Equilateral of Exclusion Risk

For organizations which don't have the necessary resources to dedicate FTE(s) full time to detection engineering, it can become difficult to judge which test their exclusions and judge their risk. This is where EER can come in and provide some rough guidelines/help:

Equilateral of Exclusion Risk Pyramid.png

The core principles of EER are:

When writing an exclusion, make sure that you validate that the exclusion does not render the detection useless. In other words, make sure that the detection still works as originally intended after adding the exclusion. For more on this topic, see Detection Validation

[1] [2]


Relevant Note(s):


  1. https://www.scythe.io/library/writing-better-security-exclusions-with-eer ↩︎

  2. https://github.com/malwarejake-public/conference-presentations/blob/main/Equilateral of Exclusion Risk Whitepaper.pdf ↩︎