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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.
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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
This section was updated on December 11th.
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 abstraction in application development, by leveraging Functions as a Service (FaaS) for their computation requirements. Functions are billed only while they are executing, including sub-second billing (AWS Lambda charges per 100ms). Paying only for executing business logic, as opposed to running a full container or a virtual machine, 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. Achieving least privilege is more difficult with more components to protect, contain, and update. 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. Because serverless apps naturally scale and bill based on traffic, distributed denial of service attacks can more easily translate directly to the bottom line, depending on the number of simultaneous executions allowed by the application.
Another risk is data that may be leveraged by multiple functions to process a business transaction. Because a serverless application may include more components than prior application architectures, the data may be at more risk of interception or manipulation. Comprehensive and ubiquitous use of authentication and authorization between services and encryption of data both at rest and in transit should be leveraged.
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
- Jonathan King
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.
To learn more about our predictions for 2018, register for our January 9th webcast.
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