BaseMainActivity class of the app, it loads the malicious library and calls startUpdate() and updateApplication().

Figure 4. Malicious library being loaded and executed in the app

startUpdate() checks whether the app is correctly installed by checking for the existence of a specific flag file named “background.png” and whether the fake plugin is installed already. If the device is not already infected, the fake plugin is downloaded from a hacked web server and installed after displaying a toast message to the victim. updateApplication() downloads a native binary from the same hacked server and dynamically loads it. The downloaded file (saved as libSound1.1.so) is then deleted after being loaded into memory and, finally, it executes an exported function which acts as a trojan. As previously explained, this file is similar to the file dropped by the fake plugin which is discussed later in this post.

Figure 5 Additional payload download servers

Fake Plugin

The fake plugin is downloaded from a hacked web server with file extension “.mov” to look like a media file. When it is installed and executed, it displays a toast message saying the plugin was successfully installed (in Korean) and calls a native function named playMovie(). The icon for the fake plugin soon disappears from the screen. The native function implemented in LibMovie.so, which is stored inside the asset folder, drops a malicious trojan to the current running app’s directory masquerading as libpng.2.1.so file. The dropped trojan is originally embedded in the LibMovie.so xor’ed, which is decoded at runtime. After giving permissions, the address of the exported function “Libfunc” in the dropped trojan is dynamically retrieved using dlsym(). The dropped binary in the filesystem is deleted to avoid detection and finally Libfunc is executed.

Figure 6 Toast message when malware is installed

In the other forked process, it tries to access the “naver.property” file on an installed SD Card, if there is one, and if it succeeds, it tries starting “.KaKaoTalk” activity which displays a Google phishing page (more on that in the next section) . The overall flow of the dropper is explained in the following diagram:

Figure 7. Execution flow of the dropper

Following is a snippet of a manifest file showing that “.KaKaoTalk” activity is exported.

Figure 8. Android Manifest defining “.KaKaoTalk” activity as exported

Phishing in JavaScript

KakaoTalk class opens a local HTML file, javapage.html, with the user’s email address registered on the infected device automatically set to log into their account.

Figure 9. KakaoTalk class loads malicious local html file

The victim’s email address is set to the local page through a JavaScript function setEmailAddress after the page is finished loading. A fake Korean Google login website is displayed:

Figure 10. The malicious JavaScript shows crafted Google login page with user account

We found the following attempts of exploitation of Google legitimate services by the malware author:

  • Steal victim’s Google account and password
  • Request password recovery for a specific account
  • Set recovery email address when creating new Google account

An interesting element of the phishing attack is that the malware authors tried to set their own email as the recovery address on Google’s legitimate services. For example, when a user clicks on the new Google account creation link in the phishing page, the crafted link is opened with the malware author’s email address as a parameter of RecoveryEmailAddress.

Figure 11. The crafted JavaScript attempts to set recovery email address for new Google account creation.

Fortunately for end users, none of the above malicious attempts are successful. The parameter with the malware author’s email address is simply ignored at the account creation stage.

Trojan

In addition to the Google phishing page, when “Libfunc” function of the trojan (dropped by the fake plugin or downloaded from the server) is executed, the mobile phone is totally compromised. It receives commands from the following hardcoded list of C2 servers. The main functionality of the trojan is implemented in a function called “doMainProc()”. Please note that there are a few variants of the trojanwith different functionality but, overall, they are pretty much the same.

Figure 12. Hardcoded list of C2 servers

The geolocation of hardcoded C2 servers lookslike the following:

Figure 13. Location of C2 Servers

Inside doMainProc(), the trojan receives commands from the C2 server and calls appropriate handlers. Part of the switch block below gives us an idea of what type of commands this trojan supports.

Figure 14. Subset of command handlers implemented in the dropped trojan.

As you can see, it has all the functionality that a normal trojan has. Downloading, uploading and deleting files on the device, leaking information to a remote server and so on. The following table explains supported C2 commands:

Figure 15. C2 Commands

Before entering the command handling loop, the trojan does some initialization, like sending device information files to the server and checking the UID of the device. Only after the UID checking returns a 1 does it enter the loop.

Figure 16 Servers connected before entering command loop

Among these commands, directory indexing in particular is important. The directory structure is saved in a file named “kakao.property” and while indexing the given path in the user device, it checks the file with specific keywords and if it matches, uploads the file to the remote upload server. These keywords are Korean and its translated English version is as per the following table:

Figure 17 Search file keywords

By looking at the keywords we can anticipate that the malware authors were looking for files related to the military, politics and so on. These files are uploaded to a separate server.

Figure 18 Keyword matching file upload server

Conclusion

Applications can easily trick users into installing them before then leaking sensitive information. Also, it is not uncommon to see malware sneaking onto the official Google Play store, making it hard for users to protect their devices. This malware has not been written for ordinary phishing attempts, but rather very targeted attacks, searching the victim’s devices for files related to the military and politics, likely trying to leak confidential information. Users should always install applications that they can fully trust even though they are downloaded from trusted sources.

McAfee Mobile Security detects this threat as Android/MalBus and alerts mobile users if it is present, while protecting them from any data loss. For more information about McAfee Mobile Security, visit https://www.mcafeemobilesecurity.com.

Hashes (SHA-256)

Initial Downloader (APK)
• 19162b063503105fdc1899f8f653b42d1ff4fcfcdf261f04467fad5f563c0270
• bed3e665d2b5fd53aab19b8a62035a5d9b169817adca8dfb158e3baf71140ceb
• 3252fbcee2d1aff76a9f18b858231adb741d4dc07e803f640dcbbab96db240f9
• e71dc11e8609f6fd84b7af78486b05a6f7a2c75ed49a46026e463e9f86877801

Fake Plugin (APK)
• ecb6603a8cd1354c9be236a3c3e7bf498576ee71f7c5d0a810cb77e1138139ec
• b8b5d82eb25815dd3685630af9e9b0938bccecb3a89ce0ad94324b12d25983f0

Trojan (additional payload)
• b9d9b2e39247744723f72f63888deb191eafa3ffa137a903a474eda5c0c335cf
• 12518eaa24d405debd014863112a3c00a652f3416df27c424310520a8f55b2ec
• 91f8c1f11227ee1d71f096fd97501c17a1361d71b81c3e16bcdabad52bfa5d9f
• 20e6391cf3598a517467cfbc5d327a7bb1248313983cba2b56fd01f8e88bb6b9

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McAfee Labs 2019 Threats Predictions Report

These predictions were written by Eoin Carroll, Taylor Dunton, John Fokker, German Lancioni, Lee Munson, Yukihiro Okutomi, Thomas Roccia, Raj Samani, Sekhar Sarukkai, Dan Sommer, and Carl Woodward.

As 2018 draws to a close, we should perhaps be grateful that the year has not been entirely dominated by ransomware, although the rise of the GandCrab and SamSam variants show that the threat remains active. Our predictions for 2019 move away from simply providing an assessment on the rise or fall of a particular threat, and instead focus on current rumblings we see in the cybercriminal underground that we expect to grow into trends and subsequently threats in the wild.

We have witnessed greater collaboration among cybercriminals exploiting the underground market, which has allowed them to develop efficiencies in their products. Cybercriminals have been partnering in this way for years; in 2019 this market economy will only expand. The game of cat and mouse the security industry plays with ransomware developers will escalate, and the industry will need to respond more quickly and effectively than ever before.

Social media has been a part of our lives for more than a decade. Recently, nation-states have infamously used social media platforms to spread misinformation. In 2019, we expect criminals to begin leveraging those tactics for their own gain. Equally, the continued growth of the Internet of Things in the home will inspire criminals to target those devices for monetary gain.

One thing is certain: Our dependency on technology has become ubiquitous. Consider the breaches of identity platforms, with reports of 50 million users being affected. It is no longer the case that a breach is limited to that platform. Everything is connected, and you are only as strong as your weakest link. In the future, we face the question of which of our weakest links will be compromised.

—Raj Samani, Chief Scientist and McAfee Fellow, Advanced Threat Research

Twitter @Raj_Samani

 

Predictions

Cybercriminal Underground to Consolidate, Create More Partnerships to Boost Threats

Artificial Intelligence the Future of Evasion Techniques

Synergistic Threats Will Multiply, Requiring Combined Responses

Misinformation, Extortion Attempts to Challenge Organizations’ Brands

Data Exfiltration Attacks to Target the Cloud

Voice-Controlled Digital Assistants the Next Vector in Attacking IoT Devices

Cybercriminals to Increase Attacks on Identity Platforms and Edge Devices Under Siege

Cybercriminal Underground to Consolidate, Create More Partnerships to Boost Threats

Hidden hacker forums and chat groups serve as a market for cybercriminals, who can buy malware, exploits, botnets, and other shady services. With these off-the-shelf products, criminals of varying experience and sophistication can easily launch attacks. In 2019, we predict the underground will consolidate, creating fewer but stronger malware-as-a-service families that will actively work together. These increasingly powerful brands will drive more sophisticated cryptocurrency mining, rapid exploitation of new vulnerabilities, and increases in mobile malware and stolen credit cards and credentials.

We expect more affiliates to join the biggest families, due to the ease of operation and strategic alliances with other essential top-level services, including exploit kits, crypter services, Bitcoin mixers, and counter-antimalware services. Two years ago, we saw many of the largest ransomware families, for example, employ affiliate structures. We still see numerous types of ransomware pop up, but only a few survive because most cannot attract enough business to compete with the strong brands, which offer higher infection rates as well as operational and financial security. At the moment the largest families actively advertise their goods; business is flourishing because they are strong brands (see GandCrab) allied with other top-level services, such as money laundering or making malware undetectable.

Underground businesses function successfully because they are part of a trust-based system. This may not be a case of “honor among thieves,” yet criminals appear to feel safe, trusting they cannot be touched in the inner circle of their forums. We have seen this trust in the past, for example, with the popular credit card shops in the first decade of the century, which were a leading source of cybercrime until major police action broke the trust model.

As endpoint detection grows stronger, the vulnerable remote desktop protocol (RDP) offers another path for cybercriminals. In 2019 we predict malware, specifically ransomware, will increasingly use RDP as an entry point for an infection. Currently, most underground shops advertise RDP access for purposes other than ransomware, typically using it as a stepping stone to gain access to Amazon accounts or as a proxy to steal credit cards. Targeted ransomware groups and ransomware-as-a-service (RaaS) models will take advantage of RDP, and we have seen highly successful under-the-radar schemes use this tactic. Attackers find a system with weak RDP, attack it with ransomware, and propagate through networks either living off the land or using worm functionality (EternalBlue). There is evidence that the author of GandCrab is already working on an RDP option.

We also expect malware related to cryptocurrency mining will become more sophisticated, selecting which currency to mine on a victim’s machine based on the processing hardware (WebCobra) and the value of a specific currency at a given time.

Next year, we predict the length of a vulnerability’s life, from detection to weaponization, will grow even shorter. We have noticed a trend of cybercriminals becoming more agile in their development process. They gather data on flaws from online forums and the Common Vulnerabilities and Exposures database to add to their malware. We predict that criminals will sometimes take a day or only hours to implement attacks against the latest weaknesses in software and hardware.

We expect to see an increase in underground discussions on mobile malware, mostly focused on Android, regarding botnets, banking fraud, ransomware, and bypassing two-factor authentication security. The value of exploiting the mobile platform is currently underestimated as phones offer a lot to cybercriminals given the amount of access they have to sensitive information such as bank accounts.

Credit card fraud and the demand for stolen credit card details will continue, with an increased focus on online skimming operations that target third-party payment platforms on large e-commerce sites. From these sites, criminals can silently steal thousands of fresh credit cards details at a time. Furthermore, social media is being used to recruit unwitting users, who might not know they are working for criminals when they reship goods or provide financial services.

We predict an increase in the market for stolen credentials—fueled by recent large data breaches and by bad password habits of users. The breaches lead, for example, to the sale of voter records and email-account hacking. These attacks occur daily.

Artificial Intelligence the Future of Evasion Techniques

To increase their chances of success, attackers have long employed evasion techniques to bypass security measures and avoid detection and analysis. Packers, crypters, and other tools are common components of attackers’ arsenals. In fact, an entire underground economy has emerged, offering products and dedicated services to aid criminal activities. We predict in 2019, due to the ease with which criminals can now outsource key components of their attacks, evasion techniques will become more agile due to the application of artificial intelligence. Think the counter-AV industry is pervasive now? This is just the beginning.

In 2018 we saw new process-injection techniques such as “process doppelgänging” with the SynAck ransomware, and PROPagate injection delivered by the RigExploit Kit. By adding technologies such as artificial intelligence, evasion techniques will be able to further circumvent protections.

Different evasions for different malware

In 2018, we observed the emergence of new threats such as cryptocurrency miners, which hijack the resources of infected machines. With each threat comes inventive evasion techniques:

  • Cryptocurrency mining: Miners implement a number of evasion techniques. One example is WaterMiner, which simply stops its mining process when the victim runs the Task Manager or an antimalware scan.
  • Exploit kits: Popular evasion techniques include process injection or the manipulation of memory space and adding arbitrary code. In-memory injection is a popular infection vector for avoiding detection during delivery.
  • Botnets: Code obfuscation or anti-disassembling techniques are often used by large botnets that infect thousands of victims. In May 2018, AdvisorsBot was discovered using junk code, fake conditional instructions, XOR encryption, and even API hashing. Because bots tend to spread widely, the authors implemented many evasion techniques to slow reverse engineering. They also used obfuscation mechanisms for communications between the bots and control servers. Criminals use botnets for activities such as DDOS for hire, proxies, spam, or other malware delivery. Using evasion techniques is critical for criminals to avoid or delay botnet takedowns.
  • Advanced persistent threats: Stolen certificates bought on the cybercriminal underground are often used in targeted attacks to bypass antimalware detection. Attackers also use low-level malware such as rootkits or firmware-based threats. For example, in 2018 ESET discovered the first UEFI rootkit, LoJax. Security researchers have also seen destructive features used as anti-forensic techniques: The OlympicDestroyer malware targeted the Olympic Games organization and erased event logs and backups to avoid investigation.

Artificial intelligence the next weapon

In recent years, we have seen malware using evasion techniques to bypass machine learning engines. For example, in 2017 the Cerber ransomware dropped legitimate files on systems to trick the engine that classifies files. In 2018, PyLocky ransomware used InnoSetup to package the malware and avoid machine learning detection.

Clearly, bypassing artificial intelligence engines is already on the criminal to-do list; however, criminals can also implement artificial intelligence in their malicious software. We expect evasion techniques to begin leveraging artificial intelligence to automate target selection, or to check infected environments before deploying later stages and avoiding detection.

Such implementation is game changing in the threat landscape. We predict it will soon be found in the wild.

Synergistic Threats Will Multiply, Requiring Combined Responses

This year we have seen cyber threats adapt and pivot faster than ever. We have seen ransomware evolving to be more effective or operate as a smoke screen. We have seen cryptojacking soar, as it provides a better, and safer, return on investment than ransomware. We can still see phishing going strong and finding new vulnerabilities to exploit. We also noticed fileless and “living off the land” threats are more slippery and evasive than ever, and we have even seen the incubation of steganography malware in the Pyeongchang Olympics campaign. In 2019, we predict attackers will more frequently combine these tactics to create multifaced, or synergistic, threats.

What could be worse?

Attacks are usually centered on the use of one threat. Bad actors concentrate their efforts on iterating and evolving one threat at a time for effectiveness and evasion. When an attack is successful, it is classified as ransomware, cryptojacking, data exfiltration, etc., and defenses are put in place. At this point, the attack’s success rate is significantly reduced. However, if a sophisticated attack involves not one but five top-notch threats synergistically working together, the defense panorama could become very blurry. The challenge arises when an attempt is made to identify and mitigate the attack. Because the ultimate attack goals are unknown, one might get lost in the details of each threat as it plays a role in the chain.

One of the reasons synergic threats are becoming a reality is because bad actors are improving their skills by developing foundations, kits, and reusable threat components. As attackers organize their efforts into a black-market business model, they can focus on adding value to previous building blocks. This strategy allows them to orchestrate multiple threats instead of just one to reach their goals.

An example is worth a thousand words

Imagine an attack that starts with a phishing threat—not a typical campaign using Word documents, but a novel technique. This phishing email contains a video attachment. When you open the video, your video player does not play and prompts you to update the codec. Once you run the update, a steganographic polyglot file (a simple GIF) is deployed on your system. Because it is a polyglot (a file that conforms to more than one format at the same time), the GIF file schedules a task that fetches a fileless script hosted on a compromised system. That script running in memory evaluates your system and decides to run either ransomware or a cryptocurrency miner. That is a dangerous synergistic threat in action.

The attack raises many questions: What are you dealing with? Is it phishing 2.0? Is it stegware? Is it fileless and “living off the land”? Cryptojacking? Ransomware? It is everything at the same time.

This sophisticated but feasible example demonstrates that focusing on one threat may not be enough to detect or remediate an attack. When you aim to classify the attack into a single category, you might lose the big picture and thus be less effective mitigating it. Even if you stop the attack in the middle of the chain, discovering the initial and final stages is as important for protecting against future attempts.

Be curious, be creative, connect your defenses

Tackling sophisticated attacks based on synergic threats requires questioning every threat. What if this ransomware hit was part of something bigger? What if this phishing email pivots to a technique that employees are not trained for? What if we are missing the real goal of the attack?

Bearing these questions in mind will not only help capture the big picture, but also get the most of security solutions. We predict bad actors will add synergy to their attacks, but cyber defenses can also work synergistically.

Cybercriminals to Use Social Media Misinformation, Extortion Campaigns to Challenge Organizations’ Brands

The elections were influenced, fake news prevails, and our social media followers are all foreign government–controlled bots. At least that’s how the world feels sometimes. To say recent years have been troubled for social media companies would be an understatement. During this period a game of cat and mouse has ensued, as automated accounts are taken down, adversaries tactics evolve, and botnet accounts emerge looking more legitimate than ever before. In 2019, we predict an increase of misinformation and extortion campaigns via social media that will focus on brands and originate not from nation-state actors but from criminal groups.

Nation-states leverage bot battalions to deliver messages or manipulate opinion, and their effectiveness is striking. Bots often will take both sides of a story to spur debate, and this tactic works. By employing a system of amplifying nodes, as well as testing the messaging (including hashtags) to determine success rates, botnet operators demonstrate a real understanding of how to mold popular opinion on critical issues.

In one example, an account that was only two weeks old with 279 followers, most of which were other bots, began a harassment campaign against an organization. By amplification, the account generated an additional 1,500 followers in only four weeks by simply tweeting malicious content about their target.

Activities to manipulate public opinion have been well documented and bots well versed in manipulating conversations to drive agendas stand ready. Next year we expect that cybercriminals will repurpose these campaigns to extort companies by threatening to damage their brands. Organizations face a serious danger.

Data Exfiltration Attacks to Target the Cloud

In the past two years, enterprises have widely adopted the Software-as-a-Service model, such as Office 365, as well as Infrastructure- and Platform-as-a-Service cloud models, such as AWS and Azure. With this move, far more corporate data now resides in the cloud. In 2019, we expect a significant increase in attacks that follow the data to the cloud.

With the increased adoption of Office 365, we have noticed a surge of attacks on the service— especially attempts to compromise email. One threat the McAfee cloud team uncovered was the botnet KnockKnock, which targeted system accounts that typically do not have multifactor authentication. We have also seen the emergence of exploits of the trust model in the Open Authorization standard. One was launched by Fancy Bear, the Russian cyber espionage group, phishing users with a fake Google security app to gain access to user data.

Similarly, during the last couple of years we have seen many high-profile data breaches attributed to misconfigured Amazon S3 buckets. This is clearly not the fault of AWS. Based on the shared responsibility model, the customer is on the hook to properly configure IaaS/PaaS infrastructure and properly protect their enterprise data and user access. Complicating matters, many of these misconfigured buckets are owned by vendors in their supply chains, rather than by the target enterprises. With access to thousands of open buckets and credentials, bad actors are increasingly opting for these easy pickings.

McAfee has found that 21% of data in the cloud is sensitive—such as intellectual property, and customer and personal data—according to the McAfee Cloud Adoption and Risk Report. With a 33% increase in users collaborating on this data during the past year, cybercriminals know how to seek more targets:

  • Cloud-native attacks targeting weak APIs or ungoverned API endpoints to gain access to the data in SaaS as well as in PaaS and serverless workloads
  • Expanded reconnaissance and exfiltration of data in cloud databases (PaaS or custom applications deployed in IaaS) expanding the S3 exfiltration vector to structured data in databases or data lakes
  • Leveraging the cloud as a springboard for cloud-native man-in-the-middle attacks (such as GhostWriter, which exploits publicly writable S3 buckets introduced due to customer misconfigurations) to launch cryptojacking or ransomware attacks into other variants of MITM attacks.

Voice-Controlled Digital Assistants the Next Vector in Attacking IoT Devices

As tech fans continue to fill their homes with smart gadgets, from plugs to TVs, coffee makers to refrigerators, and motion sensors to lighting, the means of gaining entry to a home network are growing rapidly, especially given how poorly secured many IoT devices remain.

But the real key to the network door next year will be the voice-controlled digital assistant, a device created in part to manage all the IoT devices within a home. As sales increase—and an explosion in adoption over the holiday season looks likely—the attraction for cybercriminals to use assistants to jump to the really interesting devices on a network will only continue to grow.

For now, the voice assistant market is still taking shape, with many brands still looking to dominate the market, in more ways than one, and it is unclear whether one device will become ubiquitous. If one does take the lead, its security features will quite rightly fall under the microscope of the media, though not perhaps before its privacy concerns have been fully examined in prose.

(Last year we highlighted privacy as the key concern for home IoT devices. Privacy will continue to be a concern, but cybercriminals will put more effort into building botnets, demanding ransoms, and threatening the destruction of property of both homes and businesses).

This opportunity to control a home’s or office’s devices will not go unnoticed by cybercriminals, who will engage in an altogether different type of writing in relation to the market winner, in the form of malicious code designed to attack not only IoT devices but also the digital assistants that are given so much license to talk to them.

Smartphones have already served as the door to a threat. In 2019, they may well become the picklock that opens a much larger door. We have already seen two threats that demonstrate what cybercriminals can do with unprotected devices, in the form of the Mirai botnet, which first struck in 2016, and IoT Reaper, in 2017. These IoT malware appeared in many variants to attack connected devices such as routers, network video recorders, and IP cameras. They expanded their reach by password cracking and exploiting known vulnerabilities to build worldwide robot networks.

Next year we expect to see two main vectors for attacking home IoT devices: routers and smartphones/ tablets. The Mirai botnet demonstrated the lack of security in routers. Infected smartphones, which can already monitor and control home devices, will become one of the top targets of cybercriminals, who will employ current and new techniques to take control.

Malware authors will take advantage of phones and tablets, those already trusted controllers, to try to take over IoT devices by password cracking and exploiting vulnerabilities. These attacks will not appear suspicious because the network traffic comes from a trusted device. The success rate of attacks will increase, and the attack routes will be difficult to identify. An infected smartphone could cause the next example of hijacking the DNS settings on a router. Vulnerabilities in mobile and cloud apps are also ripe for exploitation, with smartphones at the core of the criminals’ strategy.

Infected IoT devices will supply botnets, which can launch DDoS attacks, as well as steal personal data. The more sophisticated IoT malware will exploit voice-controlled digital assistants to hide its suspicious activities from users and home-network security software. Malicious activities such as opening doors and connecting to control servers could be triggered by user voice commands (“Play music” and “What is today’s weather?”). Soon we may hear infected IoT devices themselves exclaiming: “Assistant! Open the back door!”

Cybercriminals to Increase Attacks on Identity Platforms and Edge Devices Under Siege

Large-scale data breaches of identity platforms—which offer centralized secure authentication and authorization of users, devices, and services across IT environments—have been well documented in 2018. Meanwhile, the captured data is being reused to cause further misery for its victims. In 2019, we expect to see large-scale social media platforms implement additional measures to protect customer information. However, as the platforms grow in numbers, we predict criminals will further focus their resources on such attractive, data-rich environments. The struggle between criminals and big-scale platforms will be the next big battleground.

Triton, malware that attacks industrial control systems (ICS), has demonstrated the capabilities of adversaries to remotely target manufacturing environments through their adjacent IT environments. Identity platform and “edge device” breaches will provide the keys to adversaries to launch future remote ICS attacks due to static password use across environments and constrained edge devices, which lack secure system requirements due to design limitations. (An edge device is any network-enabled system hardware or protocol within an IoT product.) We expect multifactor authentication and identity intelligence will become the best methods to provide security in this escalating battle. We also predict identity intelligence will complement multifactor authentication to strengthen the capabilities of identity platforms.

Identity is a fundamental component in securing IoT. In these ecosystems, devices and services must securely identify trusted devices so that they can ignore the rest. The identity model has shifted from user centric in traditional IT systems to machine centric for IoT systems. Unfortunately, due to the integration of operational technology and insecure “edge device” design, the IoT trust model is built on a weak foundation of assumed trust and perimeter-based security.

At Black Hat USA and DEF CON 2018, 30 talks discussed IoT edge device exploitation. That’s a large increase from just 19 talks on the topic in 2017. The increase in interest was primarily in relation to ICS, consumer, medical, and “smart city” verticals. (See Figure 1.) Smart edge devices, combined with high-speed connectivity, are enabling IoT ecosystems, but the rate at which they are advancing is compromising the security of these systems.

Figure 1: The number of conference sessions on the security of IoT devices has increased, matching the growing threat to poorly protected devices. 

Most IoT edge devices provide no self-defense (isolating critical functions, memory protection, firmware protection, least privileges, or security by default) so one successful exploit owns the device. IoT edge devices also suffer from “break once, run everywhere” attacks—due to insecure components used across many device types and verticals. (See articles on WingOS and reverse engineering.)

McAfee Advanced Threat Research team engineers have demonstrated how medical device protocols can be exploited to endanger human life and compromise patients’ privacy due to assumed trust. These examples illustrate just a few of many possible scenarios that lead us to believe adversaries will choose IoT edge devices as the path of least resistance to achieve their objectives. Servers have been hardened over the last decade, but IoT hardware is far behind. By understanding an adversary’s motives and opportunities (attack surface and access capability), we can define a set of security requirements independent of a specific attack vector.

Figure 2 gives a breakdown of the types of vulnerabilities in IoT edge devices, highlighting weak points to address by building identity and integrity capabilities into edge hardware to ensure these devices can deflect attacks.

Figure 2: Insecure protocols are the primary attack surface in IoT edge devices.

IoT security must begin on the edge with a zero-trust model and provide a hardware root of trust as the core building block for protecting against hack and shack attacks and other threats. McAfee predicts an increase in compromises on identity platforms and IoT edge devices in 2019 due to the adoption of smart cities and increased ICS activity.

The post McAfee Labs 2019 Threats Predictions Report appeared first on McAfee Blogs.

Android/TimpDoor Turns Mobile Devices Into Hidden Proxies

The McAfee Mobile Research team recently found an active phishing campaign using text messages (SMS) that tricks users into downloading and installing a fake voice-message app which allows cybercriminals to use infected devices as network proxies without users’ knowledge. If the fake application is installed, a background service starts a Socks proxy that redirects all network traffic from a third-party server via an encrypted connection through a secure shell tunnel—allowing potential access to internal networks and bypassing network security mechanisms such as firewalls and network monitors. McAfee Mobile Security detects this malware as Android/TimpDoor.

Devices running TimpDoor could serve as mobile backdoors for stealthy access to corporate and home networks because the malicious traffic and payload are encrypted. Worse, a network of compromised devices could also be used for more profitable purposes such as sending spam and phishing emails, performing ad click fraud, or launching distributed denial-of-service attacks.

Based on our analysis of 26 malicious APK files found on the main distribution server, the earliest TimpDoor variant has been available since March, with the latest APK from the end of August. According to our telemetry data, these apps have infected at least 5,000 devices. The malicious apps have been distributed via an active phishing campaign via SMS in the United States since at least the end of March. McAfee notified the unwitting hosts of the phishing domains and the malware distribution server; at the time of writing this post we have confirmed that they are no longer active.

Campaign targets North America

Since at least the end of March users in the United States have reported suspicious text messages informing them that they have two voice messages to review and tricking them into clicking a URL to hear them:

Figure 1. User reporting a text that required downloading a fake voice app. Source 800notes.com.

Figure 2. An August 9 text. Source: findwhocallsyou.com.

Figure 3. An August 26 text. Source: 800notes.com.

If the user clicks on one of these links in a mobile device, the browser displays a fake web page that pretends to be from a popular classified advertisement website and asks the user to install an application to listen to the voice messages:

Figure 4. A fake website asking the user to download a voice app.

In addition to the link that provides the malicious APK, the fake site includes detailed instructions on how to disable “Unknown Sources” to install the app that was downloaded outside Google Play.

Fake voice app

When the user clicks on “Download Voice App,” the file VoiceApp.apk is downloaded from a remote server. If the victim follows the instructions, the following screens appear to make the app look legitimate:

Figure 5. Fake voice app initial screens.

The preceding screens are displayed only if the Android version of the infected device is 7.1 or later (API Level 25). If the Android version is earlier, the app skips the initial screens and displays the main fake interface to listen to the “messages”:

Figure 6. The main interface of the fake voice messages app.

Everything on the main screen is fake. The Recents, Saved, and Archive icons have no functionality. The only buttons that work play the fake audio files. The duration of the voice messages does not correspond with the length of the audio files and the phone numbers are fake, present in the resources of the app.

Once the user listens to the fake messages and closes the app, the icon is hidden from the home screen to make it difficult to remove. Meanwhile, it starts a service in the background without user’s knowledge:

Figure 7. Service running in the background.

Socks proxy over SSH

As soon as the service starts, the malware gathers device information: device ID, brand, model, OS version, mobile carrier, connection type, and public/local IP address. To gather the public IP address information, TimpDoor uses a free geolocation service to obtain the data (country, region, city, latitude, longitude, public IP address, and ISP) in JSON format. In case the HTTP request fails, the malware make an HTTP request to the webpage getIP.php of the main control server that provides the value “public_ip.”

Once the device information is collected, TimpDoor starts a secure shell (SSH) connection to the control server to get the assigned remote port by sending the device ID. This port will be later used for remote port forwarding with the compromised device acting as a local Socks proxy server. In addition to starting the proxy server through an SSH tunnel, TimpDoor establishes mechanisms to keep the SSH connection alive such as monitoring changes in the network connectivity and setting up an alarm to constantly check the established SSH tunnel:

Figure 8. An execution thread checking changes in connectivity and making sure the SSH tunnel is running.

To ensure the SSH tunnel is up, TimpDoor executes the method updateStatus, which sends the previously collected device information and local/public IP address data to the control server via SSH.

Mobile malware distribution server

By checking the IP address 199.192.19[.]18, which hosted VoiceApp.apk, we found more APK files in the directory US. This likely stands for United States, considering that the fake phone numbers in the voice app are in the country and the messages are sent from US phone numbers:

Figure 9. APK files in the “US” folder of the main malware distribution server.

According to the “Last modified” dates on the server, the oldest APK in the folder is chainmail.apk (March 12) while the newest is VoiceApp.apk (August 27) suggesting the campaign has run for at least five months and is likely still active.

We can divide the APK files into two groups by size (5.1MB and 3.1MB). The main difference between them is that the oldest use an HTTP proxy (LittleProxy) while the newest (July and August) use a Socks proxy (MicroSocks), which allows the routing of all traffic for any kind of network protocol (not only HTTP)TTp on any port. Other notable differences are the package name, control server URLs, and the value of appVersion in the updateStatus method—ranging from 1.1.0 to 1.4.0.

In addition to the US folder we also found a CA folder, which could stand for Canada.

Figure 10. The “CA” folder on the distribution server.

Checking the files in the CA folder we found that VoiceApp.apk and relevanbest.apk are the same file with appVersion 1.4.0 (Socks proxy server). Octarineiads.apk is version 1.1.0, with an HTTP proxy.

TimpDoor vs MilkyDoor

TimpDoor is not the first malware that turns Android devices into mobile proxies to forward network traffic from a control server using a Socks proxy though an SSH tunnel. In April 2017 researchers discovered MilkyDoor, an apparent successor of DressCode, which was found a year earlier. Both threats were distributed as Trojanized apps in Google Play. DressCode installs only a Socks proxy server on the infected device; MilkyDoor also protects that connection to bypass network security restrictions using remote port forwarding via SSH, just as TimpDoor does. However, there are some relevant differences between TimpDoor and MilkyDoor:

  • Distribution: Instead of being part of a Trojanized app in Google Play, TimpDoor uses a completely fake voice app distributed via text message
  • SSH connection: While MilkyDoor uploads the device and IP address information to a control server to receive the connection details, TimpDoor already has the information in its code. TimpDoor uses the information to get the remote port to perform dynamic port forwarding and to periodically send updated device data.
  • Pure proxy functionality: MilkyDoor was apparently an adware integrator in early versions of the SDK and later added backdoor functionality. TimpDoor’s sole purpose (at least in this campaign) is to keep the SSH tunnel open and the proxy server running in the background without the user’s consent.

MilkyDoor seems to be a more complete SDK, with adware and downloader functionality. TimpDoor has only basic proxy functionality, first using an HTTP proxy and later Socks.

Conclusion

TimpDoor is the latest example of Android malware that turns devices into mobile backdoors—potentially allowing cybercriminals encrypted access to internal networks, which represents a great risk to companies and their systems. The versions found on the distribution server and the simple proxy functionality implemented in them shows that this threat is probably still under development. We expect it will evolve into new variants.

Although this threat has not been seen on Google Play, this SMS phishing campaign distributing TimpDoor shows that cybercriminals are still using traditional phishing techniques to trick users into installing malicious applications.

McAfee Mobile Security detects this threat as Android/TimpDoor. To protect yourselves from this and similar threats, employ security software on your mobile devices and do not install apps from unknown sources.

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‘McAfee Labs Threats Report’ Highlights Cryptojacking, Blockchain, Mobile Security Issues

As we look over some of the key issues from the newly released McAfee Labs Threats Report, we read terms such as voice assistant, blockchain, billing fraud, and cryptojacking. Although voice assistants fall in a different category, the other three are closely linked and driven by the goal of fast, profitable attacks that result in a quick return on a cybercriminal’s investment.

One of the most significant shifts we see is that cryptojacking is still on the rise, while traditional ransomware attacks—aka “shoot and pray they pay”—are decreasing. Ransomware attacks are becoming more targeted as actors conduct their research to pick likely victims, breach their networks, and launch the malware followed by a high-pressure demand to pay the ransom. Although the total number of ransomware samples has fallen for two quarters, one family continues to spawn new variants. The Scarab ransomware family, which entered the threat landscape in June 2017, developed a dozen new variants in Q2. These variants combined make up more than 50% of the total number of Scarab samples to date.

What spiked the movement, starting in fall 2017, toward cryptojacking? The first reason is the value of cryptocurrency. If attacker can steal Bitcoins, for example, from a victim’s system, that’s enough. If direct theft is not possible, why not mine coins using a large number of hijacked systems. There’s no need to pay for hardware, electricity, or CPU cycles; it’s an easy way for criminals to earn money. We once thought that CPUs in routers and video-recording devices were useless for mining, but default or missing passwords wipe away this view. If an attacker can hijack enough systems, mining in high volume can be profitable. Not only individuals struggle with protecting against these attacks; companies suffer from them as well.

Securing cloud environments can be a challenge. Building applications in the cloud with container technology is effective and fast, but we also need to create the right amount of security controls. We have seen breaches in which bad actors uploaded their own containers and added them to a company’s cloud environment—which started to mine cryptocurrency.

New technologies and improvements to current ones are great, but we need to find the balance of securing them appropriately. Who would guess to use an embedded voice assistant to hack a computer? Who looks for potential attack vectors in new technologies and starts a dialog with the industry? One of those is the McAfee Advanced Threat Research team, which provides most of the analysis behind our threats reports. With a mix of the world’s best researchers in their key areas, they take on the challenge of making the (cyber) world safer. From testing vulnerabilities in new technologies to examining malware and the techniques of nation-state campaigns, we responsibly disclose our research to organizations and the industry. We take what we learn from analyzing attacks to evaluate, adapt, and innovate to improve our technology.

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