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Risk profiling

No organization will ever have a perfectly secure application or IT infrastructure. Security requires prioritizing and understanding the risks and tradeoffs associated with different actions. Risk profiling is the process of outlining the organization’s known security risks and its policies and practices related to managing that risk. Every organization must accept some level of risk, but should be clear about how much risk is acceptable. Risk profiling should be done not only for the organization as a whole, but for individual applications. Sensitive workloads, or workloads that are in scope for compliance requirements, have a different risk profile than non-sensitive workloads.

Risk profiling also helps assess the significance of vulnerabilities that exist within the environment. Responding to every vulnerability would be impossible, so a strong security posture requires evaluating the risk of every vulnerability in order to prioritize remediation correctly.

In a distributed, containerized application, it can be difficult to understand and prioritize an application’s risk profile. There might be hundreds of vulnerabilities in any potential application, but all vulnerabilities do not have the same risk. Security risk from a vulnerability depends on factors such as:

  • The severity of the vulnerability
  • Whether or not the application is public-facing
  • If the application is in production
  • Whether the application is in scope for compliance regulations
  • Whether or not the application accesses sensitive data
  • The container’s privilege level
  • The container’s network exposure

While organizations should define ahead of time what level of risk is acceptable, often by establishing internal policies about how quickly vulnerabilities at each severity level must be fixed, risk profiling is not a static exercise. The process of evaluating security risks, particularly in the context of a containerized application, has to happen continually during runtime.

Manually triaging potential security incidents, vulnerabilities and policies is a recipe for error and burnout. Especially at scale, risk profiling often simply isn’t possible to do without relying on automated tools to uncover and prioritize security risks. Successful risk profiling in Kubernetes should make use of Kubernetes’ declarative, contextual data to automate the prioritization process. This allows security teams to focus on fixing the highest-risk deployments first instead of spending time on the risk profiling process.

Ideally, risk profiling can be used as both a reactive and proactive tool. When risks are found and fixed in one deployment, that information can be used to find other deployments with similar risk factors and proactively address the potential security risks ahead of time.

Last updated: May-30-2020