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 […]

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

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.

‘McAfee Labs 2018 Threats Predictions Report’ Previews Five Cybersecurity Trends

This report was written by members of McAfee Labs and the Office of the CTO.
Welcome to the McAfee Labs 2018 Threats Predictions Report. We find ourselves in a highly volatile stage of cybersecurity, with new devices, new risks, and new threats appeari…

This report was written by members of McAfee Labs and the Office of the CTO.

Welcome to the McAfee Labs 2018 Threats Predictions Report. We find ourselves in a highly volatile stage of cybersecurity, with new devices, new risks, and new threats appearing every day. In this edition, we have polled thought leaders from McAfee Labs and the Office of the CTO. They offer their views on a wide range of threats, including machine learning, ransomware, serverless apps, and privacy issues.

The Adversarial Machine Learning Arms Race Revs Up
The rapid growth and damaging effects of new cyberthreats demand defenses that can detect new threats at machine speeds, increasing the emphasis on machine learning as a valuable security component. Unfortunately, machines will work for anyone, fueling an arms race in machine-supported actions from defenders and attackers. Human-machine teaming has tremendous potential to swing the advantage back to the defenders, and our job during the next few years is to make that happen. To do that, we will have to protect machine detection and correction models from disruption, while continuing to advance our defensive capabilities faster than our adversaries can ramp up their attacks.

Ransomware Pivots to New Targets, New Objectives
The profitability of traditional ransomware campaigns will decline as vendor defenses, user education, and industry strategies improve to counter them. Attackers will target less traditional, more profitable ransomware targets, including high net-worth individuals, connected devices, and businesses. This pivot from the traditional will see ransomware technologies applied beyond the objective of extorting individuals, to cyber sabotage and disruption of organizations. The drive among adversaries for greater damage, disruption, and the threat of greater financial impact will not only spawn new variations of cybercrime “business models,” but also begin to seriously drive the expansion of the cyber insurance market.

Serverless Apps: New Opportunities for Friend and Foe
Serverless apps can save time and reduce costs, but they can also increase the attack surface by introducing privilege escalation, application dependencies, and the vulnerable transfer of data across networks. Serverless apps enable greater granularity, such as faster billing for services. But they are vulnerable to attacks exploiting privilege escalation and application dependencies. They are also vulnerable to attacks on data in transit across a network. Function development and deployment processes must include the necessary security processes, and traffic that is appropriately protected by VPNs or encryption.

When Your Home Becomes the Ultimate Storefront
As connected devices fill your house, companies will have powerful incentives to observe what you are doing in your home, and probably learn more than you want to share. In 2018, McAfee predicts more examples of corporations exploring new ways to capture that data. They will consider the fines of getting caught to be the cost of doing business, and change the terms and conditions on your product or service to cover their lapses and liabilities. It is more difficult to protect yourself from these issues, and the next year will see a significant increase in breaches and discoveries of corporate malfeasance.

Inside Your Child’s Digital Backpack
Perhaps the most vulnerable in this changing world are our children. Although they face an amazing future of gadgets, services, and experiences, they also face tremendous risks to their privacy. We need to teach them how to pack their digital backpacks so that they can make the most of this future. The world is becoming very public, and though many of us seem to be OK with that, the consequences of an ill-considered post or thoughtless online activity can be life altering for years to come.

The Adversarial Machine Learning Arms Race Revs Up

Attackers and defenders work to out-innovate each other in AI

Human-machine teaming is becoming an essential part of cybersecurity, augmenting human judgment and decision making with machine speed and pattern recognition. Machine learning is already making significant contributions to security, helping to detect and correct vulnerabilities, identify suspicious behavior, and contain zero-day attacks.

During the next year, we predict an arms race. Adversaries will increase their use of machine learning to create attacks, experiment with combinations of machine learning and artificial intelligence (AI), and expand their efforts to discover and disrupt the machine learning models used by defenders. At some point during the year, we expect that researchers will reverse engineer an attack and show that it was driven by some form of machine learning. We already see black-box attacks that search for vulnerabilities and do not follow any previous model, making them difficult to detect. Attackers will increase their use of these tools, combining them in novel ways with each other and with their attack methods. Machine learning could help improve their social engineering—making phishing attacks more difficult to recognize—by harvesting and synthesizing more data than a human can. Or increase the effectiveness of using weak or stolen credentials on the growing number of connected devices. Or help attackers scan for vulnerabilities, boosting the speed of attacks and shortening the time from discovery to exploitation.

Whenever defenders come out with something new, the attackers try to learn as much about it as possible. Adversaries have been doing this for years with malware signatures and reputation systems, for example, and we expect them to do the same with the machine learning models. This will be a combination of probing from the outside to map the model, reading published research and public domain material, or trying to exploit an insider. The goal is evasion or poisoning. Once attackers think they have a reasonable recreation of a model, they will work to get past it, or to damage the model so that either their malware gets through or nothing gets through and the model is worthless.

On the defenders’ side, we will also combine machine learning, AI, and game theory to probe for vulnerabilities in both our software and the systems we protect, to plug holes before criminals can exploit them. Think of this as the next step beyond penetration testing, using the vast capacity and unique insights of machines to seek bugs and other exploitable weaknesses.

Because adversaries will attack the models, defenders will respond with layers of models—operating independently—at the endpoint, in the cloud, and in the data center. Each model has access to different inputs and is trained on different data sets, providing overlapping protections. Speaking of data, one of the biggest challenges in creating machine learning models is gathering data that is relevant and representative of the rapidly changing malware environment. We expect to see more progress in this area in the coming year, as researchers gain more experience with data sets and learn the effects of old or bad data, resulting in improved training methods and sensitivity testing.

The machines are rising. They will work with whoever feeds them data, connectivity, and electricity. Our job is to advance their capabilities faster than the attackers, and to protect our models from discovery and disruption. Working together, human-machine teaming shows great potential to swing the advantage back to the defenders.

Ransomware Pivots to New Targets, New Objectives

Swings from the traditional to new targets, technologies, tactics, and business models

McAfee sees an evolution in the nature and application of ransomware, one that we expect to continue through 2018 and beyond.

The good news about traditional ransomware. McAfee Labs saw total ransomware grow 56% over the past four quarters, but evidence from McAfee Advanced Threat Research indicates that the number of ransomware payments has declined over the last year.

Our researchers assert that the trend suggests a greater degree of success during the last 12 months by improved system backup efforts, free decryption tools, greater user and organizational awareness, and the collaborative actions of industry alliances such as NoMoreRansom.org and the Cyber Threat Alliance.

How cybercriminals are adjusting. These successes are forcing attackers to pivot to high-value ransomware targets, such as victims with the capacity to pay greater sums, and new devices lacking comparable vendor, industry, and educational action.

Targeting higher net-worth victims will continue the trend toward attacks that are more personal, using more sophisticated exploitation of social engineering techniques that deliver ransomware via spear phishing messages. These high-value targets will be attacked at their high-value endpoints, such as their increasingly expensive personal devices, including the latest generation of smart phones. Cloud backups on these devices have made them relatively free from traditional ransomware attacks. McAfee predicts that attackers will instead try to “brick” the phones, making them unusable unless a ransom payment is sent to restore them.

McAfee believes this pivot from the traditional is reflected in the slight decline in the number of overall ransomware families, as criminals shift to a smaller number of higher-value technologies and tactics, more talented purveyors of techniques, and more specialized, more capable ransomware-as-a-service providers.

New ransomware families discovered in 2017. On average, 20%‒30% per month of new samples are based on Hidden Tear ransomware code. Source: McAfee Labs.

The less sophisticated, mostly well-known, mostly predictable, one-to-many technology, tactics, and providers are simply failing to deliver the rewards to justify the investments, even modest ones.

If well-understood ransomware families survive and thrive, McAfee believes they will do so in the hands of trusted service providers that continue to establish themselves with more established, sophisticated backends, as is currently the case with the Locky family.

Where the digital impacts the physical. Every year, we read predictions about threats to our physical safety from security breaches of industrial systems in transportation, water, and power. We are also perennially entertained with creative depictions of physical threats brought about by the imminent hacking rampage of consumer devices, from the car to the coffeemaker.

McAfee resists the temptation to join the cybersecurity-vendor chorus line to warn you of the danger that lurks within your vacuum cleaner. But our researchers do foresee digital attacks impacting the physical world. Cybercriminals have an incentive to place ransomware on connected devices providing a high-value service or function to high-value individuals and organizations.

Rather than seize control of your grandmother’s automobile brakes as she drives along a winding mountain road, our researchers believe it more likely and more profitable for cybercriminals to apply ransomware to an important business executive’s car, preventing them from driving to work. We believe it more likely and more profitable for cybercriminals to place ransomware on a wealthy family’s thermostat in the dead of winter, than to set the homes of millions ablaze through their coffeemakers.

In these and other ways, we believe cybercriminals will see greater return in orchestrating digital attacks that physically impact individuals for profit, rather than fatal damage.

Beyond extortion to disruption and destruction. The WannaCry and NotPetya ransomware outbreaks foreshadow a trend of ransomware being applied in new ways, in pursuit of new objectives, becoming less about traditional ransomware extortion and more about outright system sabotage, disruption, and damage.

The WannaCry and NotPetya campaigns quickly infected large numbers of systems with ransomware, but without the payment or decryption capabilities necessary to unlock impacted systems. Although the exact objectives are still unclear, McAfee believes the attackers could have sought to blatantly disrupt or destroy huge networks of computers, or disrupt and distract IT security teams from identifying other attacks, in much the same way DDoS attacks have been used to obscure other real aspects of attacks. It is also possible that they represented spectacular proofs of concept, demonstrating their disruptive and destructive power, intending to engage large organizations with mega-extortion demands in the future.

In 2018, McAfee expects to see ransomware used in the manner of WannaCry and NotPetya. Ransomware-as-a-service providers will make such attacks available to countries, corporations, and other nonstate actors seeking to paralyze national, political, and business rivals in much the same way that NotPetya attackers knocked global IT systems out of commission at corporations around the world. We expect an increase in attacks intended to cause damage, whether by unscrupulous competitors or by criminals trying to mimic a mafia-style protection racket in cyber form.

Although this weaponization of ransomware at first seems to stretch the definition of the technology and tactical concept, consider the incentive of avoiding a WannaCry or NotPetya specific to your organization, complete with rapid, wormlike propagation and a demonstration of material disruption and damage, but with a demand for payment to make it all stop.

Of course, this raises the biggest, unavoidable ransomware question of 2017: Were WannaCry and NotPetya actually ransomware campaigns that failed in their objectives to make significant revenue? Or perhaps incredibly successful wiper campaigns?

Finally, McAfee predicts that these shifts in the nature and objectives of ransomware attacks, and their potential for real material financial impacts, will create an opportunity for insurance companies to extend their digital offerings with a range of ransomware insurance.

Serverless Apps: New Opportunities for Friend and Foe

Serverless apps attempt to match the security of a container or virtual machine

“Serverless” apps, the latest aspect of virtual computing, enable a new degree of granularity in computing functions. Some providers have recently reduced the billing iteration to seconds, which will have a substantial impact on growth. Billing for functions in seconds, instead of using containers or virtual machines that require minutes or hours, can reduce costs by a factor of 10 for some operations.

But what about the security of these function calls? They are vulnerable in traditional ways, such as privilege escalation and application dependencies, but also in new ways, such as traffic in transit and an increased attack surface.

Let’s start with the traditional vulnerabilities. Serverless apps that are quickly implemented or rapidly deployed can use an inappropriate privilege level, leaving the environment open to a privilege escalation attack. Similarly, the speed of deployment can result in a function depending on packages pulled from external repositories that are not under the organization’s control and have not been properly evaluated.

Then there are the new risks. By looking at the URL, we can tell if the request is going to a serverless environment. As a result, it might be possible for an attacker to disrupt or disable the infrastructure from the outside, affecting a large number of organizations.

Another risk is the data included in the function call. Because the data is not on the same server that executes the function, it must transit some network and may be at risk of interception or manipulation.

We predict the increased granularity of serverless apps will lead to a comparable increase in the attack surface. More functions, transiting to one or more providers, means more area for an attacker to exploit or disrupt. Make sure your function development and deployment process includes the necessary security steps, and that traffic is appropriately protected by VPNs or encryption.

When Your Home Becomes the Ultimate Storefront

Without controls, you might surrender your privacy to corporate marketers

Corporate marketers have powerful incentives to observe and understand the buying needs and preferences of connected home device owners. Networked devices already transmit a significant amount of information without the knowledge of the overwhelming majority of consumers. Customers rarely read privacy agreements, and, knowing this, corporations are likely to be tempted to frequently change them after the devices and services are deployed to capture more information and monetize it.

In 2018, connected home device manufacturers and service providers will seek to overcome thin operating margins by gathering more of our personal data—with or without our agreement—as we practically surrender the home to become a corporate virtual store front.

With such dynamics in play, and with the technical capabilities already available to device makers, corporations could offer discounts on devices and services in return for the ability to monitor consumer behavior at the most personal level.

Rooms, devices, and apps are easily equipped with sensors and controls capable enough to inform corporate partners of the condition of home appliances, and bombard consumers with special upgrade and replacement offers.

It is already possible for children’s toys to monitor their behavior and suggest new toys and games for them, including upgrades for brand-name content subscriptions and online educational programs.

It is already possible for car manufacturers and their service centers to know the location of specific cars, and coordinate with owners calendars and personal assistants to manage and assist in the planning of their commutes. Coffee, food, and shopping stops could automatically be integrated into their schedules, based on their preferences and special offers from favorite food and beverage brands.

Whether this strikes you as a utopia for consumers and marketers, or a dystopian nightmare for privacy advocates, many aspects of these scenarios are close to reality.

Data collection from the current wide range of consumer devices and services is running far ahead of what most people believe.

Although there is certainly a legal argument that consumers have agreed to the collection of their data, even those of us technically knowledgeable to know this is taking place do not read the contracts that we agree to, and some corporations might change them after the fact or go beyond what they promise.

We have seen numerous examples of corporate malfeasance in recent years. A flashlight app developer’s license agreement did not disclose that the app gathered geolocation data. Three years ago, a video game hardware company pushed an update with no option to refuse; users had to agree to new terms or stop using the product they had purchased. In many agreements, users “agree” to all future changes that the company makes unilaterally to the terms: “Continued use of the service after any such changes shall constitute your consent to such changes.”

In July, the US Federal Bureau of Investigation warned parents to be wary of connected children’s toys that could be capable of collecting their children’s personally identifiable information.

Businesses will continue to seek to understand what and how consumers consume in the privacy of their homes, certainly requiring more user data than consumers will likely be comfortable sharing. McAfee asserts that a substantial number of corporations will break privacy laws, pay fines, and still continue such practices, thinking they can do so profitably. But the FBI’s recent toy warning to parents might suggest that such approaches could result in regulatory and even criminal legal consequences.

Next year will provide new examples of how well, and how badly, corporations are able to navigate the temptations and opportunities presented by connected homes.

We thank the Electronic Frontier Foundation for their assistance with this article.

Inside Your Child’s Digital Backpack

Protecting your children from corporate abuse of their user-generated content

It seems that every product, service, or experience we interact with today creates some type of digital record, whether or not we like it. As adults, we are gradually coming to terms with this effect and learning to manage our digital lives, but what about our children? Employers are already making hiring decisions influenced by search results. Could this extend to schools, health care, and governments? Will children be denied entry to a school because of how much time they spent binge-watching videos, or find it difficult to run for office because of a video made when they were seven?

Online information, or digital baggage, can be positive, negative, or neutral. As our children go on their increasingly digital journey through life, what are they packing for their trip? Likely, it will be a combination of mostly innocuous and trivial things, some positive and amazing ones that will help them on their journey, and some negative items that could weigh them down. Unfortunately, we predict that many future adults will suffer from negative digital baggage, even if it comes about without their intention.

As parents, our challenge is to help our children navigate this new world, in which they can be tracked almost from the moment of conception. Remember that story from 2012 about a girl who received coupons from a retailer for pregnancy-related items before she acknowledged that she was pregnant?

To help our children, we need to understand the kinds of digital artifacts that are being captured and stored. There are generally three types: explicit, implicit, and inadvertent.

Explicit content is all of those things that happen after you click the “I Agree” button on the terms and conditions or end user license agreement. Given recent breaches, it seems that anything stored online will at some point be hacked, so why not assume that from the beginning? If they really want to, a prospective employer may be able to find out what content you created, your social habits, and a host of other data points. This is an area that parents (at least initially) have a lot of control and influence over, and can teach and model good habits. Are you buying “M”-rated games for your 10-year-old, or letting your teens post videos without some oversight? Sadly, what happens online is not private, and there could eventually be consequences.

Implicit content is anything you do or say in an otherwise public place, which could be photographed, recorded, or somehow documented. This ranges from acting silly to drinking or taking drugs, but also includes what people say, post, tweet, etc. in public or online. We do not think that childlike behavior (by children) is going to be frequently or successfully used against people in the future, so we can still let our kids be kids.

Inadvertent content is the danger area. These are items that were intended to remain private, or were never expected to be captured. Unfortunately, inadvertent content is becoming increasingly common, as organizations of all types (accidentally or on purpose) bend and break their own privacy agreements in a quest to capture more about us. Whether with a toy, a tablet, a TV, a home speaker, or some other device, someone is capturing your child’s words and actions and sending them to the cloud. This is the most challenging part of the digital journey, and one that we must manage vigilantly. Pay attention to what you buy and install, turn off unnecessary features, and change the default passwords to something much stronger!

Our children face an amazing potential future, full of wonderful gadgets, supportive services, and amazing experiences. Let’s teach them at home to pack their digital backpacks so that they can make the most of it.

In the corporate world, McAfee predicts that the May 2018 implementation of the European Union’s General Data Protection Regulation (GDPR) could play an important role in setting ground rules on the handling of both consumer data and user-generated content in the years to come. The new regulatory regime impacts companies that either have a business presence in EU countries, or process the personal data of EU residents, meaning that companies from around the world will be compelled to adjust the way in which they process, store, and protect customers’ personal data. Forward-looking businesses can leverage this to set best practices that benefit customers using consumer appliances, content-generating app platforms, and the online cloud-based services behind them.

In this regard, the year 2018 may well best be remembered for whether consumers truly have the right to be forgotten.

To find out more about the data protection opportunity for businesses, visit McAfee’s GDPR site.

For more on how to protect your children from potential user-generated content abuse and other digital threats, please see McAfee’s blogs for guidance on parenting in the digital age.

Contributors

  • Christiaan Beek
  • Lisa Depew
  • Magi Diego
  • Daren Dunkel
  • Celeste Fralick
  • Paula Greve
  • Lynda Grindstaff
  • Steve Grobman
  • Kenneth Howard
  • Abhishek Karnik
  • Sherin Mathews
  • Jesse Michael
  • Raj Samani
  • Mickey Shkatov
  • Dan Sommer
  • Vincent Weafer
  • Eric Wuehler

 

About McAfee Labs

McAfee Labs is one of the world’s leading sources for threat research, threat intelligence, and cybersecurity thought leadership. With data from millions of sensors across key threats vectors—file, web, message, and network—McAfee Labs delivers real-time threat intelligence, critical analysis, and expert thinking to improve protection and reduce risks.

The post ‘McAfee Labs 2018 Threats Predictions Report’ Previews Five Cybersecurity Trends appeared first on McAfee Blogs.

McAfee Labs: Faceliker Surge Manipulates Facebook “Likes” to Promote News, Other Content

Criminals excel in manipulating the trust within human relationships, particularly as individuals project themselves into digital realms such as social media. We see it in phishing messages, which fool us into clicking on a malicious weblink from what …

Criminals excel in manipulating the trust within human relationships, particularly as individuals project themselves into digital realms such as social media. We see it in phishing messages, which fool us into clicking on a malicious weblink from what appears to be a benign organization with which we do business. We also see it in the much discussed area of “fake news” on social networks, where readers are likely to take news reports “liked” by friends as legitimate news stories. Much has been written about how “fake news” is promoted by bots and other amplification services, and how such promotion may have had an impact on recent elections.

The McAfee Labs Threats Report: September 2017, released today, identifies a notable surge in similar activity by the Faceliker malware. This Trojan manipulates Facebook accounts clicks to artificially “like” certain content. Faceliker accounted for about 8.9% of the 52 million new malware samples detected in the quarter. It was a key driver in the 67% overall growth for the category during the period.

Faceliker is not the fault of Facebook. Rather, it is something users bring to Facebook.

Faceliker infects users’ browsers when they visit malicious or compromised websites. It then hijacks their Facebook account clicks in such a way that users think they are liking one thing, but the malware is redirecting the click. It acts on their behalf to click another “like” button without their knowledge or consent, essentially making each user an accomplice in the click fraud scheme.

Users aren’t negatively impacted by the Trojan, but they do appear to over-like certain content, skewing like-ratings through fraudulent inflation. The actors behind malware such as Faceliker sell their services to the actors behind the content.

Suspicious users can remove unrecognized likes by surveying their record of behavior in their activity log. To its credit, Facebook has put up defenses that detect fraudulent likes and ask a user to confirm that they intended to click as their browser appeared to click.

McAfee Labs Vice President Vincent Weafer has commented that as long as there is profit in such efforts, we should expect to see more such schemes in the future.

“Faceliker leverages and manipulates the social media and app-based communications we increasingly use today,” Weafer said. “By making apps or news articles appear more popular, accepted, and legitimate among friends, unknown actors can covertly influence the way we perceive value and even truth.”

Please see more threat statistics and trends analysis in this quarter’s report and follow us on Twitter at @McAfee_Labs.

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New Variant of Petya Ransomware Spreading Like Wildfire

The world woke up today to another ransomware outbreak wreaking havoc throughout companies’ networks. This time, the family causing the fuss is Ransomware Petya, a nasty variant that encrypts files and the computer’s master boot record (MBR), rende…

The world woke up today to another ransomware outbreak wreaking havoc throughout companies’ networks. This time, the family causing the fuss is Ransomware Petya, a nasty variant that encrypts files and the computer’s master boot record (MBR), rendering the machine unusable.

Ransomware Petya has been around since at least March 2016 and differs from usual ransomware families because it encrypts a system’s MBR in addition to encrypting files. This double stroke renders the disk inaccessible and prevents most users from recovering anything on it.

The new variant found today has further increased its nastiness by adding a spreading mechanism similar to what we saw in WannaCry just a few weeks ago. Petya comes as a Windows DLL with only one unnamed export, and uses the same Eternal Blue exploit when it attempts to infect remote machines, as we can see below:

In the preceding image we can see the typical transaction occurring right before the exploit is sent—as we discussed in our WannaCry blog.

Once the exploit succeeds, the malware copies itself to the remote machine under C:\Windows, and starts itself using rundll32.exe. The process is executed under lsass.exe, the Windows process injected by the Eternal Blue exploit.

Because the WannaCry outbreak caused many people to apply all the latest Windows patches, Petya introduces a few more spreading mechanisms to be more successful. The next method Petya attempts is to copy itself and a copy of psexec.exe to the remote machine’s ADMIN$ folder. If it is successful, the malware attempts to start psexec.exe using a remote call to run it as a service, as we can see below:

The preceding image first shows the DLL being copied to the remote host. And the following image shows psexec being copied and then attempting to start it using the svcctl remote procedure call.

Both files are copied to the C:\Windows folder.

One last method attempted by the malware is to use the Windows Management Instrumentation Command-line (WMIC) to execute the sample directly on the remote machine, using stolen credentials. The command used by the malware looks like this:

  • exe %s /node:”%ws” /user:”%ws” /password:”%ws” process call create “C:\Windows\System32\rundll32.exe \”C:\Windows\%s\” #1

where “%ws” is a variable representing a wide string, which will be generated based on the current machine and credential being exploited.

Once the malware runs on the machine, it will drop psexec.exe to the local system as c:\windows\dllhost.dat, and another .EXE (either 32- or 64-bit version depending on the operating system) to the %TEMP% folder. This binary is a modified version of a password dump tool, similar to Mimikatz or LSADump.

The preceding code shows the LSA functions used during password extraction.

This .EXE accepts as parameter a PIPE name similar to the following:

  • \\.\pipe\{df458642-df8b-4131-b02d-32064a2f4c19}

This pipe is used by the malware to receive the stolen passwords, which are then used by the WMIC shown above.

All these files are present in the resource section of the main DLL in a compressed form, as follows:

The malware then encrypts local files and the MBR, and installs a scheduled task to reboot the machine after one hour using schtasks.exe, as seen below:

The encryption used by the malware is AES-128 with RSA. This is different from previous variants, which used SALSA20. The RSA public key used to encrypt the file encryption keys is hardcoded and can be seen below:

The malware also attempts to clear Event logs to hide its traces, by executing the following commands:

  • wevtutil cl Setup & wevtutil cl System & wevtutil cl Security & wevtutil cl Application & fsutil usn deletejournal /D %c:

After the machine is rebooted, the ransom message appears and demands US$300 in Bitcoins:

At this moment there are few transactions to this account, but this could change quickly once more people start to notice they are infected:

We will update this blog as more information arrives. For now, McAfee product users with McAfee ENS 10.5 and WSS should be protected from known samples if their products are up to date and by McAfee Global Threat Intelligence. (This Knowledge Center article has more information.) McAfee ATP detects both the main DLL as well as the dropped EXE, as seen below:

Detection for the main DLL is shown above, and for the sample dropped in %TEMP% is shown below:

Indicators of compromise

Known hashes

  • 027cc450ef5f8c5f653329641ec1fed91f694e0d229928963b30f6b0d7d3a745 (main 32-bit DLL)
  • 64b0b58a2c030c77fdb2b537b2fcc4af432bc55ffb36599a31d418c7c69e94b1 (main 32-bit DLL)
  • f8dbabdfa03068130c277ce49c60e35c029ff29d9e3c74c362521f3fb02670d5 (signed PSEXEC.EXE)
  • 02ef73bd2458627ed7b397ec26ee2de2e92c71a0e7588f78734761d8edbdcd9f (64-bit EXE)
  • eae9771e2eeb7ea3c6059485da39e77b8c0c369232f01334954fbac1c186c998 (32-bit EXE)

Files

  • c:\windows\dllhost.dat
  • c:\windows\<malware_dll> (no extension)
  • %TEMP%\<random name>.tmp (EXE drop)

Other indicators

  • PIPE name: \\.\pipe\{df458642-df8b-4131-b02d-32064a2f4c19}
  • Scheduled task running “shutdown -r -n”

 

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