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Building Security Into DevOps: Security Integration Points

Adrian Lane October 3, 2015 No Comments

A couple housekeeping items before I begin today’s post – we’ve had a couple issues with the site so I apologize if you’ve tried to leave comments but could not. We think we have that fixed. Ping us if you have trouble. Also, I am very happy to announce that Veracode has asked to license this research series on integrating security into DevOps! We are very happy to have them onboard for this one. And it’s support from the community and industry that allows us to bring you this type of research, and all for free and without registration. For the sake of continuity I’ve decided to swap the order of posts from our original outline. Rather than discuss the role of security folks in a DevOps team, I am going to examine integration of security into code delivery processes. I think it will make more sense, especially for those new to DevOps, to understand the technical flow and how things fit together before getting a handle on their role. The Basics Remember that DevOps is about joining Development and Operations to provide business value. The mechanics of this are incredibly important as it helps explain how the two teams work together, and that is what I am going to cover today. Most of you reading this will be familiar with the concept of ‘nightly builds’, where all code checked in the previous day would be 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 towards full automation of the processes that support code development. The path to DevOps is typically done in two phases: First with continuous integration, which manages the building an testing of code, and then continuous deployment, which assembles the entire application stack into an executable environment. Continuous Integration The essence of Continuous Integration (CI) is where developers check in small iterative advancements to code on a regular basis. For most teams this will involve many updates to the shared source code repository, and one or more ‘builds’ each day. The core idea is smaller, simpler additions where we can more easily – and more often – find defects in the code. Essentially these are Agile concepts, but implemented in processes that drive code instead of processes that drive people (e.g.: scrums, sprints). Definition of CI has morphed slightly over the last decade, but in context to DevOps, CI also implies that code is not only built and integrated with supporting libraries, but also automatically dispatched for testing as well. And finally CI in a DevOps context also implies that code modifications will not be applied to a branch, but into the main body of the code, reducing complexity and integration nightmares that plague development teams. Conceptually, this sounds simple, but in practice it requires a lot of supporting infrastructure. It means builds are fully scripted, and the build process occurs as code changes are made. It means upon a successful build, the application stack is bundled and passed along for testing. It means that test code is built prior to unit, functional, regression and security testing, and these tests commence automatically when a new bundle is available. It also means, before tests can be launched, that test systems are automatically provisioned, configured and seeded with the necessary data. And these automation scripts must provide monitored for each part of the process, and that the communication of success or failure is sent back to Dev and Operations teams as events occur. The creation of the scripts and tools to make all this possible means operations, testing and development teams to work closely together. And this orchestration does not happen overnight; it’s commonly an evolutionary process that takes months to get the basics in place, and years to mature. Continuous Deployment Continuous Deployment looks very similar to CI, but is focused on the release – as opposed to build – of software to end users. It involves a similar set of packaging, testing, and monitoring, but with some additional wrinkles. The following graphic was created by Rich Mogull to show both the flow of code, from check-in to deployment, and many of the tools that provide automation support. Upon a successful completion of a CI cycle, the results feed the Continuous Deployment (CD) process. And CD takes another giant step forward in terms of automation and resiliency. CD continues the theme of building in tools and infrastructure that make development better _first, and functions second. CD addresses dozens of issues that plague code deployments, specifically error prone manual changes and differences in revisions of supporting libraries between production and dev. But perhaps most important is the use of the code and infrastructure to control deployments and rollback in the event of errors. We’ll go into more detail in the following sections. This is far from a complete description, but hopefully you get enough of the basic idea of how it works. With the basic mechanics of DevOps in mind, let’s now map security in. The differences between what you do today should stand in stark contrast to what you do with DevOps. Security Integration From An SDLC Perspective Secure Development Lifecycle’s (SDLC), or sometimes called Secure Software Development Lifecycle’s, describe different functions within software development. Most people look at the different phases in an SDLC and think ‘Waterfall Development process’, which makes discussing SDLC in conjunction with DevOps seem convoluted. But there are good reasons for doing this; Architecture, design, development, testing and deployment phases of an SDLC map well to roles in the development organization regardless of development process, and they provide a jump-off point for people to take what they know today and morph that into a DevOps framework. Define Operational standards: Typically in the early phases of

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