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Verizon Phone Insurance and Device Protection Plans for Business
We've got some great deals going on right now exclusively for our online customers... chat now to hear more! Rest easy knowing your devices are covered for loss, theft and damage by making the most of this limited-time chance to enroll in one of our phone insurance plans by 4.13.24. Get the protection your business needs, with a range of coverage options to choose from, including a plan that's less than $5/mo per device. Best for businesses that depend on their devices to get the job done. Total Mobile Protection for Business consists of: Wireless Phone Protection, Verizon Extended Warranty and Tech Coach (each available separately). Lost, stolen or damaged device replacements are provided by Wireless Phone Protection, which is insurance coverage underwritten in Georgia by LM General Insurance Company (Boston, MA), in Indiana by Indiana Insurance Company (Boston, MA), in Louisiana by Liberty Personal Insurance Company (Boston, MA), in New Jersey by Liberty Mutual Mid-Atlantic Insurance Company (Boston, MA), and in all other states, Liberty Insurance Underwriters Inc. (Boston, MA) or one of its insurance company affiliates; in Florida, Wireless Phone Protection includes coverage for post-warranty malfunctions (device replacement deductible and claim limit apply). Asurion Insurance Services, Inc. (in California, Agent License #OB35141; in Iowa, Agent license #1001000131), is the Agent and provides the claims servicing under this program. Except in Florida, repairs and replacements for post-warranty malfunctions are provided through the Verizon Extended Warranty program; the obligor of the Extended Warranty program is Verizon Wireless Services, LLC. All Same Day Delivery and Setup services (a benefit of Tech Coach) are subject to the following: available in select locations, which are subject to change at any time, contingent on certain criteria, including customer location, technician availability, and inventory availability. Same Day Delivery and Setup for new devices is only available for devices purchased on verizon.com, if presented as an option at the time of device purchase. Same Day Delivery and Setup for insurance replacements is available for select smartphones with approved claims, with eligibility determined at time of claim approval. Replacement device could be new or refurbished. Select smartphones that only have a cracked front screen are eligible for cracked screen repair (smartphones with damage to the back glass or other damaged components beyond front glass are not eligible for cracked screen repair). Subject to parts availability, in select locations, which are subject to change at any time. Repairs are performed by an Asurion-certified technician and come with a 12-month limited warranty. Eligibility for cracked screen repair will be determined at time of claim approval. Visit phoneclaim.com/verizon to check current device eligibility. This benefit is provided by Wireless Phone Protection. Replacement or repair for post-warranty malfunctions is provided under Verizon Extended Warranty. Repairs are available for select smartphones only, in select locations, subject to parts and technician availability. Eligibility for repair will be determined at the point of Extended Warranty claim. If a repair option is not available for your model smartphone, you will be offered a replacement device, and the Extended Warranty $49 replacement fee will be waived. Verizon Extended Warranty is not available in Florida or for Florida customers. In Florida, extended warranty coverage is provided by the insurance program (device replacement deductible and claim limit apply). The $99 damage deductible will apply for all damage that is ineligible for cracked screen repair. The $99 damage deductible will not apply if your loss and theft deductible is under $99. In such cases, the damage deductible will be the same as your loss and theft deductible. Available in select locations and for select laptops, which are subject to change at any time. Laptop health checkups are limited to diagnostic exams only, and do not include troubleshooting, triage, repair or replacement services. Anti-virus software installation, scanning and virus removal (if applicable) will also be provided. Get live, on-demand access to Tech Coach experts who can help you better utilize your device and connect it to virtually anything else. For businesses that rely on their devices for day-to-day operations. Total Equipment Coverage consists of: Wireless Phone Protection and Verizon Extended Warranty. Lost, stolen or damaged device replacements are provided by Wireless Phone Protection, which is insurance coverage underwritten in Georgia by LM General Insurance Company (Boston, MA), in Indiana by Indiana Insurance Company (Boston, MA), in Louisiana by Liberty Personal Insurance Company (Boston, MA), in New Jersey by Liberty Mutual Mid-Atlantic Insurance Company (Boston, MA), and in all other states, Liberty Insurance Underwriters Inc. (Boston, MA) or one of its insurance company affiliates; in Florida, Wireless Phone Protection includes coverage for post-warranty malfunctions (device replacement deductible and claim limit apply). Asurion Insurance Services, Inc. (in California, Agent License #OB35141; in Iowa, Agent license #1001000131), is the Agent and provides the claims servicing under this program. Except in Florida, repairs and replacements for post-warranty malfunctions are provided through the Verizon Extended Warranty program; the obligor of the Extended Warranty program is Verizon Wireless Services, LLC. Approved claims may be eligible for next day device replacements based on claim approval time, except in Alaska and Hawaii. Customers in AK and HI will receive shipping options at the time of claim approval. Replacement devices may contain original or non-original replacement parts. Colors, features and accessory compatibility are not guaranteed. Claims may be fulfilled with new or refurbished devices of the same model or another model of like kind and quality. Select smartphones that only have a cracked front screen are eligible for cracked screen repair (smartphones with damage to the back glass or other damaged components beyond front glass are not eligible for cracked screen repair). Subject to parts availability, in select locations, which are subject to change at any time. Repairs are performed by an Asurion-certified technician and come with a 12-month limited warranty. Eligibility for cracked screen repair will be determined at time of claim approval. Visit phoneclaim.com/verizon to check current device eligibility. This benefit is provided by Wireless Phone Protection. Replacement or repair for post-warranty malfunctions is provided under Verizon Extended Warranty. Repairs are available for select smartphones only, in select locations, subject to parts and technician availability. Eligibility for repair will be determined at the point of Extended Warranty claim. If a repair option is not available for your model smartphone, you will be offered a replacement device, and the Extended Warranty $49 replacement fee will be waived. Verizon Extended Warranty is not available in Florida or for Florida customers. In Florida, extended warranty coverage is provided by the insurance program (device replacement deductible and claim limit apply). The $99 damage deductible will apply for all damage that is ineligible for cracked screen repair. The $99 damage deductible will not apply if your loss and theft deductible is under $99. In such cases, the damage deductible will be the same as your loss and theft deductible. For businesses that only want coverage for post-warranty malfunctions. Get help fast at an Authorized Repair Facility for battery replacements and other post-warranty malfunctions. Verizon Extended Warranty is a service contract, separate and distinct from any product/service warranty which may be provided by the device manufacturer, and does not extend the term of any such product/service warranty. Replacement or repair for post-warranty malfunctions is provided under Verizon Extended Warranty. Repairs are available for select smartphones only, in select locations, subject to parts and technician availability. Eligibility for repair will be determined at the point of Extended Warranty claim. If a repair option is not available for your model smartphone, you will be offered a replacement device, and the Extended Warranty $49 replacement fee will be waived. Verizon Extended Warranty is not available in Florida or for Florida customers. In Florida, extended warranty coverage is provided by the insurance program (device replacement deductible and claim limit apply). Replacement or repair for post-warranty malfunctions is provided under Verizon Extended Warranty. Repairs are available for select smartphones only, in select locations, subject to parts and technician availability. Eligibility for repair will be determined at the point of Extended Warranty claim. If a repair option is not available for your model smartphone, you will be offered a replacement device, and the Extended Warranty $49 replacement fee will be waived. Verizon Extended Warranty is not available in Florida or for Florida customers. In Florida, extended warranty coverage is provided by the insurance program (device replacement deductible and claim limit apply). Get comprehensive coverage information for customers nationwide and in New York. TechTeam provides 24/7, on-demand access to tech experts who can help you with virtually any software, hardware or cloud issue. Power through your day and worry less about device issues with coverage for loss, theft and damage – even water damage. If you are already a Verizon customer, we have several options to help you get the support you need. Choose your country to view contact details. Existing customers, to your business account or . Verizon device protection options are available for eligible Verizon business wireless lines and devices. You must enroll within 30 days of device activation or during another qualifying event. Certain benefits are available with select plans. Claims limitations, deductibles and terms apply.
Learn more2021 DBIR Results & Analysis
The information provided will be used in accordance with our terms set out in our . Please confirm you have read and understood this Notice. By submitting the form, you are agreeing to receive insights, reports and other information from Verizon and affiliated companies in accordance with our . California residents can view our . Verizon may wish to contact you in the future concerning its products and/or services. If you would like to receive these communications from Verizon, indicate by selecting from the dropdown menu below. Please note that you can unsubscribe or update your preferences at any time. Indicates a required field. The content access link will be emailed to you. You will soon receive an email with a link to confirm your access. When you click to confirm from your email, your document will be available for download. If you do not receive an email within 2 hours, please check your spam folder. You may now close this message and continue to your article. The results found in this and subsequent sections within the report are based on a dataset collected from a variety of sources, including cases provided by the Verizon Threat Research Advisory Center (VTRAC) investigators, reports provided by our external collaborators, and publicly disclosed security incidents. The year-to-year data will have new incident and reach sources as we continue to strive to locate and engage with additional organizations that are willing to share information to improve the diversity and coverage of real-world events. This is a sample of convenience, and changes in contributors—both additions and those who were not able to contribute this year—will influence the dataset. Moreover, potential changes in contributors' areas of focus can shift bias in the sample over time. Still other potential factors, such as how we filter and subset the data, can affect these results. All of this means that we are not always researching and analyzing the same population. However, they are all taken into consideration and acknowledged where necessary within the text to provide appropriate context to the reader. Having said that, the consistency and clarity we see in our data year-to-year gives us confidence that while the details may change, the major trends are sound. We believe it is fair to say that one of the primary lessons that 2020 had to teach us was that it is often futile to attempt to predict the future. However, not trying to predict it is not the same thing as giving up on scenario planning and preparing your organization for probable outcomes to the best of your ability. The DBIR is not in the business of prediction, but it can go a long way to help you shape your response strategy in the face of an uncertain future. Consider Figure 9 for instance; it's your run-of-the-mill DBIR chart with all the slanted bar-charted goodness, courtesy of our Misuse action varieties. We have a few big things up top, and a lot of stuff near the end. One valid way to interpret this is that the top bar or two are the norm of what may happen, namely in this example "Privilege abuse" and "Data mishandling". Those are the Action varieties that are understood to be so common that, if they were to cause a breach, someone (most likely on a bird website) would say, "That organization should have known better.",Suffice it to say, there's a great deal of inequality in the frequencies of the varieties shown. Those small bars are the extraordinary and uncommon attacks that could happen but are unlikely. If they were to cause a breach the victim would claim, "It was an advanced attack. There was nothing that anyone could have done.",However, if you take all those small bars on the Action varieties and add their breach frequencies together, you get Figure 10. Now it doesn't look quite so uncommon anymore, does it? In fact, in this example it appears that a breach is just as likely to be caused by one of our myriad exceptions as it is to be caused by our second most likely Action variety. But does breach data always behave like this? Rather than show you lots of bar charts, we're going to condense that concept down into a single number. Figures 11 and 12 show some data with different levels of inequality. We use the word "inequality" not by chance, but to introduce the fact that we can calculate the Gini coefficient to represent this long tail behavior. The Gini coefficient is a measure of statistical dispersion most commonly used to represent the income or wealth inequality within a nation or other group of people. While it uses a lot of math none of us can be bothered with, it ultimately represents a completely equal outcome, where everyone has the same income (in other words, the "income per person" chart is a horizontal line), as a 0, and a world where one individual has all the income (in other words all we have on the chart is a huge vertical spike somewhere) as a 1. Let's bring this closer to our subject matter by looking at some security related data, like how often your SIEM generates a group of critical alerts that need immediate review. Anecdotally, you could attest that happens exactly "every time you are on-call," but humor us for a moment. In Figure 11, we generated some simulated example data that is perfectly smooth and looks horizontal on the chart—this one has an equality score of 0 (perfectly equal). Figure 12 has actual data representing the time interval between critical SIEM events, and it is extremely spikey. It has a Gini equality score of 0.95, demonstrating a huge variation time between events. It's not just you: critical SIEM events fall into everyone's laps indiscriminately. This complicated mathematical setup is to convey the reality that in the DBIR data (incident and non-incident alike) is very unequal, but at least we can measure it. Figure 13 shows the equality scores for Action, Actor, Asset, and Attribute varieties and vectors over the last seven years. The scores range from about 0.73 to 0.94, or as we would say here, "high." Breach data may seem likely to always be the same, but some varieties are more equal than others. The reality is you don't need a crystal ball, a neural network or next gen AI to tell you what the norm is. You can do that for yourself and plan accordingly. On the other hand, you can't solution your way out of the long tail. It is made up of a legion of little things that happen only rarely—they are the exceptions to the norm. Well, maybe you can if you have enough money. And some organizations that are in critical roles to our society have no choice but to try to do so. But from a purely monetary value, if you look at what breaches cost in the Impacts section, it's not a wise use of your organization's resources to engineer solutions for every single possible exception. Armed with the knowledge of what is the norm and what is the exception, an ideally optimized solution would be to engineer solutions for the norm, and train your security operation teams to handle the exceptions. Turns out humans are very flexible problem-solvers, and most love a good challenge occasionally. The next time we are up against a paradigm-shifting breach that challenges the norm of what is most likely to happen, don't listen to the ornithologists on the blue bird website chirping loudly that "We cannot patch manage or access control our way out of this threat," because in fact "doing the basics" will help against the vast majority of the problem space that is most likely to affect your organization. Read on to learn what the normal actor has been up to for the last year, and pick out the areas where you can improve, against both the norm and the exception. Because the only way to predict the future is to change it yourself. "All the world's a stage," and our threat actors "all have their exits and their entrances." We must admit that they seem to know their cues very precisely. However, at this point the analogy breaks down a bit, as rather than "playing their many parts" we seem to keep viewing the same performance repeated ad infinitum, as if forced to endlessly re-watch a recorded musical theater presentation on a streaming service. It seems clear that our External actors are not giving up their close-ups, as they continue year after year to dominate the Actor types in breaches as illustrated in Figure 14. As a reminder to our readers, the Internal type shown here will include breaches in which both Misuse actions (where the mythical winged internal threats live in our taxonomy) and Error actions (the oopsies) occurred. Of course, an External actor breaking into an organization by leveraging illicitly obtained credentials or other illegal access to pivot internally may initially resemble an internal threat before detailed incident forensics are engaged. But even though the call may be coming from inside the house, there is still a stranger on the line. As in past years, financially motivated attacks continue to be the most common (Figure 15), likewise, actors categorized as Organized crime continue to be number one (Figure 16). However, since 2015 it is relatively common for State-sponsored actors to also crave that cold hard cash as the Financial motives for those actors have fluctuated between 6% and 16% of recorded breaches. Given this result, it should come as no surprise when you glance at Figure 17 and find that the two most common cybercrime terms found on criminal forums are bank account and credit card related. Even as awareness of supply chain attacks has increased over the last few months, the overall percentage of incidents with a Secondary motive—where the ultimate goal of an incident was to leverage the victim's access, infrastructure or any other asset to conduct other incidents—has decreased slightly as a percentage from last year. There are two caveats here that should be kept in mind: The associated growth year-over-year of Financially motivated breaches, and that most Secondary motive breaches reported to us are simple in nature (which suggests the catastrophic ones on everyone's minds are still very much the exception). However, Secondary is still in second place (fittingly enough) as a top Actor motive, as Figure 18 demonstrates. So, if you are a software developer or service provider that has assets that could be repurposed in that manner, please make sure you are paying the proper attention to the operational parts of your organization. In the same way automation may be helping you scale up your defensive operations, it can also help attackers scale up their offense. Figure 19 illustrates the relative occurrence of attack types in honeypot data. Near the top of the attacker's opportunistic sales funnel, we see scanners. Down near the bottom are where the Remote Code Execution (RCE) attacks reside. Regardless of their placement in the figure, automation is likely to assist attackers in moving potential victims from the top of the funnel to the bottom. As such, it's important to limit your public facing attack surface, through asset management, defensive boundaries, and intelligent patching. In the Secondary Motive subset, we had an additional 24,913 incidents of which only one was a known breach. In all of these incidents, web apps were attacked with a secondary motive by External actors. Beyond that, we know very little. Do we have an action-packed section for you, folks! Step right up, make room in the back so everyone can see! Figures 20 and 21 will reveal all you need to know about the frequency of Action varieties for the past year. We do not want to divert all of your attention from the brand-new incident patterns. So we saved additional details on how those Actions manifested in the wild for you to dig your teeth into there. It would be impolite on our part not to address the virulent elephant in the room, so we have centered this initial analysis of Actions on evaluating how adapting to life in a pandemic-stricken world has impacted the threat landscape. The DBIR team released a COVID-19 Threat Landscape Trends article in the middle of last year, and it is only fair that we revisit how our speculations (see how we avoided the word predictions?) fared. Figure 22 shows how the Actions we highlighted in that article varied in relation to last year's report. We highlighted Phishing, Use of stolen creds, Ransomware and Errors as Action varieties that could possibly increase. Even in a year as unexpected as 2020, there are some things we can trust to stay the same. Phishing remains one of the top Action varieties in breaches and has done so for the past two years. Not content to rest on its scaly laurels, however, it has utilized quarantine to pump up its frequency to being present in 36% of breaches, (up from 25% last year). This increase correlates with our expectations given the initial rush in phishing and COVID-19-related phishing lures as the worldwide stay-at-home orders went into effect. Phishing continues to walk hand-in hand with Use of stolen credentials in breaches as it has in the past. Admittedly, we expected to see an increase here due to a larger remote workforce. However, the numbers have remained in the region of 25% of breaches, which is still a significant number. The major change this year with regard to action types was Ransomware coming out like a champ and grabbing third place in breaches (appearing in 10% of them, more than doubling its frequency from last year). This is also something we discussed, but this may have less to do with the changes in working arrangements than it does the shift in tactics of the actors who "named and shamed" their victims. These actors will first exfiltrate the data they encrypt so that they can threaten to reveal it publicly if the victim does not pay the ransom. We are not sure if this breach double-dipping is permitted in the Threat Actor Code of Conduct, but there has been no evidence that they have one anyway. The final piece of this puzzle pertains to Error actions, where we opined that we would see an increase, but actually had a decrease this year to 17% of breaches (from 22%). This breaks a three-year streak of either staying the course or increasing. Granted, the absolute number of Error breaches did increase from 883 to 905. However, as a proportion of the dataset, Error decreased due to the rapid growth of Social breaches. Of course, we here on the team secretly blame each other for this miscalculation on our part, as any team would. Still, both in relative and absolute terms, this is a significant value and is on par with Malware-related breaches as Figure 23 demonstrates, and it should certainly be front and center in your control definition strategy. A data point we started collecting over the past few years pertains to the results of Actions, which provide some interesting insights especially when you consider it as a complement to our ongoing attack chain research. For example, a threat actor might perform a Use of stolen credentials or Phishing action to Infiltrate a victim organization, but then deploy Malware in order to Exfiltrate the data they had their sights on. The heatmap in Figure 24 shows how our most frequent results relate to our top-level Action categories. Points of interest here are how well those findings align with the attack chain information that is present in some of the incidents we analyze. If an Action is concentrated into Infiltrate, it is closer to the top of the first actions in a chain chart, as shown in Figure 25, while Exfiltrate will correlate with the last one. Misuse actions are different, as they often assume or require legitimate access to the Asset that was breached, and, as such, are very focused into Exfiltration. With regard to Malware, well, given the Swiss Army Knife behavior of modern variants, it looks like you can eat your cake and have it too. Another noteworthy change this year is the increase in rank of Desktop sharing as the vector of a Hacking action to second place. As Figure 28 demonstrates, it is completely overshadowed by Web application as the attack vector. But it is now on the 5% threshold and we recommend attention to the authentication security of those. Notably, 89% of the Hacking varieties in this vector involved some sort of credential abuse (Use of stolen creds or Brute force). If, after looking at Figures 27 and 28, you had to double check that you weren't still in 2020, you would be forgiven. Servers are still dominating the Asset landscape due to the prevalence of web apps and mail services involved in incidents. And as social attacks continue to compromise people (they have now pulled past user devices), we begin to see the domination of phishing emails and websites delivering malware used for fraud or espionage. However, we can glimpse the impact of a world where the flickering flames of digital transformation have slowly built into a sizable inferno when we review the Assets involved in breaches. Figure 29 shows that there is a large gap between Person and User devices as the most breached Assets, and the decline of User devices is statistically verifiable in relation to the previous two years. This result makes sense when we consider that breaches are moving toward Social and Webapp vectors, and those are becoming more server based, such as gathering credentials and using them against cloud-based email systems. A related result that will likely not be surprising is that this year, external cloud assets were more common than on-premises assets in both incidents and breaches. Now before you put that in your marketing brochure for your next gen AI cloud security product, there were 10 times as many Unknowns (quite plainly incidents where the information on the location of the assets was not available) as there were cloud assets. That is more than enough to tip the scales in the other direction if we'd known more about what happened. Still, in a sample of random organizations, 17% that had a web presence had internet-facing cloud assets.. If it was not obvious by now, cloud assets deserve a seat at the grown-up security table and a piece of your budget pie. Even the median random organization with an internet presence has 17 internet-facing assets (Figure 30). Figure 30 gives you an idea of how vulnerable those organizations are. Most had no vulnerabilities at all. Furthermore, one might think that more recent vulnerabilities would be more common. However, as we saw last year, it is actually the older vulnerabilities that are leading the way. Rather than selecting out of something like the Alexa top 1 million domains, we randomly sampled a database of hundreds of millions of companies worldwide. Out of a million companies, only 1.4% had a web presence (a domain connected to the organization). It's easy to forget that the average security-conscious organization might be quite different from the average company. These older vulnerabilities are what the attackers continue to exploit. Figure 32 shows the discovery years of vulnerabilities that attackers attempted to exploit in bulk as seen from the perspective of honeypots. If Tom Brokaw were writing this report, he'd call them the greatest generation of vulnerabilities. Eternal Blue is a crowd favorite, which shows that the amount of time since discovery does not really factor into why actors target vulnerabilities. Instead, it seems to be simply a matter of what capabilities exploiting a vuln provides to the attacker, along with the robustness of current working exploits and payloads. So, what's a good, clean-cut, security-conscious organization to do? Based on Figure 33, the patching performance this year in organizations has not been stellar. Granted, it's never been great. There are several likely hypotheses to explain why this year might be underperforming. The ideal state for any organization is to patch smarter, not harder, by using vulnerability prioritization not necessarily to improve security, but to improve the organization's productivity. Every patch that has to be applied means you are that much farther from putting down the keyboard and picking up the d-pad. Anything you can do to avoid patching vulnerabilities that do not improve your security keeps you just as secure but involves much less work (and less chance of burnout from your employees or service providers). Mobile phones made the list in Figure 28 at the beginning of this section. As with last year, this finding is somewhat anticlimactic as the vast majority are simply lost phones. Still, that's not quite the end of our mobile foray. We also have mobile data on malicious URLs and APKs in Figure 34. What we found, in short, was that you don't have to be a large organization to have a good chance that one of your members that received a malicious URL or even installed a malicious APK. The Attributes are the Confidentiality, Integrity and Availability (aka the CIA Triad) violations of the impacted asset. Whether it is a confirmed data breach in which the confidentiality of the data was compromised, or an integrity incident, such as altering the behavior of a person via phishing, the actions against the assets result in CIA violations. First, let's discuss Confidentiality and the types of data that are most frequently compromised. As we have pointed out in previous reports, Credentials remain one of the most sought-after data types (Figure 35). Personal data is a close second. Considering that Personal data includes items such as Social Security numbers, insurance related information, names, addresses, and other readily monetizable data, it is little wonder that attackers favor them as they do. They are also useful for financial fraud further down the line, not to mention their resale value. We do not mean to imply that attackers are the only way data is compromised. Sadly, we cannot discount the ability of our own employees to make mistakes, thereby contributing to the problem. However, they are less likely to involve credentials, and more likely to involve other data such as Personal information, (Figure 36). Moving on to Integrity violations (Figure 37), these are usually the result of a Social or Malware action. For the Social actions, Phishing and Pretexting will alter the behavior of their targeted victim. In some cases, Pretexting results in the initiation of a Fraudulent transaction, causing money to go where it was not supposed to. With the prevalence of Phishing and Pretexting in our dataset this year (43% of breaches) it is no surprise that Alter behavior ranks first among the Integrity violations. But we must not forget the Malware actions. Software installation comes in second place due to the high number of System Intrusion pattern cases that had a Malware component. Most commonly these were directly installed by the actor after system access—usually after a Hacking action such as the Use of stolen creds or Brute force. Finally, we arrive at our Availability violations (Figure 38). The most common is Obscuration, which is what you get when ransomware is installed and the encryption is triggered. Loss is our second most common violation, and results from either a lost or stolen asset, as you no longer have access to that data. This year we decided to take a look at which breach types take the longest to discover (Figure 39). Traditionally, this has been insider Privilege Misuse. However, when looking at this year's data (largely due to the insight provided by the new patterns), we found that the differences between Privilege Misuse and System intrusion were negligible. Both were present in the longest to discover breaches. In contrast, the breaches that are the fastest to discover appear to be those where it becomes readily apparent something is wrong. Examples include Stolen assets, because the employee found evidence of a break-in, and Errors, where the employee had that sinking feeling that they screwed up, and reported it in the hopes that it could be quickly contained. These are both internal methods of discovery, and if you don't already have an easy and fast way for your people to report these kinds of breaches, you should look into it. Why not cultivate your employees to be your early warning system when it can have a great return on investment? The other end of the spectrum for discovery methods is when the threat actor involved makes the "notification" in the form of a ransom note that appears on screen. Finally, we were also curious what kind of data was the fastest to be compromised, and that turns out to be Credentials. This is particularly the case in Phishing, which typically goes after the victim's credentials for use in gaining further access to their chosen victim organization. Attackers continue to profit substantially from the adversity that befalls breach and incident victims. And while that profit is certainly of interest, what really concerns us is how the amounts tally up on the other side of the transaction. Figure 40 illustrates the range of loss from various types of incidents based on adjusted losses reported to the FBI Internet Criminal Complaint Center (IC3). In this figure, each dot represents half a percent of incidents. First and foremost, according to IC3 data, is the fact that whether the attack was a Business Email Compromise (BEC), Computer Data Breach (CDB), or a ransomware attack, a large percentage of incidents did not actually result in a financial loss (42%, 76%, and 90% respectively). When losses did occur, they were not of the one-size-fits-all variety. Following the rules of good business, we expect attackers to charge what the market can bear. For a small organization that is usually a small amount. For a large organization, however, losses can be much more substantial. When examining breaches that included a reported loss, 95% of BECs fell between $250 and $985,000 dollars with $30,000 being the median. That is a pretty big range, you say? Maybe so, but CDB ranges were even wider with 95% falling between $148 and $1.6 million, and a median loss of $30,000. Finally, for ransomware the median amount lost was $11,150, and the range of losses in 95% of the cases fell between $70 and $1.2 million. Let us state this in a somewhat different manner: If you only consider the bottom-half (everything below the medians that we just mentioned), CDBs are often associated with bigger losses than are ransomware events. This finding, when coupled with the 90% of ransomware incidents that did not result in any loss, could be telling the story that organizations are no longer paying the ransoms. It must also be kept in mind that this loss data includes individuals as well as organizations, which is another potential reason for the numbers being smaller. Unfortunately, we do not have a sufficient level of detail to distinguish between the two. There is also the specter of potential bias toward underreporting of larger ransoms. If, however, organizations are skipping the ransom, the low payout ranges could have been yet another contributing factor for the rise of the ransomware "name and shame" threat actors witnessed in late 2019. In a "glass half full" view of the above situation, there is some possible good news in that there is a chance you can reverse the mass migration of your funds to other environs. The IC3 Recovery Asset Team (RAT) can sometimes assist victims in the freezing of lost funds for possible recovery. In Figure 41, we see that when the IC3 RAT acts on BECs, and works with the destination bank, half of all US-based business email compromises had 99% of the money either recovered or frozen, whereas only 11% had nothing at all recovered. If your organization experiences an incident, we highly recommend that you contact the local branch of your national law enforcement and seek their assistance. Or, better yet, get to know them before the breach occurs!,Of course, direct losses are not the sole cost one encounters due to a breach. Apart from the damage done by the attacker, there remains the expense of Digital Forensics and Incident Response (DFIR) and legal counsel. Figure 42 provides an idea of what to expect in these areas based on cyber insurance,It should be pointed out that insurance data can be somewhat biased. For instance, insurance may not cover legal costs or penalties. There may also be an additional deductible not covered in the overall costs. Of course, to address the elephant in the room, it is unlikely that your insurance will cover the damage to your company's reputation. And depending on several factors such as disclosure requirements, the size of the breach, and other things hiding in the fine print, that damage can be considerable. Various studies have arrived at very different conclusions regarding the impact on stock price from a breach in the days immediately following a breach, including 2.53% (Rosati, Cummins, Gogolin, van der Werff, & Lynn, 2017), 5% (Cambell, Gordon, Loeb, & Zhou, 2003), 2.1% (Cavusoglu, Mishra, & Raghunathan, 2004), and 1% (Goel & Shawky, 2009). The findings of these studies are helpful, but they don't shed much light on what happens in the long term. Figure 43 may help to illuminate the matter somewhat. Based on data collected by comparitech.com, breached companies underperformed the NASDAQ (a U.S. Stock Market) by about 5% after six months, though if you look at 95% of companies the performance was anywhere from 48% under to 39% over performing. If we look two years into the future of those organizations (after the breach), those downward trends continued, suggesting that perhaps the breach wasn't actually the cause, but the symptom. To answer the question, "what might a breach cost in total?" we ran 1,000 Monte Carlo simulations using bootstrap sampling on breaches we had cost information about on this year's dataset like the good data nerds we are. Fourteen percent of the simulated breaches had no impact. Of the 86% that were impacted, Table 1 captures the results. What you do with these numbers is, of course, up to you. While you could plan for the median breach of $21,659, a better option might be to plan for the middle 80% of breach impacts, $2,038 to $194,035. Or better yet, be prepared for the most common 95% of impacts, between $826 and $653,587. If you add to that an organizational devaluation of around 5% (from Figure 43), then you just may have yourself a tangible figure you can plan around. 1 - Simulated Breach Costs,Over the past decade, the cyber threat has grown exponentially with nation state and cyber criminals increasing the scale, scope, and level of sophistication of their cyber attacks. Addressing this kind of complex and agile environment requires a more comprehensive response than any one single government agency, business, technology, or data source can provide. Instead, an interwoven architecture of combined capabilities from across public agencies and the private sector must be leveraged to protect critical infrastructure and impose risk and consequences on attackers. The FBI is committed to sharing as much as possible about cyber threats as quickly as possible so the public is alerted and prepared. We strive to be viewed as an indispensable partner, using our unique authorities as a law enforcement agency and member of the United States Intelligence Community to enable government operations against our cyber adversaries and allow the public to enhance their security posture. Because of our unique authorities, world-class capabilities, enduring partnerships, and presence we can conduct investigations, collect intelligence, and interact with victims – all in pursuit of attribution. Attribution is what allows the U.S. government to impose risk and consequences on our adversaries and prioritize our operations with our partners, including the private sector. Cyber [Combatting cyber crime] is the ultimate team sport and we all must be committed to using every tool we have at our disposal to address the cyber threat. Of utmost importance to the FBI, and a key component of our foundational cyber strategy, is the ability to share relevant and actionable information with our government partners, the international community, private industry, and the public. But, we also rely on the information received from our partners, private industry, and victims to develop a broader picture of cyber threats. The Internet Crime Complaint Center (IC3) serves as a reliable, convenient, tool for submitting information to the FBI about suspected internet-facilitated criminal activity, while also developing effective partnerships with law enforcement and private sector entities. Information provided to the IC3 is further analyzed, resulting in investigative leads or the identification of new or emerging cyber threats. We share what we've learned through our analysis of IC3 data with the public and private industry through PSAs, alerts and reports such as the DBIR. For the 2021 DBIR, the FBI's IC3 focused on supplying data specifically for business email compromises/ email compromises (BEC/EAC), and other data breach incidents reported to IC3. In recent years, the FBI's IC3 has observed that BEC/EAC and data breach incidents trend more towards victimizing corporations and/or private sector entities and less on targeting a single individual. IC3 recognizes that the public plays a central role in IC3 being able to understand how cyber criminals are evolving. By submitting a cyber related complaint, the public is assisting the FBI in addressing those specific complaints, as well as, identifying the critical details of developing cyber threat trends. Convenience sampling is a type of nonrandom sampling that involves the sample being drawn from that part of the population that is close at hand or available. More details can be found in our "Methodology" section. Though we do suggest you put your money on Trail Blazer in the third. Where are my insider threat fans at? Whoop whoop!,This report makes no claim about the validity of such a statement. Please refer to our official spokesperson and legal counsel. The data privacy of our readers is of the utmost importance to us. And completely obliterate our page count budget. A less well-known fact is that the wish for wealth redistribution led to the term Gini in a bottle. Not really, but it would have been cool if it did. A technical term of art in Data Science, we assure you. We deeply apologize to the junior U.S. senator from Vermont for the fact that the top 3% of varieties are responsible for 87% of the breaches. You're reading the DBIR, and that is a great step in the right direction, if we may say so. This argument does not consider potential incidents where loss of life or the security of individuals is concerned, as it would make no sense to assign a monetary value to that, and would, in fact, be callous and cruel. As You Like It, William Shakespeare. Anyone know if the Cyber+ trademark is available?,Or the hot ethereal cryptocurrency. Viruphant? Eleplent?Just like your Momma said. Mmm…cake. Emphasis on the "Artificial" not on "Intelligence.",See the sidebar for what we mean by 'random organizations.,A terrible "pie in the sky" joke was edited out here. You are welcome!,You know, because of patching. Just don't call them "boomer vulnerabilities," or you will start a fight. They might even tell you to get off their lawn. As we write this section, a Microsoft Exchange Remote Code Execution Vulnerability (CVE-2021-26855) is being actively and massively exploited that has all the ingredients to also be part of this growing background noise of exploitation activity in the internet. 2017 DBIR, Figure 56. Or your kid, or your running shoes, or something else that keeps you sane. Android apps. Observant readers may have noticed the assets section missing anything about Information Technology (IT) vs. Operational Technology (OT) assets. That's because it was largely missing from our dataset as well. We've heard those OT breaches are somewhere, but they're not in our dataset. Not the CIA that keeps the alien presence on the DL, the other kind. It would be fascinating to analyze profitability of different types of attacks from the perspective of the threat actors, but not only do we not believe we have the data necessary; we are not sure if this analysis would benefit the threat actors more than the defenders. For an additional fee, the Verizon will provide a version of the DBIR that replaces all instances of Cyber with Security. See your local Verizon representative for details. Another elephant? This is a pachyderm-filled space!,More precisely, Paul Bischoff's (@pabischoff) blog post at,Dr. Frank N. Furter nods approvingly. If you are already a Verizon customer, we have several options to help you get the support you need. Choose your country to view contact details. Existing customers, to your business account or . 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Learn moreDBIR Report 2022 - Appendices Business
The information provided will be used in accordance with our terms set out in our . Please confirm you have read and understood this Notice. By submitting the form, you are agreeing to receive insights, reports and other information from Verizon and affiliated companies in accordance with our . California residents can view our . Verizon may wish to contact you in the future concerning its products and/or services. If you would like to receive these communications from Verizon, indicate by selecting from the dropdown menu below. Please note that you can unsubscribe or update your preferences at any time. Indicates a required field. The content access link will be emailed to you. You will soon receive an email with a link to confirm your access, or follow the link below. You may now close this message and continue to your article. Knowing our readership cares about such things and consumes this information with a keen eye helps keep us honest. Detailing our methods is an important part of that honesty. First, we make mistakes. A column transposed here; a number not updated there. We're likely to discover a few things to fix. When we do, we'll list them on our corrections page: . Second, we check our work. The same way the data behind the DBIR figures can be found in our GitHub repository, as with last year, we're also publishing our fact check report there as well. It's highly technical, but for those interested, we've attempted to test every fact in the report. Third, science comes in two flavors: creative exploration and causal hypothesis testing. The DBIR is squarely in the former. While we may not be perfect, we believe we provide the best obtainable version of the truth, (to a given level of confidence and under the influence of biases acknowledged below). However, proving causality is best left to randomized control trials. The best we can do is correlation. And while correlation is not causation, they are often related to some extent, and often useful. We would like to reiterate that we make no claim that the findings of this report are representative of all data breaches in all organizations at all times. Even though we believe the combined records from all our contributors more closely reflect reality than any of them in isolation, it is still a sample. And although we believe many of the findings presented in this report to be appropriate for generalization (and our conviction in this grows as we gather more data and compare it to that of others), bias exists. Our overall process remains intact and largely unchanged from previous years. All incidents included in this report were reviewed and converted (if necessary) into the VERIS framework to create a common, anonymous aggregate data set. If you are unfamiliar with the VERIS framework, it is short for Vocabulary for Event Recording and Incident Sharing, it is free to use, and links to VERIS resources are at the beginning of this report. The collection method and conversion techniques differed between contributors. In general, three basic methods (expounded below) were used to accomplish this:,All contributors received instruction to omit any information that might identify organizations or individuals involved. Our data is non-exclusively multinomial, meaning a single feature, such as "Action," can have multiple values (i.e. "social," "malware" and "hacking"). This means that percentages do not necessarily add up to 100%. For example, if there are 5 botnet breaches, the sample size is 5. However, since each botnet used phishing, installed keyloggers, and used stolen credentials, there would be 5 social actions, 5 hacking actions, and 5 malware actions, adding up to 300%. This is normal, expected, and handled correctly in our analysis and tooling. Another important point is that when looking at the findings, "unknown" is equivalent to "unmeasured". Which is to say that if a record (or collection of records) contains elements that have been marked as "unknown" (whether it is something as basic as the number of records involved in the incident, or as complex as what specific capabilities a piece of malware contained) it means that we cannot make statements about that particular element as it stands in the record—we cannot measure where we have too little information. Because they are 'unmeasured', they are not counted in sample sizes. The enumeration "Other" is counted, however, as it means the value was known but not part of VERIS (or not one of the other bars if found in a bar chart). Finally, "Not Applicable" (normally "NA") may be counted or not counted depending on the claim being analyzed. This year we have again made liberal use of confidence intervals to allow us to analyze smaller sample sizes. We have adopted a few rules to help minimize bias in reading such data. Here we define 'small sample' as less than 30 samples. For a potential entry to be eligible for the incident/breach corpus, a couple of requirements must be met. The entry must be a confirmed security incident defined as a loss of Confidentiality, Integrity, or Availability. In addition to meeting the baseline definition of "security incident" the entry is assessed for quality. We create a subset of incidents (more on subsets later) that pass our quality filter. The details of what makes a "quality" incident are:,In addition to having the level of details necessary to pass the quality filter, the incident must be within the timeframe of analysis, (November 1, 2020 to October 31, 2021 for this report). The 2021 caseload is the primary analytical focus of the report, but the entire range of data is referenced throughout, notably in trending graphs. We also exclude incidents and breaches affecting individuals that cannot be tied to an organizational attribute loss. If your friend's laptop was hit with Emotet it would not be included in this report. Lastly, for something to be eligible for inclusion into the DBIR, we have to know about it, which brings us to several potential biases we will discuss next. Many breaches go unreported (though our sample does contain many of those). Many more are as yet unknown by the victim (and thereby unknown to us). Therefore, until we (or someone) can conduct an exhaustive census of every breach that happens in the entire world each year (our study population), we must use sampling. Unfortunately, this process introduces bias. The first type of bias is random bias introduced by sampling. This year, our maximum confidence is +/- 0.7% for incidents and +/- 1.4% for breaches, which is related to our sample size. Any subset with a smaller sample size is going to have a wider confidence margin. We've expressed this confidence in the complementary cumulative density (slanted) bar charts, hypothetical outcome plot (spaghetti) line charts, quantile dot plots and pictograms. The second source of bias is sampling bias. We strive for "the best obtainable version of the truth" by collecting breaches from a wide variety of contributors. Still, it is clear that we conduct biased sampling. For instance, some breaches, such as those publicly disclosed, are more likely to enter our corpus, while others, such as classified breaches, are less likely. The below four figures are an attempt to visualize potential sampling bias. Each radial axis is a VERIS enumeration and we have stacked bar charts representing our data contributors. Ideally, we want the distribution of sources to be roughly equal on the stacked bar charts along all axes. Axes represented by only a single source are more likely to be biased. However, contributions are inherently thick tailed, with a few contributors providing a lot of data and a lot of contributors providing a few records within a certain area. Still, we mostly see that most axes have multiple large contributors with small contributors adding appreciably to the total incidents along that axis. You'll notice a rather large contribution on many of the axes. While we'd generally be concerned about this, they represent contributions aggregating several other sources, so not actual single contributions. It also occurs along most axes, limiting the bias introduced by that grouping of indirect contributors. The third source of bias is confirmation bias. Because we use our entire dataset for exploratory analysis, we cannot test specific hypotheses. Until we develop a collection method for data breaches beyond a sample of convenience this is probably the best that can be done. As stated above, we attempt to mitigate these biases by collecting data from diverse contributors. We follow a consistent multiple-review process and when we hear hooves, we think horse, not zebra. We also try to review findings with subject matter experts in the specific areas ahead of release. We already mentioned the subset of incidents that passed our quality requirements, but as part of our analysis there are other instances where we define subsets of data. These subsets consist of legitimate incidents that would eclipse smaller trends if left in. These are removed and analyzed separately, though they may not be written about if no relevant findings were, well, found. This year we have two subsets of legitimate incidents that are not analyzed as part of the overall corpus:,Both subsets were separated out the last five years as well. Finally, we create some subsets to help further our analysis. In particular, a single subset is used for all analysis within the DBIR unless otherwise stated. It includes only quality incidents as described above and excludes the two aforementioned subsets. Since the 2015 issue, the DBIR includes data that requires analysis that did not fit into our usual categories of "incident" or "breach." Examples of non-incident data include malware, patching, phishing, DDoS, and other types of data. The sample sizes for non-incident data tend to be much larger than the incident data, but from fewer sources. We make every effort to normalize the data, (for example weighting records by the number contributed from the organization so all organizations are represented equally). We also attempt to combine multiple partners with similar data to conduct the analysis wherever possible. Once analysis is complete, we try to discuss our findings with the relevant partner or partners so as to validate it against their knowledge of the data. While the DBIR is celebrating its 15th birthday, VERIS (the data standard underlying the DBIR) is creeping up to the ripe old age of 12. The standard was born out of necessity as a means of cataloging in a repeatable manner the key components of an incident. This enables analysis of what happened, who was impacted and how it occurred. Since then it has grown and matured into a standard that can be adopted by many different types of stakeholders. VERIS is tailored to be a standard that provides not only ease of communication, but also a connection point to other industry standards and best practices, such as the Center for Internet Security (CIS) and MITRE Adversary Tactics, Techniques & Common Knowledge (ATT&CK). We realize that there isn't going to be one universal framework (or language or well, anything) to rule them all, but we certainly believe in the importance of peaceful co-existence between all the frameworks that have enabled the growth of this community. Below are some of the great projects and connection points that exist with VERIS and it is our hope that the standard will bring more players to the cybersecurity table. The CIS Critical Security Controls (CIS CSC) are a community-built, prioritized list of cybersecurity best practices that help organizations of different maturity levels protect themselves against threats. The CIS CSC aligns well with VERIS, as the DBIR is built to help organizations catalogue and assess cybersecurity incidents. This mapping connects the dots between the bad things that are happening and things that can help protect the organizations. Since 2019 we've published a mapping document that can help organizations crosswalk the patterns that are most concerning to them with the Safeguards that can protect them from the attacks within those patterns. Within each industry section, organizations can find the Implementation Group 1 set of controls, as the starting point for all organizations regardless of capability, based on the top patterns for that industry. MITRE's (ATT&CK) has become one of the defining ways of capturing technical tactical information in terms of what attackers do as part of their attack process. This rich dataset not only includes the specific techniques, but also the software, groups and mitigations associated with each technique, and as of earlier this year, the associated VERIS components. To assist organizations with translating the technical tactical information into strategic insights, Verizon collaborated with partners at the Center for Threat Informed Defense (CTID) and created the official VERIS to ATT&CK mapping, available free of charge to anyone with an internet connection. The mapping data is represented in Structured Threat Information eXpression (STIX) format, includes tools and scripts to update the mapping and also has a visualization layer that can be imported into ATT&CK Navigator. By providing this mapping, we hope that the various stakeholders of the organization can communicate and share their needs in a consistent fashion. One thing you may notice in the DBIR is that outside of a few small areas such as the Timeline section, we do not discuss the path the attack takes. This is because non-atomic data (like paths and graphs of actions) is really hard, for us and the rest of the information security ecosystem. Whether it's describing breaches, writing signatures, creating repeatable pen tests or control validations, or communicating to leadership, attack paths and graphs are difficult to create, share, and analyze. The DBIR team, with MITRE CTID and its participants, hope to change that with the Attack Flow project. Att&ck Flow is a data schema for capturing both the causal path of an attack as well as the contextual data around it as it "flows". Because breaches fan out and then come back together, go down a path and come back to a server, Attack Flow supports arbitrary graphs of actions and assets interacting. Because we all need to know different things about the attack, it uses a knowledge graph structure to capture the context of the flow. And because we all organize differently, it supports multiple namespaces. So, for example, you could use VERIS Actions, Mitre ATT&CK actions, organization specific actions, or even a combination of all of the above as part of your attack path analysis. With Att&ck Flow, we now have a format we can use to share non-atomic data. Digital Forensics and Incident Response (DFIR) folks could document an incident as a flow. Detection vendors could use it to create a signature. Control validation tools can use it to simulate the incident. The Security Engineering team can use it to build attack surface graphs and plan mitigations. And they all can use the structure to create communications to leadership, and all be able to share the same underlying data with each other in a standardized but flexible structure. If that sounds like something you could get behind, check out the MITRE project at and the DBIR team's graph based tools for working with it at . In 2021 we reported that the human element impacted 85% of breaches, which decreased slightly to 82% this year. Unfortunately, strong asset management and a stellar vulnerability scanner aren't going to solve this one. Instead, you're going to need to change the behavior of humans, and that is quite an undertaking. Regardless of how you plan on doing it (be it giving them a reason to change, providing training or a combination of the two), you will need a way to tell if it worked, and that normally means running a test. Here's a cheat-sheet of things that your internal department or vendor who is responsible for conducting the training should provide to you so you can determine if it is paying off:,This test may be something run specifically for you or a test the trainer already ran. As long as the population, outcome, etc. are close to yours, it doesn't matter. The manner in which the results are reported is just as important as how the testing was conducted. Here are a few things you should expect in the results:,Unfortunately, there's no way to guarantee something works. But, if you're getting the information above (Population, Outcome, Intervention, Control, Random, Conditions) and (Results, When, Dropout, Qualitative) you can be reasonably confident you're getting something for your effort. So, remember those easy acronyms: POICRC and RWDQ!The ways in which we live, work, and interact with each other has changed dramatically the last few years. The increased use of Internet platforms during the COVID-19 pandemic clearly demonstrates our growing economic dependence on information technology, and with that increased risk of cybercrime. Transnational cyber criminals continue to expand their capabilities, and their ability to cause harm—regardless of if they are financially or politically motivated. In terms of criminal activity, 2021 experienced a growth in crimes involving cryptocurrencies. This includes digital extortion schemes (including ransomware), theft of credentials or private keys that control substantial value in digital assets, manipulation of decentralized finance (DeFi) systems, and new money laundering methods that enable a wide variety of illicit activity. Transnational criminals are increasingly using cryptocurrency and other digital assets, rather than traditional physical assets or the intermediated financial system. Cryptocurrencies even found their way into Superbowl advertisements. What was once a niche market is now a growing part of modern life – investing, trading, and for illicit activity as well. Since its creation in 1865, the U.S. Secret Service has continuously evolved its investigative strategies and methods to protect our nation's financial system. We are no longer chasing counterfeiters on horseback but are now focused on preventing cyber fraud by identifying and arresting cybercriminals worldwide. In 2010, when the Secret Service first joined in developing the DBIR, the foremost risk we were seeing was the theft of payment card and PII data for use in fraud. As this year's report shows that risk is still present, but we are seeing development of new schemes by those who illicitly exploit the Internet. To keep pace with evolving criminal activity, the U.S. Secret Service focuses on partnering to enable businesses and law enforcement to take effective actions to mitigate risk. The DBIR is a key part of this—providing recommendations derived from analysis of aggregated incident reports. We also aid our partners and prevent cyber incidents through the work of our Cyber Fraud Task Forces, and the over 3,000 state, local tribal and territorial (SLTT) law enforcement personnel we trained at the National Computer Forensics Institute (NCFI) in FY 2021. We coordinate these activities globally through a dedicated group of investigators in our Global Investigative Operations Center (GIOC) focused on achieving the most effective outcomes—from recovering and returning stolen assets to victims to apprehending those responsible. This past year clearly demonstrated the increasing impact ransomware is having on businesses, critical infrastructure, and national security. The most prolific ransomware networks are Russian-speaking, though this crime is not limited to one country or region. According to one industry estimate, 74% of ransomware payments were Russian affiliated. We have also seen the use of destructive malware, which is functionally similar to ransomware, but lacks a means for payment. This dynamic, coupled with the limited cooperation of some states in countering ransomware, illustrates a growing risk which blurs distinctions politically and financially motivated cybercrimes. This risk reinforces why partnership is essential in improving cybersecurity by both improving the resilience of computer systems and apprehending the threat actors. Despite transnational cybercrime being a daunting challenge, the U.S. Secret Service relentlessly pursues these cases. In 2021, the Secret Service led or participated numerous multi-national operations to counter cyber criminal networks. For example, we conducted a multinational operation with Dutch Police and Europol to arrest multiple individuals responsible for ransomware attacks affecting over 1,800 victims in 71 countries. In total, Secret Service responded to over 700 network intrusions and prevented over $2.3 billion in cyber financial losses last fiscal year. Identity theft and fraud continues to be a core activity of transnational cyber criminals—it provides a means to convert stolen personally identifiable information into profit. The COVID-19 pandemic created new opportunities for this sort of fraud, as criminals defrauded relief programs. In response, the U.S. Secret Service named a National Pandemic Fraud Recovery Coordinator to focus on partnering with financial institutions to prevent and recover fraudulent payments. These efforts resulted in the U.S. Secret Service recovering more than $1.2 billion, the return of more than $2.3 billion of fraudulently obtained funds, and over 100 arrests. As the world becomes more digitized, in addition to being connected to each other through technology, we are connected to a wide array of devices, such as the internet of things (IoT). Other emerging technologies that may soon be the targets of cybercriminals include quantum cryptography, 5G wireless technology and Artificial Intelligence (AI). These technologies have the potential to improve lives and open new lines of communication. Conversely, cybercriminals will seek ways to use these technologies for malicious gains. The U.S. Secret Service, while focused on thwarting criminal activity today, has already started to train and prepare for the cybercrimes of the future. Preventing cybercrime requires a multi-pronged strategy including increasing cybersecurity resilience and pursuing criminals and seizing illicit gains to deter and prevent future crimes. Both of these efforts are strengthened by the analysis of aggregated incident reports, and evidence-based recommendations the DBIR provides. In 2022, the U.S. Secret Service looks forward to further strengthening our partnerships, to stay ahead of our changing use of technology, the efforts of criminals to exploit it, and ensure there is no safe place for cyber criminals to hide. Assistant Director U.S. Secret ServiceThe U.S. Secret Service, while focused on thwarting criminal activity today, has alreadyTo that end, we have combined the value chain targeting and distribution data, phishing test success rate data, criminal forum data, and ransomware payment data to estimate what the business looks like from the criminal's side. First, let's examine the cost of access. Figure 121 illustrates the cost of hiring (criminal) professional services to do the actor's dirty work. These (and larger criminal organizations with internal staff for access) are likely going for riskier, bigger payout attacks. The small-time criminal is less of a techie and more of a manager. They are trying to minimize costs so will not invest in professional services. Instead, they buy access products outright in the form of credentials, emails for phishing, vulnerabilities, or botnet access. Figure 122 gives an idea of the costs. Instead of $100,000, the majority of access doesn't even cost a dollar. This is because most access is email which is incredibly cheap, even when the median click rate is only 2.9%. While purchasing access directly in the form of access to a bot, login credentials, or knowledge of a vulnerability are also included, it's email that steers the ship. Contrast Figure 122 with the profits in Figure 123. Sixty percent of ransomware incidents had no profit and aren't shown in the figure. A large portion had a profit near one dollar. However, the median is just over $100. Figure 124 shows what those same profits look like over time. After 300 simulated ransoms the actor has over $600,000 in income. To see if this was an anomaly, we simulated 500 ransomware actors and 1.4% of them showed a loss. However, the median profit after 300 incidents was $178,465, with the top simulated earner making $3,572,211. The takeaway is that ransomware is more of a lottery than a business. You gamble on access, win the lottery 40% of the time, and get a payout from a few bucks to thousands of dollars. But for something more actionable, focus on the access. If an actor has to pay for services to break in rather than just an access product, you've made yourself much less of a target. Use antivirus to remove bots, implement patching, filtering, and asset management to prevent exposed vulnerabilities and standardize two-factor authentication and password managers to minimize credential exposure. Lastly, with email being the largest vector, you can't ignore the human element. Start with email and web filtering followed by training. (See the Changing Behavior Appendix for a recommendation on how to tell if your training is working.),Akamai Technologies Ankura Anomali Apura Cybersecurity Intelligence AttackIQ Atos,Bad Packets Bit-x-bit BitSight BlackBerry Cylance,Center for Internet Security CERT Division of Carnegie CERT European Union Checkpoint Software Technologies Ltd. Chubb Coalition Computer Incident Response Center Luxembourg (CIRCL) Coveware CrowdStrike Cybersixgil Cybercrime Support Network Cybersecurity and Infrastructure Security Agency (CISA) CyberSecurity Malaysia, an agency under the Ministry of Communications and Multimedia (KKMM) Cybir (formerly DFDR Forensics),Defense Counterintelligence Security Agency (DCSA) Dell Digital Shadows Domain Tools (formerly Farsight Security) Dragos, Inc DomainTools (formerly Farsight Security),EASE (Energy Analytic Security Exchange) Edgescan Elevate Security Emergence Insurance EUROCONTROL,Domain Tools (formerly Farsight Security) Financial Services ISAC (FS-ISAC) Federal Bureau of Investigation - Internet Crime Complaint Center (FBI IC3) Fortinet,Global Resilience Federation Grey Noise,HackedEDU Hasso-Plattner Institut,Irish Reporting and Information Security Service (IRISS-CERT),Jamf JPCERT/CC,K-12 SIX—(K-12 Security Information Exchange) Kaspersky KnowBe4 Kordamentha,Lares Consulting Legal Services - ISAO LMG Security Lookout,Malicious Streams Maritime Transportation System ISAC (MTS-ISAC) Micro Focus mnemonic,NetDiligence® NETSCOUT NINJIO Cybersecurity Awareness Training,Palo Alto Networks ParaFlare Pty Ltd Proofpoint PSafe,Qualys,Ransomwhere Recorded Future,S21sec SecurityTrails Shadowserver Foundation Shodan SISAP - Sistemas Aplicativos Swisscom,U.S. Secret Service,VERIS Community Database Verizon Cyber Risk Programs Verizon DDoS Shield Verizon Mobile Security Dashboard Verizon Network Operations and Engineering Verizon Professional Services Verizon Sheriff Team Verizon Threat Intelligence Platform Verizon Threat Research Advisory Center (VTRAC) Vestige Digital Investigations,WatchGuard Technologies,ZscalerAs does this sentence. A unique finding is more likely to be something mundane such as a data collection issue than an unexpected result. Often referred to as the Rumsfeld paradox. We assume tax-free. I suppose not everyone can be good at business. Even criminals. If you are already a Verizon customer, we have several options to help you get the support you need. Choose your country to view contact details. Existing customers, to your business account or . These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work. These cookies do not store any personally identifiable information. 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