photo taken from

I recently completed the FAIR analysis fundamentals course and here are my thoughts on it.

FAIR stands for Factor Analysis of Information Risk, and is the only international standard quantitative model for information security and operational risk. (

I was introduced to FAIR early this year. The interest to learn more came from two observations.

The first was that we had many definitions of what constitute risk. We refer to “script-kiddies”as risks. Not having a security control is referred to as risk. SQL injection is a risk. We also said things like “How much risk is there with this risk?”

The other observation was with our approach at quantifying risk. We derived the level of risk based on the likelihood and impact. And sometimes it was hard to get agreement on those values.

Having completed the course, one of the things I like about FAIR is their definitions. Their definitions of what is a risk, and what it must included. It should include an asset, threat, effect with a method that could be optional. An example of a risk is the probability of malicious internal users impacting the availability of our customer booking system via denial of service.

It uses future loss as the unit of measurement rather than a rating of critical, high, medium & low. The value of future loss is expressed as a range with a most likely value along with the confidence level of that most likely value. As such it focuses on accuracy rather than precision. I quite like that as it makes risk easier to understand and compare. Reporting that a risk has a 1 in 2 year probability of happening with a loss between $20K to $50K but likely being $30K is a lengthy statement. However it is more tangible and makes more sense than reporting that the risk is a High Risk.

Now it sounds like I’m all for FAIR, but I have some reservations. The main one being that there isn’t always data available to determine such an empirical result. Risk according to FAIR is calculated by a multiplication of loss frequency (the number of times a loss event will occur in a year) with loss magnitude (the $ range of loss from productivity, replacement, response, compliance and reputation). It’ll be hard to come up with a loss frequency value when there is no past data to base it on. I’ll be guessing the value and not estimating it. FAIR suggests doing an estimate for a subgroup if there isn’t enough reliable data available, but again I see the same problem. The subgroup for loss frequency is the multiplication of number of time the threat actors attempt to effect the asset with the percentage of attempts being successful. Unless you have that data, that to me is no less easier to determine.

Overall it still feels like a much better way of quantifying risk. I’ll end with a quote from the instructor. “Risk statements should be of probability, not of predictions or what’s possible.” It resonated with me as it is something I too often forget.