My first week here at Mobile System 7 was a crazy one; we spent hours with dry-erase markers in our hands, going over drawings of architecture, conceptual drawings of data flows and event streams, a bit of equations, and lots of (probably crucial) stuff that never made it into my notebook. I knew that our goal was to help organizations identify and block Bad Guys, but I probably came out of that week thinking that the product was more about whiteboards than anything else.
Over the months my conceptual model of Interlock has distilled into a better approximation of its true essence: risk, as it applies to identities, both noticing risk and responding to risk. Risk is a challenging problem, seemingly impossible at first glance. Calculated risk is a measure of not only the likelihood that a given set of features is going to have a downside, but also a measure of the severity of that downside. It seems like there are too many degrees of freedom, that this set of equations has too many unknowns. How can we even approach this problem, much less do it reliably?
Indeed, it is a challenge to effectively estimate risk, and in a lot of ways it is both a people problem and a technology problem, but it is in no way impossible. In order to better understand the overall picture of risk, it is informative to first separate Interlock's view of risk into two separate concepts: unsubstantiated risk and intrinsic risk.
Unsubstantiated risk is the risk posed by activities with unsubstantiated parameters, such as activities with a new device or in a new location. The important aspect of the unsubstantiated parameters is that they represent a departure from the user's (or population's) normal operating parameters. Each activity that has unsubstantiated parameters potentially poses a threat because it is associated with a nonzero probability that the person taking the action is not the person they claim they are. Think about it: if you saw someone log into their email from their house, using the same MacBook they've used every day for a year, at time of day that they log in every day, it is almost certainly that person; if instead they suddenly logged in from Sudan using a new Windows PC at a time when they are normally asleep, the activities performed with those parameters are much more likely to be malicious. These Sudanese activities pose a large unsubstantiated risk.
It's worth saying that the typical approach to unsubstantiated risk is to build more structure and trust around authentication, to try and ensure that the person behind each activity is the person they claim to be. Unfortunately, we have seen time and again that dedicated attackers can and will gain access to desired resources despite expensive and complicated authentication measures such as MFA. As a result, conflating authentication and security creates a common blind spot for organizations, one that we talk about a lot: the identity gap. The identity gap results when authentication is the last line of defense, leaving each further action subject to no analysis. Monitoring unsubstantiated risk for each access goes a long way toward closing this security gap. Bad guys can no longer act with impunity, as every action they take may reveal them.
Intrinsic risk is the risk posed by the identity as a result of its characteristics, things like the total number of devices it uses or the number of groups it is in, as well as labelable characteristics like that the user is a frequent traveller. Intrinsic risk adds an element of risk to every activity associated with the given identity. Each identity with intrinsically risky characteristics potentially poses a threat because they have the capability to be very destructive to the organization. As a result, every action they take must be subject to higher scrutiny. Intrinsic risk helps prevent a number of potential issues, but it's particularly useful in identifying potential insider threats.
Because it adds risk to activities, intrinsic risk also magnifies any unsubstantiated risk the identity may be associated with. Because intrinsic risk implies that the identity has the power to be very destructive, the implications of a compromised account with high intrinsic risk are dire. For this reason, intrinsically risky identities with activities exhibiting unsubstantiated risk represent the largest threat to an organization.
The ultimate goal is not to have the most accurate estimate of risk for each identity, but to have the most accurate actionable estimate of risk. Each estimate can therefore be associated with a measure of reliability and a measure of actionability based on all of the information we have available to us. Each type of risk has its own methods for computing confidence, and has different ways of responding to the addition of new information.
By its very nature, intrinsic risk has a high degree of reliability, but by itself represents low actionability. Options for remediating intrinsic risk include destructive actions such as revoking permissions of the identity permanently, which lowers the intrinsic risk directly, or forcing the identities to constantly validate their actions. As most organizations have a spectrum of intrinsic risk across their identities, neither option is acceptable in general.
In contrast, unsubstantiated risk typically has a low degree of reliability at first blush, but a high degree of actionability. This is because unsubstantiated risk can be remediated by allowing the user to substantiate the parameters of their action. Substantiating actions in this way can happen automatically or manually. If a user logs into a service from their new phone, it is an unsubstantiated risk; if they continue to use the phone within otherwise normal parameters (e.g. logging in from their normal operating locations at their normal times of day using normal access patterns) that phone grows to be trusted automatically. Alternatively, assuming the presence of a trusted communication channel the user can be asked to verify the parameters directly - did you just use a new Android phone in Brazil?
Responding to Risk
Ultimately, how we address a given risk boils down to a combination of the above factors, the degree of each type of risk, the distribution of each type of risk in the population, and the policies specified by the user. Adaptive access control aims to respond to risk in the way that is both least intrusive and most effective.
Addressing unsubstantiated risk by asking the user to verify the parameters of the activities directly offers a one-time process for responding to risk. If the parameters are indeed correct, the unsubstantiated risk is attenuated; if not, it is a direct confirmation of a security failure. We are currently developing a direct solution like this for risk remediation in Interlock. It promises a tremendous improvement to the focus and accuracy of our risk estimates with little or no expenditure of scarce security resources on the part of the organization.
The correct response to intrinsic risk is usually taking no action at all but rather subjecting the identity to closer scrutiny. A direct approach to intrinsic risk is inappropriate. For a potential insider threat the user herself represents the threat and would be expected to respond negatively; for a sensitive user, substantiated activities are part of normal operating procedure.
In many ways, the biggest challenge is the final factor in responding to risk: user policies. What tools can we provide the user with to help them understand the identities in their organization, the scope of their risk, and the best way to address that risk? How can we leverage the functional differences between mitigation strategies to effectively and unobtrusively respond to risk? What granularities of mitigation make sense across organizations and within specific organizations? These are all questions we are continually striving to answer in Interlock. Ultimately, organizational risk mitigation is a human problem more than a technology problem. The best we can do is continue to work with organizations who are struggling with this burden now to find the best solution for everyone.
If you're an organization interested in finding the best solutions to addressing risk in your identities contact us about a free Test Drive of Interlock. If you're a developer (or data scientist, or UX designer!) who wants to help navigate risk across and among populations of thousands of identities with hundreds of millions of activities send me an email with who you are what you can add to our team.