Over the past decade exploitation techniques have been developed and refined to the point that very little expertise has been needed to successfully exploit software vulnerabilities.  These refinements have lowered the bar for attackers and drastically increased the probability that an attack will be successful.  This has led to the need for mitigation techniques that can prevent or otherwise reduce the reliability of a given exploitation technique.  In relation to one another, we can think about exploitation techniques as attempting to drive the probability of successful exploitation to 100%, whereas mitigation techniques attempt to drive the same probability to zero.  While probability gives us a nice measure for the effectiveness of a mitigation technique, it doesn't give us immediate insight into the specific problems being solved by mitigations or the techniques that are being used to solve those problems.

Understanding the problems that are solved by mitigations is what provided the motivation for the presentation I will be giving at BlueHat.  Many of the materials in this presentation were taken from my work with Leviathan Security Group and have been repurposed to focus on taking attendees on a journey through the technical evolution of the mitigation techniques developed by Microsoft.  This evolution is illustrated in terms of the problems each mitigation technique is attempting to solve, the methods used to solve them, and how well each mitigation has stood the test of time thus far.  The journey itself starts first with /GS and ends with a glimpse of the mitigation techniques we might expect to see in the future. 

When a data owner's (a business) sensitive data is breached it is difficult to quantify the monetary loss. According to respectable survey sources, the average cost of sensitive data breach for a large size company is about $50,000. I am attempting here to think about this in simple mathametical terms:

There is a data breach. From the data owner's perspective the loss is:

Loss = Cost to protect data + Loss of business due to data theft aka cost of competitive disadvantage

From the data thief's perspective

Net Gain= [Cost of producing the data  *  Data freshness factor] - Cost to steal the data + Profit of business due to data aka gain of competitive advantage

From the above two equations it is very clear that this is not a zero sum game. There is a clear cost asymmetry for a data owner and for a data thief. When there is an asymmetry there is an opportunity. Data owner would not even know that the data is lost because the original copy of the data may be still intact - data thief could have simply copied the data. Data theft does not look like a car theft, there is no vacuum left behind. 

This motivates a data thief to keep the cost to steal low, steal highly valuable data that has a long shelf life and in a way that data owner will never even be aware of theft.

From a data thief's perspective, the cost to steal data if kept high would disincentive him. Moreover, Data freshness factor, i.e. how valuable this data is over period of time plays an important role. A good example is content of today's newspaper is hardly valuable tomorrow, but the content of newspaper two days ahead (if can be procured)would be invaluable. Data relevance is a function of time and other marketplace variables -  Data freshness Factor accounts for that variable. A good way to discourage data thief is to increase his/her cost to steal the data. There are other inferences from the above equation. If there exists no competitive advantage with the stolen data, hardly any thief would even venture to steal the data in the first place. If the cost of producing data is very low, then probably thief can just produce the data himself and would not attempt to steal the data. If the cost of theft is kept high, it would definitely deter the data thief from stealing data using technical mechanisms, then the data thief would exploit weak links in data security such as use of social engineering to get access to the data.

From data owner perspective protecting data becomes very important. How much would the owner be willing to spend? Not definitely the cost equal to cost of producing the data. 1% to 10% of cost of producing data is considered prudent. For a data owner it is difficult to estimate cost of data protection of a specific data, because it is not easy to chunkify data protection costs. Moreover, as Dan Geer says in his book, a data owner has to protect himself from number of intruders not just one.

It pays for a data owner to: be aware of data breaches (or data leaks), employ appropriate mechanisms to protect the data; the cost of protection which is fractional cost of the valuable data and enhance information security awareness of personnel who handle the data.

Data loss is not a zero sum game. The advantage is in favor of a data thief (data thieves rather). Data owner does not give much thought on the value of data unless there is a data theft. But, a data thief has every reason to think about economics of data theft before he acts to steal the data else data thief won't survive in this game and he is very well aware of his advantageous position.

COBIT rivals ITIL from The IT Skeptic

“Everyone is tiptoeing around the fact that COBIT offers a significant competitive body of knowledge (BOK) to ITIL. Sure ITIL goes into more depth in places, but to say COBIT sits over the top is to grossly understate the overlap. COBIT extends a long way down into the “how” and it does it with an intellectual rigour that ITIL lacks.”

Interesting stuff that.  A detailed mapping might help some folks.  Either way, the good news for those keen on understanding risk management is that governance metrics, done right, allow us to understand a part of that “capability to manage risk” we’re always looking for.   Assurance, verification and the acquisition and interpretation of knowledge is king.   Speaking of which….

How To Tell When “Nothing Happens” by Pete Lindstrom

“…problem is that, it isn’t really true that “nothing happens” when you employ some specific security control to prevent an exploit. Not only that, but even when it is difficult to collect data on what didn’t happen, one can devise experiments to tell how frequently that nothing occurred.”

Good analysis is all about the uncertainty.   Speaking of accounting for uncertainty…

Assets Good Until Reached For by Gunnar Peterson

“If you have a 100,000 dekstops or 100,000 servers it hard to manage. You will need to automate and to do that you need to abstract, but you should also realize that its a drawing on a whiteboard not reality. You need abstraction assurance.”

And there’s the trick.  We might call “abstraction assurance” an analog to “confidence” or “uncertainty” in certain priors (metrics) or posteriors (calculated values based on those metrics).  The stronger that abstraction assurance is, the less uncertainty we have in our knowledge and the better our ability to create wisdom from that knowledge (you know, make decisions).

Epstein, Snow and Flake: Three Views of Software Security by Adam Shostack

Adam’s focus is on software security, but the discussion here can be abstracted out into the broader realm of risk management quite nicely.

Two-thirds of firms hit by cybercrime from Security Focus

The US DoJ says that in 2005 (there’s some timely data) 2/3 of their surveyed firms detected at least one cybercrime.  “Cybercrime” is “classified … into cyber attacks, cyber theft, and other incidents.”  Pretty general.  Also from the report:  “Computer viruses made up more than half of all cyber attacks.”

(That sound you hear is me tapping my forehead lightly on large iron object)

Lessons Learned from “Personal” Risk Management By: Christopher Daugherty

“This process is what I call “personal risk management.”  All of us have done it and will continue to do so.  Why is it, then, many companies have ignored following similar principles with the on-going health of the business?  This is a debate with many different answers so I ask you to select the best answer for your employer:

a) Have not ignored as this keeps me awake at night!

b) Please restate the problem, I cannot hear well with my head buried in the sand.

c) We passed our SOX audit so we checked this off the list!

d) We are informed of the challenge but we have a business to run and profits to make

e) Is this what internal audit and risk management has been telling us?”