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Enterprise DevSecOps: Security Test Integration and Tooling

Adrian Lane October 14, 2019 2 Comments

In this section we show you how to weave security into the fabric of your DevOps automation framework. We are going to address the questions “We want to integrate security testing into the development pipeline, and are going to start with static analysis. How do we do this?”, “We understand “shift left”, but are the tools effective?” and “What tools do you recommend we start with, and how do we integrate them?”. As DevOps encourages testing in all phases of development and deployment, we will discuss what a build pipeline looks like, and the tooling appropriate for stage. The security tests typically sit side by side with functional and regression tests your quality assurance teams has likely already deployed. And beyond those typical post-build testing points, you can include testing on a developer’s desktop prior to check-in, in the code repositories before and after builds, and in pre-deployment staging areas. Build Process During a few of the calls we had, several of the senior security executives did not know what constituted a build process. This is not a condemnation as many people in security have not participated in software production and delivery, so we want to outline the process and the terminology used by developers. If you’re already familiar with this, skip forward to ‘Building s Security Toolchain’. Most of you reading this will be familiar with “nightly builds”, where all code checked in the previous day is compiled overnight. And you’re just as familiar with the morning ritual of sipping coffee while you read through the logs to see if the build failed and why. Most development teams have been doing this for a decade or more. The automated build is the first of many steps that companies go through on their way toward full automation of the processes that support code development. Over the last several years we have mashed our ‘foot to the floor’, leveraging more and more automation to accelerate the pace of software delivery. The path to DevOps is typically taken in two phases: first with continuous integration, which manages the building and testing of code; then continuous deployment, which assembles the entire application stack into an executable environment. And at the same time, there are continuous improvements to all facets of the process, making it easier, faster and more reliable. It takes a lot of work to get here, and the scripts and templates used often take months just to build out the basics, and years to mature them into reliable software delivery infrastructure. Continuous Integration The essence of Continuous Integration (CI) is developers regularly check-in small iterative code advances. For most teams this involves many updates to a shared source code repository, and one or more builds each day. The key is smaller, simpler additions, where we can more easily and quickly find code defects. These are essentially Agile concepts, implemented in processes which drive code, rather than processes that drive people (such as scrums and sprints). The definition of CI has evolved over the last decade, but in a DevOps context CI implies that code is not only built and integrated with supporting libraries, but also automatically dispatched for testing. Additionally, DevOps CI implies that code modifications are not applied to branches, but directly into the main body of the code, reducing the complexity and integration nightmares that can plague development teams. This sounds simple, but in practice it requires considerable supporting infrastructure. Builds must be fully scripted, and the build process occurs as code changes are made. With each successful build the application stack is bundled and passed along for testing. Test code is built before unit, functional, regression, and security testing, and checked into repositories and part of the automated process. Tests commence automatically whenever a new application bundle is available, but it means the new tests are applied with each new build as well. It also means that before tests can be launched test systems must be automatically provisioned, configured, and seeded with the necessary data. Automation scripts must provide monitoring for each part of the process, and communication of success or failure back to Development and Operations teams as events occur. The creation of the scripts and tools to make all this possible requires Operations, Testing and Development teams to work closely together. The following graphic shows an automated build pipeline, including security test points, for containers. Again, this level of orchestration does not happen overnight, rather an evolutionary process that take months to establish the basics and years to mature. But that is the very essence of continuous improvement. Continuous Deployment Continuous Deployment looks very similar to CI, but focuses on the releasing software to end users rather than building it. It involves similar packaging, testing, and monitoring tasks, with some additional wrinkles. Upon a successful completion of a build cycle, the results feed the Continuous Deployment (CD) process. CD takes another giant step forward for automation and resiliency but automating the release management, provisioning and final configuration for the application stack, then launches the new application code. When we talk about CD, there are two ways people embrace this concept. Some teams simply launch the new version of their application into an existing production environment. The CD process automates the application layer, but not the server, data or network layers. We find this common with on-premise applications and in private cloud deployments, and some public cloud deployments still use this model as well. A large percentage of the security teams we spoke with are genuinely scared of Continuous Deployment. They state “How can you possibly allow code to go live without checks and oversight!”, missing the point that the code does not go live until all of the security tests have been passed. And some CI pipelines contain manual inspection points for some tests. In our experience, CD means more reliable and more secure releases. CD addresses dozens of issues that plague code deployment — particularly in the areas of error-prone manual changes, and discrepancies in

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