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2021 DBIR Results & Analysis
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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 2023 - Appendix 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. One of the things readers value most about this report is the level of rigor and integrity we employ when collecting, analyzing and presenting data. 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 not 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 must 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 dataset. 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. Some source spreadsheets are converted to our standard spreadsheet formatted through automated mapping to ensure consistent conversion. Reviewed spreadsheets and VERIS Webapp JavaScript Object Notation (JSON) are ingested by an automated workflow that converts the incidents and breaches within into the VERIS JSON format as necessary, adds missing enumerations and then validates the record against business logic and the VERIS schema. The automated workflow subsets the data and analyzes the results. Based on the results of this exploratory analysis, the validation logs from the workflow and discussions with the partners providing the data, the data is cleaned and reanalyzed. This process runs nightly for roughly two months as data is collected and analyzed. 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 five botnet breaches, the sample size is five. However, since each botnet used phishing, installed keyloggers and used stolen credentials, there would be five Social actions, five Hacking actions and five 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," however, is counted 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 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 is 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, 2021, to October 31, 2022, for this report). The 2022 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 Trickbot, 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 below. 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 and quantile dot plots. 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 four figures below 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 only represented by 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 those axes. You'll notice rather large contributions on many of the axes. While we'd generally be concerned about this, they represent contributions aggregating several other sources, 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 horses, not zebras. 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 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 the last six 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 aforementioned two subsets. Since the 2015 issue, the DBIR includes data that requires the analysis that did not fit into our usual categories of "incident" or "breach." Examples of non-incident data include malware, patching, phishing and DDoS. 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. When it comes to sailing the stormy seas of the cybersecurity world, a map comes in handy to help you chart your direction. We consider the DBIR to be one of those maps, helping organizations navigate the complicated and ever-changing conditions of the cybersecurity landscape. To make sure this map is the most accurate possible, we have created the VERIS Framework, which captures most of the important components of data breaches in order to facilitate risk-oriented decision making for our weary cyber mariners. Over the years, new guiding frameworks have been created that provide different levels of detail, MITRE ATT&CK® being by far the most popular. We have worked with MITRE Engenuity and the Center for Threat Informed Defense to capture the relationships between VERIS to ATT&CK so that organizations can leverage the benefits of both in their navigation. The results of that work are remarkable: ATT&CK provides excellent tactical and technical details into the specific techniques the threat actors leverage, while VERIS provides a strategic view of the landscape, covering a wider range of possible mishaps. Errors, for instance, are present in 9% percent of breaches this year but are out of scope in ATT&CK. When VERIS and ATT&CK are combined, they provide you with a clearer view of what type of assets were impacted and what type of victims those assets belonged to while still preserving the specifics of the attack techniques that were leveraged. This combination of forces is timely due to the increased regulatory pressure of reporting data breaches to governments, although there is no commonly accepted format in how this reporting should be done. We, of course, cannot opine on the need for such regulations, but we would like to do our part to make sure that organizations have the right tooling to reduce their burden as new laws come to fruition. The second version of this mapping has just been released as of April 6, 2023, and we are very excited about it. In addition to VERIS Actions, a lot of thought was put into mapping Attributes. To make it better, Actors were mapped to ATT&CK Groups. There are also new mappings to ATT&CK for Mobile and ATT&CK for ICS. If this interests you at all, please hop over to for all the details of the work. Even if it doesn't, you are already reaping the benefits of the work thanks to the ATT&CK Technique mappings we have added to some select Incident Patterns to help you in your epic journey to "full control coverage.",Our team puts a lot of thought and energy into trying to make the VERIS Framework more accessible and helpful for all. If you are curious about the framework or have tried it in the past and want to check what's new, get in touch with the DBIR team at . It's hard to believe that the Verizon Threat Research Advisory Center (VTRAC) is 20 years old! I've had the unique pleasure of being part of the team since the very beginning—or should I say the "zero-day"?,Over those 20 years, we've had a few different names but always the same passionate team behind the scenes. Back then, I was part of a small gaggle of geeks in New York City, always having a suitcase packed and ready to hop a flight to anywhere to take on the next big data breach investigation. Our forensic lab at the time was a collection of systems that didn't even fill a single full-height server rack. It bears reminding that, 20 years ago, "cybersecurity" was not a commonly used or understood word. If you asked the average person what "cyber" was, you would probably get back responses that sounded like something from a science fiction movie. There was no such thing as a cybersecurity college degree—the closest thing that existed at the time was a computer science or engineering degree. Today, there are hundreds of universities around the world that not only offer cybersecurity bachelor's degrees, but also master's degrees and Ph.D.s. I can still remember some of the first data breaches I ever investigated. Old timers will appreciate the days when we showed up onsite with our "medical bag"—typically a bag that had a binder of bootable floppy disks, a collection of assorted cables, and a variety of hard drives and enclosures. As mentioned above, hardly anyone knew what cybersecurity was back then, and the average person had no idea of the purpose of the equipment in that medical bag. In a world just following 9/11, going through airport security with that bag of odd-looking electronics and cables guaranteed that I was frequently the lucky winner of "random" extra screening. If only that luck carried over into a few of the trips to Vegas …,Today, we rarely need to travel. We have enterprise tools that can facilitate remote forensic evidence collection from anywhere in the world. Taking advantage of our telecommunications backbone and advances in cellular connectivity, we're even able to provide immediate emergency and out-of-band communications via 5G, allowing us to collect forensic data at speeds in excess of 1 Gbps, even if the victim organization has its own network, systems or infrastructure outages. The then and now comparisons over the last 20 years are staggering to consider. Today, we have exponentially more people on our team, with incredible diversity of backgrounds and geographic locations. The VTRAC supports organizations across more than 100 countries. We not only have several physical lab locations around the world but also cloud-based and client on-premises lab locations to care for nearly every conceivable data privacy and sovereignty concern. Of course, I cannot forget to mention the incredible work of the DBIR team that makes this very publication possible. Many have heard me say that the DBIR is my third child. It was born 16 years ago as part of an early incarnation of VTRAC (back then we were called the RISK Team) with a vision of sharing our data breach insights with the world. Metaphorically, I heard it say its first words and watched it take its first steps alongside the other co-creators. Thankfully, I don't have to save for the DBIR's college tuition. I couldn't be prouder of what the past and present members of the VTRAC have built and accomplished over the past 20 years. It is the passion and dedication of each and every team member that contributes to our long client tenure, never having missed a contractual service level agreement, world-class thought leadership and consistent rating as a leader by industry analysts. I look forward to the adventures, innovation and excitement to come in our next 20 years!,Happy 20th birthday, VTRAC!,—Chris Novak Akamai Technologies,Ankura,Apura Cyber IntelligenceBit-x-bit,Bit Sight,BlackBerryCensys, Inc. Center for Internet Security,Cequence Security,CERT Division of Carnegie Mellon University's Software Engineering Institute,CERT – European Union,CERT Polska,Check Point Software Technologies Ltd. Chubb,Coalition,Computer Incident Response Center Luxembourg (CIRCL),Coveware,CrowdStrike,Cybersecurity and Infrastructure Security Agency (CISA),CyberSecurity Malaysia, an agency under the Ministry of Communications and Multimedia (KKMM),Cybersixgill,CYBIRDell,Department of Government Services, Victorian State Government, Australia,DomainTools Energy Analytic Security Exchange (EASE),Edgescan,Elevate Security,Emergence Insurance,EUROCONTROL,EvidenFederal Bureau of Investigation – Internet Crime Complaint Center (FBI IC3),FortinetGlobal Resilience Federation,GreyNoiseHackEDUIrish Reporting and Information Security Service (IRISS-CERT),IvantiJPCERT/CCK-12 Security Information Exchange (K-12 SIX),Kaspersky,KordaMenthaLegal Services Information Sharing and Analysis Organization (LS- (ISAO)Malicious Streams,Maritime Transportation System ISAC (MTS-ISAC),mnemonicNetDiligence®,NETSCOUTOkta,OpenText CybersecurityPalo Alto Networks,ProofpointS21 Sec,SecurityTrails, a Recorded Future Company,Shadowserver Foundation,SISAP – Sistemas Aplicativos,Shodan,SwisscomU.S. Secret ServiceVERIS Community Database,Verizon Cyber Risk Programs,Verizon Cyber Security Consulting,Verizon DDoS Defense,Verizon Network Operations and Engineering,Verizon Threat Research Advisory Center (VTRAC),Vestige Digital InvestigationsWatchGuard Technologies, Inc. As does this sentence,A unique finding is more likely to be something mundane, such as a data collection issue, than an unexpected result. Who are we kidding? We would love to have more data to analyze!How dare you?,Editor's note: We hope the DBIR is actually helping you pay for tuition for your human children. 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. These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. We use both third party and first party cookies for this purpose. All information these cookies collect is aggregated and therefore anonymous. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance. These cookies enable the website to provide enhanced functionality and personalisation. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly. These cookies may be set through our site by Verizon and third parties. They are used to present Verizon advertising on third party sites that you may visit. They do not store directly personal information, but are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising from Verizon. BackClear Filters,All Consent Allowed
Learn moreTop Cybersecurity Threats for June 2023 Business
We've got some great deals going on right now exclusively for our online customers... chat now to hear more! Author: Phil Muncaster,On the third Wednesday of every month, the Verizon Threat Research Advisory Center (VTRAC) holds its Monthly Intelligence Briefing (MIB) to discuss the current cybersecurity landscape and provide the latest threat intelligence. Below is the summary of their most recent briefing and here is the . 1. Verizon 2023 Data Breach Investigation Report (DBIR) reveals developments in the current threat landscape,2. MOVEit flaw exploited by Clop ransomware group in large supply chain attack,3. Barracuda zero-day bug exploited by Chinese state-linked threat actor,If you'd like to receive new articles, solutions briefs, whitepapers and more—just let us know. The has been released. This year's report provides detailed insight into the threat landscape, gleaned from 16,312 incidents, of which 5,199 (32%) were confirmed data breaches. It found that external (83%) and financially motivated (95%) breaches were most common, thanks to the dominant role of organized crime. Insiders accounted for a fifth (19%), although this includes negligence as well as malicious activity. The human factor accounted for 74% of breaches. That's not surprising considering (49%) and (12%) were the top two techniques for gaining entry into networks, followed by vulnerability exploitation (5%). Among social engineering, business email compromise (BEC), or , is now present in more incidents than phishing. As stated on page 31 of the 2023 DBIR, cases doubled over the past year, with the . (24%) recorded its highest-ever share of breaches, and continues to impact organizations of all sizes and in all industries. Infamous ransomware group Clop exploited in popular managed file transfer software MOVEit to steal data from countless MOVEit customers. The group is currently adding victim names to its leak site as the data for ransom payment expired. It has claimed hundreds of victims, while VTRAC has counted at least 96 so far. Among these are the BBC, British Airways and the U.S. Department of Energy. It was a sophisticated, multi-stage attack, which calls to mind the of 2021, also linked to Clop. As well as the original zero-day (), two more critical vulnerabilities have since been found and patched by MOVEit developer Progress Software: another SQLi flaw () and (). Financial services and insurance companies appear hardest hit, with the financial and reputational impact likely to be high. The U.S. government a $10 million dollar reward for information linking the attack to a nation-state. In early June, Barracuda Networks took the of urging all customers of its Barracuda Email Security Gateway appliance impacted by a recent to replace the devices immediately, regardless of patch version. That followed efforts by the cybersecurity vendor to update the appliances on May 21. The reason became clear after new intelligence on the case, which it was brought in to help with. An aggressive and persistent state-linked Chinese actor had been exploiting the zero-day in an espionage campaign dating back to October 2022. The Mandiant report named the unknown group UNC4841. It said that Barracuda decided to issue the call for customers to replace their appliances after the group switched malware and deployed new persistence mechanisms, following the issuing of the Barracuda update. UNC4841 stepped up its campaign from May 22-24, with high frequency operations targeting victims in 16 countries. A third were government agencies, but individual victims included well-known academics in Taiwan and Hong Kong and Asian and European government officials in Southeast Asia. Mandiant warned network defenders to continue monitoring for UNC4841 activity. Learn more about the ever-evolving nature of security threats and complex risk environments. Advanced Security Operations Center (SOC) Services,To help detect and contain sophisticated threats and help prevent them from spreading. Rapid Response Retainer,To help accelerate response to serious attacks. Web Application Firewall,To help mitigate the risks associated with the exploitation of public-facing applications. SASE Management,To help neutralize the cybersecurity risk from hybrid workers. To find out more, listen to the full threat intelligence briefing from the . 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 . . * Indicates a required field. We will follow up from your contact request using the information provided. 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. These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. We use both third party and first party cookies for this purpose. All information these cookies collect is aggregated and therefore anonymous. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance. These cookies enable the website to provide enhanced functionality and personalisation. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly. These cookies may be set through our site by Verizon and third parties. They are used to present Verizon advertising on third party sites that you may visit. They do not store directly personal information, but are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising from Verizon. BackClear Filters,All Consent Allowed
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