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cyber threat intelligence

Intelligence Defined and its Impact on Cyber Threat Intelligence

August 25, 2016

Michael Cloppert wrote a great piece to argue for a new definition of cyber threat intelligence. The blog is extremely well written (I personally love the academic style and citations) and puts forth a good discussion on operations. Sergio Caltagirone published a rebuttal equally valuable where he agreed with Mike that there is accuracy missing from current cyber threat intelligence definitions but noted that Mike focused too much on operations. The purpose of this blog is not to rebut their findings but to add to the conversation. In many aspects I agree with both Mike and Sergio; I would highlight that the forms of intelligence discussed though are very policy focused (sometimes even military focused) and influence how we define cyber threat intelligence. I do not envision that between these three blogs we’ve settled a long standing debate on intelligence but the intent is to add to the discussion and encourage thoughts by others.

In Mike’s piece the definition he presented for the field of cyber threat intelligence is the “union of cyber threat intelligence operations and analysis” each of which he previously defined. Sergio responded by stating “Intelligence doesn’t serve operations, intelligence serves decision-making which in turn drives operations to achieve policy outcomes.” I agree with this understanding of intelligence to meet policy needs and while Sergio intentionally does not intend to cover all aspects of intelligence outside of policy I believe it is important to consider. Mike teased out at one point that “…’intelligence’ more broadly is a bias toward a particular type of intelligence, and they continue to overwhelmingly focus on geopolitical outcomes.” He gives an example of business intelligence as another form of intelligence and accepts that the basis of intelligence is interpreted information with an assessment to advance an interest. This is where he stops though in an effort to stay focused on defining cyber threat intelligence. This is where I would like to begin.

Dr. Michael S. Goodman, a professor of intelligence studies at Kings College in London, wrote a piece for the CIA’s Center for the Study of Intelligence where he discussed the challenges and benefits in studying and teaching intelligence. He specifically noted that “The academic study of intelligence is a new phenomenon” although the field of intelligence itself is very old. More relevantly to this blog post he wrote that “Producing an exact definition of intelligence is a much-debated topic.” In a non-government intelligence focused piece the University of Oregon has a page dedicated to the theories and definitions of intelligence. There, they cite psychologists and educators Howard Gardner, David Perkins, and Robert Sternberg to assign attributes to intelligence and state that it is a combination of the ability to:

  • Learn
  • Pose Problems
  • Solve Problems

These three attributes are core to any definition of intelligence whether it’s business intelligence, emotional intelligence, or military intelligence. Additionally, the distinctly human component of this process, for those of you considering artificial intelligence as you read this, is harder to capture but likely exists in the ability to pose and solve problems. Machines can pose and solve problems to an extent but how they do that sets them apart from humans. More to the point, how each of us pose and solve problems is influenced at some level by bias. That bias is often an influence analysts seek to minimize so that it does not jade how we analyze problems and the answers we derive. However, that bias in how we pose and solve problems is likely the only distinctly human component of intelligence. That is a discussion for a longer future piece though.

Further in the University of Oregon piece, different types of intelligences are listed from Gardner, Perkins, and Sternbeg. A few are listed below:

  • Linguistic
  • Intrapersonal
  • Spatial
  • Practical
  • Experiential
  • Neural
  • Reflective

These different types of intelligence are not all encompassing and focus on the psychological more than classic government intelligence. However, they offer a more robust view into what it means to be able to process and analyze information which is in of itself core to cyber threat intelligence. I gravitate more towards Robert Sternberg’s understanding of intelligence and specifically his view of experiential and componential intelligence. According to his 1988 and 1997 writings on intelligence experiential intelligence is “the ability to deal with novel situations; the ability to effectively automate ways of dealing with novel situations so they are easily handled in the future; the ability to think in novel ways.” His understanding of componential intelligence is “the ability to process information effectively. This includes metacognitive, executive, performance, and knowledge-acquisition components that help to steer cognitive processes.”

I enjoy these two the most because they seem to map the closest to the idea of intelligence generation and intelligence consumption. In the field of cyber threat intelligence we often hear vendors, security researchers, and companies talk about “threat intel” and standing up teams to do intel-y things but without specific guidance. There is a stark difference in generating intelligence and in consuming it. Most companies are looking for threat intelligence consumption teams (those that can map their organization’s requirements and search for what is available to help drive defense) not threat intelligence generation teams (those individuals who analyze adversary information to extract knowledge which may or may not be immediately useful). A good team is usually the mix of both but with a clear understanding of which one is the priority and which effort is the goal at any given time. Sternberg’s experiential intelligence speaks more to threat intelligence generation whereas his componential intelligence addresses the ability to process, or consume, intelligence. The definitions are not as simple as this but it is thought provoking.

In reviewing Mike and Sergio’s excellent blog posts with the addition of a wider view on intelligence both from a classical, psychological, and philosophical aspect there are attributes that emerge. These attributes mean that intelligence:

  • Must be analyzed information
    • To perform analysis is a distinctly human trait likely due to our influence of bias and our efforts to minimize it (i.e. no $Vendor your tool does not create intelligence) meaning that it is always up to our interpretation and others may have other valuable and even competing interpretations
  • Must meet a requirement
    • Requirements can be wide ranging such as policy, military operations, geo-political, business, friendly forces movements and tactics, or self-awareness; the lack of a requirement would result in intelligence not being useful and by that extension be an inhibitor to intelligence (i.e. overloading analysts with indicators of compromise is not intelligence)
  • Must respect various forms
    • There is no one definition of intelligence but each definition must allow for different ways of interpreting, processing, and using the intelligence

To further qualify to be threat intelligence the presented intelligence must be about threats; threats are not only geo-political in nature but also may encompass insiders. However, I disagree with the notion that there is an unwitting insider threat because the definition of threat I subscribe to must have the following three attributes:

  • Opportunity
    • There must be the ability to do harm. In many organizations this means knowing your systems, people, vulnerabilities, etc.
  • Intent
    • There must be an intention to do harm, if it is unintentional the harm is still as impactful but it cannot be properly classified as a threat. Understanding adversary intention is difficult but this is where analysis comes in understanding the threat landscape
  • Capability
    • The adversary must have some capability to do you harm. This may be malware, it may be PowerShell left running in your environment, and it could be non-technical such as the means to influence public perception through leaked documents

Therefore, I use the following definition, heavily inspired by classic definitions, for intelligence: “The process and product resulting from the interpretation of raw data into information that meets a requirement.” The product may be knowledge, it may be a report, it could be tradecraft of an adversary, etc. Further, I use the following definition for cyber threat intelligence “The process and product resulting from the interpretation of raw data into information that meets a requirement as it relates to the adversaries that have the intent, opportunity and capability to do harm.” (Note that in this definition of cyber threat intelligence the adversary is distinctly human. Malware isn’t the threat; the human or organization of humans intending you harm is the threat.) Each definition is concise but open-ended enough to serve multiple purposes beyond military intelligence.

I in no way think that this solves any aspect of this debate. And I do not feel that my definitions actually conflict with what Mike and Sergio have put forward but are instead meant simply as an extension of the topic. Mike and Sergio are both extremely competent individuals that I am privileged to call my friends, peers, and over numerous occasions mentors. However, their blogs inspired me to explore the topic for myself and this blog was simply my way to share my opining on my findings. I hope it has been useful in some manner to your own exploration.

The Problems with Seeking and Avoiding True Attribution to Cyber Attacks

March 4, 2016

Attribution to cyber attacks means different things to different audiences. In some cases analysts only care about grouping multiple intrusions together to identify an adversary group or their campaign. This helps analysts identify and search for patterns. In this case analysts often use made up names such as “Sandworm” just to group activity together. To others, attribution means determining the person, organization, or nation-state behind the successful intrusion or attack; this latter type of attribution I will refer to as true attribution. There are many issues with true attribution that I want to explore here. However, there are also those that have pushed back on analysts exploring motives to an attack that I also want to call attention to. When dealing with attribution analysts should avoid the extremes: using true attribution inappropriately or being too hypersensitive to perform analysis and explore motives. Good analysts know when to seek true attribution and when to avoid it.

To explore these concepts I will look at true attribution at the tactical, operational, and strategic level of threat intelligence. While these levels should not be seen as a static category it will help shape the discussion. Tactical threat intelligence often deals with those folks who do the day-to-day security such as performing incident response and hunting for threats in the environment, operational threat intelligence refers to those personnel who work to identify adversary campaigns and often focus on aspects such as information sharing and working through organization knowledge gaps, and the strategic threat intelligence category I’ll use to refer to those personnel that sit at senior decision making levels whether it be executives or board of directors members at companies or national government officials and policy makers.

True Attribution at the Tactical Threat Intelligence Level

In my opinion, true attribution at the tactical threat intelligence level is only harmful to good security practices. Trying to identify who was responsible for the attack seems like a good idea to help shape security practices. As an example, an analyst who thinks that China is in their network might begin looking for intellectual property theft and try to shortcut their effort to identify the adversary. But think about that for a moment. Because our hypothetical analyst thought China was in the network, they have begun to look at the data in front of them differently. In this case, attribution has led our analyst to the land of cognitive bias. Cognitive biases are especially dangerous when performing analysis as they bias the way you think – and analysis leans so heavily on the human thought processes that it can lead us to inappropriate conclusions. Now, instead of keeping an open mind and searching for the threat in the network our analyst is falling prey to confirmation bias where the analyst is looking at the data differently based on their original hypothesis that China is in the network.

This begs the question though, if the analyst has nothing else to go off of shouldn’t they look for the tactics, techniques, and procedures of China in the network as a starting place? In my opinion that is the role of those often funky sounding made up campaign names or intrusion set names; this is what others sometimes call attribution but not true attribution. An analyst that thinks they know what “China” looks like really only knows previously observed activity. If I tell you to think about what China would be doing in a network you might think intellectual property theft. If I tell you the threat is Russia you might think of cybercrime or military pre-positioning. If I say Iran maybe you think about data destruction. The problem is, that thought process is tied to previously observed activity and it’s also going off of the assumption that previous true attribution you’ve heard is correct. Even if we assume all the previously true attribution was correct though analysts have only ever heard of or seen some of the campaigns by adversaries. Russia has teams that are interested in intellectual property theft just as China has teams that are interested in military pre-positioning. We are biased in how we view nation-state attribution based on campaigns we have seen before and it is difficult to take into consideration what is unknown. The better tactic is in identifying patterns of activity such as “Sandworm” and thinking to previous observed threats tactics, techniques, and procedures as a starting place in how we search the network for threats. Then tactical level threat intelligence analysts aren’t biased by true attribution but can use some element of attribution to learn from threats they’ve observed before while attempting to avoid cognitive biases.

True Attribution at the Operational Threat Intelligence Level

At the operational threat intelligence level the use of attribution needs to fit the audience. Operational level threat intelligence analysts should always attempt to serve as the bridge between the strategic level players and the tactical level analysts. When using the observations and information from the tactical level to translate to strategic level players there can be a role for true attribution, which we will explore later. When translating the observations at the strategic level and operational level to the tactical level though true attribution then again becomes dangerous. The way threat intelligence is positioned should be determined by the audience consuming it.

Consider this: an operational level threat intelligence analyst has been asked to take the campaigns observed in the community and translate that information for the tactical level folks to use. The indicators of compromise and security recommendations that the tactical level personnel should use are independent of attribution. The security recommendations and fixes are based off of the observed threat to the systems and vulnerabilities not the attribution; or said another way if you have to patch a vulnerability you don’t patch it differently if the exploit was Chinese or Russian based.

However, that same operational threat intelligence analyst has been asked to identify the threat landscape, the observed campaigns in the community that are relevant to the organization, and make recommendations for strategic level players that can influence organizational change. Here, the analyst may not be able to prove true attribution based off of observed adversary activity but it is in their best interest to identify patterns and motives to attacks. As an example, if there have been a number of campaigns recently that align with the motives of Chinese actors targeting the analysts’ company the recommendation from the operational level analyst to the strategic members might have them take into consideration how they interact with and do business with China. Here the analyst should use language to structure their assessment that the observed threats are Chinese based such as “high confidence”, “medium confidence”, and “low confidence.” Language such as “it is definitively China” should be avoided. Ultimately analysis is based on incomplete data sets (consider the difference between inductive and deductive reasoning) and the provided information is just an assessment.

At the operational level of threat intelligence analysts should be mindful of their audience and be open to putting forth good analysis based on observed activities, threats, and motives without being definitive on true attribution.

True Attribution at the Strategic Threat Intelligence Level

Strategic level audiences often heavily care about true attribution but not always with good reason. Government leaders and company executives want to know their threat landscape and how it might shape how they conduct business or policy. That is a good thing. However, strategic level players should be careful not to use true attribution when it’s not required.

As an example, if the organization is facing security challenges and is consistently having intellectual property stolen they need to look at the security culture of the organization and the resource investments needed to increase security and minimize risk. This inward look at the culture and security investments should usually be independent of true attribution. The tactical and operational level impacts are going to be the same whether the previous culprits were China, Iran, Russia, or the North Pole. However, if the organization is taking an outward approach to doing business or policy making they may need to consider true attribution. Because true attribution is usually based off of assessments and not usually definitive it should usually be approached as a continuum.

To look at true attribution especially for this level of threat intelligence I highly recommend two resources. First, a paper by Dr. Thomas Rid and (soon to be Dr. – congrats Ben!) Ben Buchanan titled Attributing Cyber Attacks. This paper will get you into the right mindset and understanding of attribution for the second paper I would recommend by Jason Healey titled Beyond Attribution. In Beyond Attribution, Jason Healey discusses the concept of responsibility as it applies to attribution. In short, a nation-state has responsibilities with regards to cyber operations especially if they might have been conducted from within its borders. At one side of the scale, a state can take an approach of prohibiting attacks and actually help other nations when an attack has begun. On the other side of the scale a state actually conducts the attack and integrates their attack with third-party proxies such as private companies for hire or hacktivists.

Analysts should be mindful of this spectrum of state responsibility, as Jason calls it, when considering true attribution and the nature of intelligence assessments. It is difficult to have true attribution and true attribution can be harmful to tactical level security. However, identifying motives in attacks and understanding the spectrum of state responsibility to attacks should be considered at the strategic level so that we are not so hypersensitive on the topic of attribution that every adversary gets to operate without consequence.

Case Study: Cyber Attack on the Ukrainian Power Grid

Let’s take these concepts and apply it to the cyber attack on the Ukrainian power grid. If you’re unfamiliar with the case you can read about it here. In this case, I have been very careful about my wording as I know there are multiple audiences that see my quotes in media or read my reports. On one hand, I teach a threat intelligence course and an ICS/SCADA active defense and incident response course at the SANS Institute. In this capacity most of my audience is tactical and operational level personnel. For those reasons I have often tried to reinforce that attribution in Ukraine doesn’t matter for them. Identifying indicators of compromise to hunt throughout the network, preparing the network to make it more defensible, and applying lessons learned from the Ukraine attack are all independent of true attribution. True attribution simply doesn’t matter for how we apply the lessons learned for security at those levels.

However, I also deal with strategic level players in my role in academia as a PhD student at Kings College London and as a Non-Resident National Cyber Security Fellow at New America where I work with policy makers. For this audience, it is important for me to note that definitive true attribution has not been obtained in the Ukraine attack and may never be obtained. However, in considering Jason’s spectrum of state responsibility we have to look at the attack and realize the potential motives, the larger geo-political setting, and analyze if there are any courses of action strategic level personnel should take. In my opinion, I doubt the Russian government itself carried out the attack. However, the attack on the Ukrainian power grid did not fit any apparent financial motives and the motives aligned with various Russian based actors; whether those are private companies, hacktivists, or senior government officials. Therefore, it is in my opinion and in my analysis that strategic level players should look at the elements of attribution that link to Russian based teams and consider Jason’s spectrum of state responsibility. Even if Russia had nothing to do with the attack there should be an investigation into whether or not it occurred from within their borders. If the attack is state-ignored it sets a dangerous precedent. Senior policy makers in other nations should under no circumstance jump to blaming Russia for anything. However, they should look for international cooperation and potentially an investigation as this is a first-of-its-kind cyber attack on civilian infrastructure that led to a power outage. There is a line between espionage and offense; that line was crossed in Ukraine and we must be careful of the precedent it sets.

Conclusion

In conclusion, true attribution is highly abused in the information security community today. Many organizations want true attribution but do not know how to use it appropriately and many private companies are quick to assign definitive attribution to attacks where they simply do not have the appropriate data to support their conclusions. True attribution makes media headlines and the motives for companies to engage in this activity are significant for that reason. Claims of true attribution do increase international tension; not as significantly as some would assume but they are individual data points to policy makers and national level leaders. However, being hypersensitive about true attribution enforces a culture in this field where nation-states can ignore responsibility such as investigating attacks or policing their borders as is normal in international law and policy in any other domain other than “cyber.” There is a balance to be struck. Knowing how to strike that balance and when to use attribution in the form of group names with no state ties or true attribution in the form of an evolving assessment will help the threat intelligence community move to a more mature point where tactical, operational, and strategic level players can all benefit.

 

*Edit 3/6/2016*

I had a good discussion with some colleagues around this post and wanted to add two points.

  • Richard Bejtlich had a really good blog post on the value of attribution and breaks it down in a number of useful ways. His blog post pre-dates mine but I failed to reference it the first time. It can be found here. I would recommend it as it’s a great read and doesn’t take long to work through.
  • Two peers, Mark and Tim, made a case for tactical level true attribution that I think is actually an interesting one to consider. I would argue that most tactical folks shouldn’t consider true attribution and that it’s highly highly abused and resource intensive with little value in the wider community today. That being said, Mark made the point that in a resource constrained environment it might be a useful factor in prioritization. As an example, if you have a lot of phishing emails or malware samples to look at and you need a place to start, true attribution could be of value as that starting point as long as you try to defeat any biases later on. The reason this could be of value (credit to Mark and Tim on this point) over just attribution of groups is: if you have data that is of use to specific countries (think F-35 fighter aircraft intellectual property being of value to China and Russia more so than Niger) using that information as a starting point and prioritization of your searches could be useful. This also touches on the topic of crown jewel analysis combined with threat intelligence; for anyone interested in that subject check here.  This to me gets closer to the operational level than the tactical level and I would expect operational folks to translate these concepts into a usable form for tactical level analysts instead of expecting them to start this process – but I can see the case for why this would be useful at the tactical level and would agree that it’s an interesting one to consider.
  • (Thanks to the peers that took the time to discuss their thoughts with me. Discussions like these help all of us explore our understanding of a topic and I always find my own learning process enhanced by them).

No, Norse is Not a Bellwether of the Threat Intel Industry but Does Hold Lessons Learned

January 30, 2016

Brian Krebs published an outstanding report today titled “Sources: Security Firm Norse Corp. Imploding” which has led to the emergence of a number of blogs and social media rumblings about what this means for the cyber threat intelligence community. Some have already begun positioning that this is the fall of threat intelligence. I would not only disagree and believe this to be a mostly isolated case but position that if anything this is a good sign of the community’s growing maturity. The purpose of this blog is to discuss why Norse’s potential and impending implosion does hold some lessons learned for the industry but holds no prediction of negative things to come for the threat intelligence community as a whole.

Before elaborating on these points though, I want to start off with the much needed statement about the people at Norse. To anyone in the community that holds strong negative feelings for Norse (and you are not alone) please be conscious that many of the individuals working at Norse were professionals and very talented. Many of the negative feelings towards the company were likely based on the marketing efforts and mislabeling of the content and value of their product; not negativity towards the people that work there. I hope the former employees land softly at their next jobs and I would encourage companies looking to hire to think of these individuals without prejudice.

With regards to Norse it was in many ways a good looking company. It garnered national media level attention through smart placement of their cyber attack map (yes the pew pew cyber map analysts have mostly grown to hate – but it looked good in media). There were some key employees recruited who were well respected in the industry. And it raised tens of millions of dollars in investments to appear as an exciting California security startup. So now that the company is apparently imploding it does seem natural to think that this may be an indication of things to come with regards to the threat intelligence industry and for a ripple effect in investments into this space. However, I would state this as wholly inaccurate although there are some lessons learned here for both investors and security startups.

First, Norse Corp. may have garnered national level attention but most of it was not actually good attention. Also, they billed themselves as a threat intelligence company when, in my opinion, they simply were not. Folks who are familiar with me, or read it in the Krebs report, will remember that I came out very publicly chastising their dangerous assessment that there were Iranian attacks on U.S. industrial control systems. The key reason that they had a bad assessment is actually why Norse was always doomed to fail. The company was interpreting Internet scanning data against their high level sensors as attack intelligence. Most threat intelligence companies rely upon enriched data complemented with access to incident response data of actual intrusions; not scanning activity. Norse also held no verifiable industrial control system expertise but were quick to make assessments about these systems. And further when they stated that there were attacks on control systems by Iran what the data seemed to show was they actually should have said scans against systems trying to mimic industrial control systems by Iranian IP addresses. The effort by them and the think tank AEI to state that there should be policy considerations in the Iranian nuclear negotiations based off of this data is a great representation of what not to do in the industry. Simply put, they were interpreting data as intelligence. There is a huge difference between data, information, and intelligence as I outlined here. While their product and Internet level scanning data was interesting and potentially very valuable for research it was not threat intelligence. So while they may have billed themselves as significant players in the threat intelligence community they were never really accepted by the community, or participating in it, by most leading analysts and companies. Therefore, they aren’t a bellwether of the threat intelligence industry or of other companies having trouble simply because they weren’t really ever in “the industry.” The threat intelligence community can be fairly small and making strategic mistakes can have significant lasting impact. Trust is a huge part of the equation in this community.

Second, this case-study of Norse holds great lessons learned. First, because trust is a significant part of doing intelligence work and in participating in this community there is a requirement for companies to realize they are dependent on the ecosystem and are not living in a bubble. Formal and informal relationships, company partnerships, and information sharing can help companies succeed quickly. It is not a competitive landscape in such that companies should think that success is a finite item where one company’s success means less is available for others. Quite the opposite. As threat intelligence is used more appropriately throughout the industry it will continually open up the market. For example, threat intelligence is meant to make good security programs better or to help give important context and information to strategic level organization decision makers – it is not meant to replace bad security programs or act as a magical solution for security. Second, threat intelligence companies should be very careful in lining up their marketing efforts with an honest assessment of what the company’s product or services actually produce. This should apply to any security startup but it is vital in the threat intelligence community. Whereas claims around general security can be difficult to interpret there are definitive ways to look at company claims in intelligence and dismiss them completely as hype. This dismissal is hard to recover from. Finally, an important lesson learned here is for investors and Venture Capital firms to dig deep not only into what is being shown by the company but also in how they are perceived in the community. There are many “experts” in this community who’ve never held the appropriate positions or roles to ever have been put in a situation to speak with expertise about threat intelligence. As an example, one of my critiques of Norse was that their “intelligence report” on industrial control system attacks was not written by anyone with industrial control system expertise. Just as we would expect a Russian intelligence analyst to have an understanding of Russia or even speak Russian the community and investors should demand that assessments are qualified by actual expertise not just general “cyber” expertise.

Venture Capital firms invest in companies with the expectation of not getting an immediate return on investment. In an overly simplified stereotype most Venture Capital funds expect not to see their returns for five to seven years with events such as an IPO or company merger/acquisition. Following that logic, it is reasonable to believe that investments made five to seven years ago are starting to be looked at for their return on investment to the Venture Capital firms. The landscape for investment will likely become much more competitive. There will be lessons learned from investing in good-sounding but under-performing companies. Investors and industry analysts will demand more proof of claims, understand what hype looks like a bit better, and invest even more intelligently. This is a good thing for the industry. I doubt Norse will be the last company to fail in the threat intelligence industry but the industry and investments into it will likely continue to grow. The focus will be on smarter money.

 

 

Data, Information, and Intelligence: Your Threat Feed is Not Threat Intelligence

July 9, 2015

This was first posted on the SANS Forensics blog here.

 

Threat feeds in the industry are a valuable way to gather information regarding adversaries and their capabilities and infrastructure. Threat feeds are not intelligence though. Unfortunately, one of the reasons many folks become cynical about threat intelligence is because the industry has pushed terminology that is inaccurate and treated threat intelligence as a solution to all problems. In a talk I gave at the DFIR Summit in Austin, Texas I compared most of today’s threat intelligence to Disney characters — because both are magical and made up.

When security personnel understand what threat intelligence is, when they are ready to use it, and how to incorporate it into their security operations it becomes very powerful. Doing all of that requires a serious security maturity in an organization. The biggest issue in the industry currently is the labeling of data and information as intelligence and the discussion of tools producing intelligence.

jp 2-0
Figure 1: Relationship of Data, Information, and Intelligence

One of the commonly referenced works when discussing intelligence is the U.S. Department of Defense’s Joint Publication 2-0: Joint Intelligence. Intelligence has been around a lot longer than the word ‘cyber’ and it’s important to look to these kinds of sources to gather important context and understanding of the world of intelligence. One of the graphics (Figure 1) presented in the publication shows the relationship of data, information, and intelligence. If the cyber threat intelligence community writ large understood this single concept it would drive a much better discussion than what is sometimes pushed through marketing channels.

Every organization has an operational environment. The physical location of the organization, the networked infrastructure they use, the interconnections they have with other networks, and their accessibility to and from the Internet are all portions of their operational environment. This operational environment contains more data than could ever be fully collected. Many organizations have difficulty collecting and retaining packet capture for their environment more than a few days (if at all) let alone all of the data. So collection efforts are often driven by tools that can reach into the operational environment and get data. On limited resources it usually takes analysts understanding where the most critical data is located and to collect it using the best tools available. Tools are required to make the most out of data collection efforts. The data in this form is raw.

This raw data is then processed and exploited into a more usable form. As an example, the packet capture that is run against an intrusion detection system generates information in the form of an alert. There should be more data than information. The information may have a sample of the data, such as the portion of the packet capture that matched the alert, and it is made available to the analyst with some context even if only “this packet matched a signature thought to be malicious”. Information can give you a yes or no answer. Another example would be an antivirus match against malware on a system. The raw data, the malware’s code, is matched against a signature in the antivirus system to generate an alert. This alert is information. It answers the question “is malware present on the system”. The answer could be incorrect, maybe the match was a false positive, but it still answered a yes or no question of interest. Tools are not required to make information but it is very inefficient to create information without tools. Most vendor tools that make claims of producing “threat intelligence” are actually producing threat information. It is extremely valuable and necessary for making the most of analysts’ time — but it is not intelligence.

Various sources of information that are analyzed together to make an assessment produce intelligence. Intelligence will never answer a yes or no question. The nature of doing intelligence analysis means that there will only be an assessment. As an example, if an intelligence analyst takes a satellite photo and notices tanks on the border of Crimea they can generate information that states that the tanks are on the border. It answers a yes or no question. If the intelligence analyst takes this source of information and combines it with other sources of information such as geopolitical information, statements from political leaders, and more they could then make an assessment that they state with low, medium, or high confidence that an invasion of Crimea is about to take place. It is impossible to know the answer for sure — there cannot be a yes or no — but the analysis created an intelligence product that is useful to decision makers. There should also be far more information than intelligence; intelligence is a refined product and process. In the cyber field we would make intelligence assessments of adversaries, their intent, potential attribution, capabilities they may be seeking, or even factors such as their opportunity and probability of attacking a victim. The intelligence can produce useful knowledge such as the tactics, techniques, and procedures of the adversary. The intelligence can even be used for different audiences which usually gets broken into strategic, operational, or tactical level threat intelligence. But it is important to understand that no tool can produce intelligence. Intelligence is only created by analysts. The analysis of various sources of information requires understanding the intelligence needs, analysis of competing hypotheses, and subject matter expertise.

By understanding the difference between data, information, and intelligence security personnel can make informed decisions on what they are actually looking for to help with a problem they face. Do you just want to know if the computer is infected? Threat information is needed. Do you just want raw data related to various threats out there? Threat data is needed. Or do you want a refined product that makes assessments about the threat to satisfy an audience’s defined needs? That requires Threat intelligence. This understanding helps the community identify what tools they should be acquiring and using for those problems. It helps guide collection processes, the types of training needed for security teams, how the security teams are going to respond, and more.

There is no such thing as threat intelligence data, there are no tools that create intelligence, and there is limited value for organizations that do not understand their operational environment to invest in threat intelligence. But when an organization understands the difference between data, information, and intelligence and understands their environment to be able to identify what constitutes a threat to them then threat intelligence is an extremely useful addition to security. I am a big believer in cyber threat intelligence when it is done correctly. It’s why I worked with Mike Cloppert and Chris Sperry to co-author SANS578 — Cyber Threat Intelligence. It is unlikely though that your threat feed is really threat intelligence. But it may be exactly what you’re looking for; know the difference so that you can save your organization time and money while contributing to security.