The problem is that (Chris’ analysis is) completely impractical. I’ll take a recent, and fairly typical situation as an example. I was taking issue with the manner in which remote access was being provisioned for a third party vendor to connect to a system hosted by one of our European business units. To cut a long story short, it was not only a breach of policy but highly insecure. I wanted the access to be disconnected, the business unit director wanted my risk assessment. And he didn’t want to wait for it.

To quote Chris Hayes, spending time on working out the expected effectiveness of controls, over a given timeframe, as measured against a baseline level of force was not going to pacify an angry Italian fearful that my decision was going to cost him money. He wanted my explanation of the risk and more importantly, what I was going to offer as a solution to keep his business functioning

As Chris is someone who actually does this for a living in a large company, and this is typical of his actual day job, I really find Stuart’s “impractical” comment to be, um, misinformed.

Also, I think Stuart mistakes the purpose of a risk analysis.  The purpose of the risk analysis is not to force someone to be “secure”, but to provide knowledge for decision making.  Using it as a “hammer” to knock in the nail of your personal risk tolerance impairs efficiency and in the long run retards “security” as it creates political resentment.  Seriously, who cares if something might violate policy or not in a pre-implementation discussion?  Policies are not stone tablets handed down from on high, they are state-in-time codification of the data owners risk tolerance.  This risk tolerance changes sometimes, and that’s OK.

To that extent, I appreciate (and I’m sure Chris does, as well) that risk analysis does not create rationality in the data owner.  Someone who sees you as a speedbump on the route to progress they may not be ready to appreciate your point of view even if it is stated in the most rational manner possible.   But it’s worth noting (and Stuart’s example is indicative of this point) that risk analysis does not create rationality in the analyst, either.  If one is being so “security minded” as to ignore the risk tolerance of the business owner - we’re bound to get a reaction similar to that Stuart encountered.  In fact, a practical risk analysis like Chris performed on his blog, done in 30 minutes, should identify the critical point of disagreement between Stuart and the data owner (again, Stuart doesn’t own the data, the agitated Italian does).

But let’s stay rational and open to alternatives to what Chris offers.  Stuart states his approach to risk analysis as:

When I need to document a risk assessment I use a very simple form: list the threats, state the level of vulnerability, list the associated operational costs and potential revenue hits. High, medium, or low risk? Describe the controls and options. Write up who needs to do what, and how much of their time it’s going to take. Job done.

At first glance, I don’t think what Chris has done is any less efficient, and it provides greater insight (using Frequency and Capability instead of just ‘listing the threats’).  But what is key here is that Chris’ approach is consistent and defensible.  Less generous risk geeks and CSO’s I know would have no little difficulty with Stuart’s approach.  But to particularly answer Stuart’s main objection (impracticality) I would offer that with practice, Chris’ work is probably quicker and easier than Stuart’s described process as it eliminates much of the ambiguity an immature risk analysis creates - reducing the need for further discussion and arguments with data owners (regardless of disposition or nationality).

Finally the irony of Stuart’s post is that the reason he had this confrontation may in fact be because he was incapable of bringing a salient model for risk to the table, one that identified the factors that create risk and developed a defensible belief statement concerning risk.   We’ll never know if one would have helped him in this isolated instance, but I can tell you that in organizations like Chris’, good risk models and strong risk anlayses create operational efficiencies, reduce costs, and streamlines intra-departmental communications.

"Risk management" is just a fancy term for the cost-benefit tradeoff associated with any security decision. It's what we do when we react to fear, or try to make ourselves feel secure. It's the fight-or-flight reflex that evolved in primitive fish and remains in all vertebrates. It's instinctual, intuitive and fundamental to life, and one of the brain's primary functions.

Some have hypothesized that humans have a "risk thermostat" that tries to maintain some optimal risk level. It explains why we drive our motorcycles faster when we wear a helmet, or are more likely to take up smoking during wartime. It's our natural risk management in action.

The problem is our brains are intuitively suited to the sorts of risk management decisions endemic to living in small family groups in the East African highlands in 100,000 BC, and not to living in the New York City of 2008. We make

systematic risk management mistakes -- miscalculating the probability of rare events, reacting more to stories than data, responding to the feeling of security rather than reality, and making decisions based on irrelevant context. And that risk cockpit of ours? It's not nearly as finely tuned as we might like it to be.

Like a rabbit that responds to an oncoming car with its default predator avoidance behavior -- dart left, dart right, dart left, and at the last moment jump -- instead of just getting out of the way, our Stone Age intuition doesn't serve us well in a modern technological society. So when we in the security industry use the term "risk management," we don't want you to do it by trusting your gut. We want you to do risk management consciously and intelligently, to analyze the tradeoff and make the best decision.

This means balancing the costs and benefits of any security decision -- buying and installing a new technology, implementing a new procedure or forgoing a common precaution. It means allocating a security budget to mitigate different risks by different amounts. It means buying insurance to transfer some risks to others. It's what businesses do, all the time, about everything. IT security has its own risk management decisions, based on the threats and the technologies.

There's never just one risk, of course, and bad risk management decisions often carry an underlying tradeoff. Terrorism policy in the U.S. is based more on politics than actual security risk, but the politicians who make these decisions are concerned about the risks of not being re-elected.

Many corporate security decisions are made to mitigate the risk of lawsuits rather than address the risk of any actual security breach. And individuals make risk management decisions that consider not only the risks to the corporation, but the risks to their departments' budgets, and to their careers.

You can't completely remove emotion from risk management decisions, but the best way to keep risk management focused on the data is to formalize the methodology. That's what companies that manage risk for a living -- insurance companies, financial trading firms and arbitrageurs -- try to do. They try to replace intuition with models, and hunches with mathematics.

The problem in the security world is we often lack the data to do risk management well. Technological risks are complicated and subtle. We don't know how well our network security will keep the bad guys out, and we don't know the cost to the company if we don't keep them out. And the risks change all the time, making the calculations even harder. But this doesn't mean we shouldn't try.

You can't avoid risk management; it's fundamental to business just as to life. The question is whether you're going to try to use data or whether you're going to just react based on emotions, hunches and anecdotes.

This essay appeared as the first half of a point-counterpoint with Marcus Ranum in Information Security magazine.