[Owasp-leaders] Potential Update to the OWASP Risk Rating Methodology

Tim tim.morgan at owasp.org
Tue Mar 12 17:41:38 UTC 2013


Hi Josh,


> In any case, if what I said above is true, then this methodology is
> effectively broken in certain situations.  I think that it would be really
> easy to correct though.  What if, instead of the average, we suggested that
> the user take the highest criteria level and use that as the impact?
> General risk management best practices that I've seen seem to reflect the
> approach of taking the worst-case scenario so this would be in line with
> that and it prevents the value from being diluted by other significantly
> low values.  Anyone out there have opinions on modifying the methodology to
> use this approach instead?


Over the last few years I've put a lot of thought into how one should
combine various risk and mitigating factors elements into a final
score or rating.  You are right that a simple average doesn't
represent the worst of the elements quite as clearly.  However, if you
just take the highest score, you lose information.  What information?
Synergy.  If you have a vulnerability that has multiple impacts, then
you lose the ability to represent all of the lesser, but present, risk
elements.  For instance, XXE generally allows for many types of
attack, but none of these attacks on their own are as bad as something
like SQLi in general, but taken together, we can't ignore the overall
variety of risks.  How should multiple impacts be combined in a
way that still represents contributions from lesser elements without
watering down the most important one?

In the past I've ended up using something like this:

Impact = Sigmoid(Sum(impact_element1 + impact_element2 + ... + impact_elementN))

The Sigmoid function (or variants of it) always returns values between
specific thresholds.  If you play with the numbers for a bit, you realize that
any one element that is high will push the output score high (which is
what you want).  However, multiple moderately high elements can also
push the score higher.  Finally, it combines things asymptotically, so
you don't lose information, it just becomes less important as you
stack up the bad things.

Combining something like Impact with probability of an attack
happening (to create a true risk rating) is yet another challenge...

tim


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