This post was previously published on The New Stack

Today, anyone can contribute to some of the world’s most important software platforms and frameworks, such as Kubernetes, the Linux kernel or Python. They can do this because these platforms are open source, meaning they are collaboratively developed by global communities.

What if we applied the same principles of democratization and free access to cybersecurity? In other words, what if anyone could contribute to security initiatives and help build a cybersecurity culture without requiring privileged access or specialized expertise?

To explore those questions, it’s worth considering the way that open source has democratized software development and comparing it to the potential we stand to realize by democratizing security. 

Although the connection between open source software and democratized security only goes so far, thinking from this angle suggests a new approach to solving the cybersecurity challenges that have become so intractable for modern businesses.

So, let’s take a look at how open source democratized development and what it might look like to do the same thing for security.

Open Source and the Democratization of Software Development

Until the origin of GNU and the Free Software Foundation in the mid-1980s, no one thought of software as something that anyone could help design or create. Instead, if you wanted to build software, you needed membership in an elite club. You generally had to be a credentialed, professional programmer, and you typically had to have a job that put you in a position to create software.

GNU began to change this by allowing volunteers to build software, like the GNU C compiler, that eventually became massively important across the IT industry. Then, in the early 1990s, the advent of the Linux kernel project changed things even more. The Linux kernel was created by an undergraduate, Linus Torvalds, whom no professional programmer had ever heard of. If a twenty-something non-professional Finnish student could create a major software platform, it was clear that anyone could.

Today, anyone still can. You don’t need a special degree or professional connections to contribute to a platform like Kubernetes, as thousands of independent programmers do. Nor do today’s users need to rely on a handful of elite programmers to write the software they want to use. They can go out and help write it themselves via participation in open source projects. (Of course, the big caveat is that you need special skills to write open source software. But we’ll get to that point later.)

As a result of this democratization of development, it has become much easier for users to obtain the software they’d like to use, as opposed to the software that closed-source vendors think they should use. Open source has also turned out to make software development faster, and it tends to lower the overall cost of software development.

Towards an Open Source Cybersecurity Framework

Now, imagine what would happen if the world of cybersecurity were democratized in the way that software development has been democratized by open source.

It would create a world where security would cease to be the domain of elite security experts alone. Instead, anyone would be able to help identify the security problems that they face, then build the solutions they need to address them, just as software users today can envision the software platforms and features they’d like to see, then help implement them through open source projects.

In other words, users wouldn’t need to wait on middlemen — that is, the experts who hold the reins — to build the security solutions they needed. They could build them themselves.

That doesn’t mean that security experts would go away. They’d still be critical, just as professional programmers working for major corporations continue to play an important role alongside independent programmers in open source software development. 

But instead of requiring small groups of security specialists to identify all the cybersecurity risks and solve them on their own, these tasks would be democratized and shared across organizations as a whole.

The result would be a world where security solutions could be implemented faster. The solutions would also more closely align with the needs of users, because the users would be building them themselves. 

And security operations would likely become less costly, too, because the work would be spread out across organizations instead of being handled only by high-earning security professionals.

The Differences Between Open Source and Security Democratization

It’s important, of course, not to overstretch the analogy between open source democratization and security democratization. In particular, there are two main differences between these concepts.

One is that, whereas open source software can be built and shared by communities at large, security is something that is mostly used only internally. The security workflows that users might define using security democratization tools would only apply inside their own companies, rather than being shared with users at large.

The other, bigger limitation is that it takes special skills to build software. While it’s possible for non-coders to contribute to open source projects by doing things like writing documentation or designing artwork, most contributions require the ability to code.

In contrast, security democratization doesn’t have to require specialized security skills on the part of users. By taking advantage of no-code tools that let anyone define, search for and remediate security risks, businesses can democratize their security cultures without having to teach every employee to be a cybersecurity expert.

What this means is that, although it may seem far-fetched at first glance to democratize security, the means for doing so — no-code automation frameworks — are already there. They just need to be placed in the hands of users.

Conclusion

Over the course of a generation, the open source software movement radically transformed the way software is built. Although plenty of closed-source code continues to exist, programmers today can contribute to critical software platforms that operate on an open source model without requiring special connections or credentials. The result has been software that better supports users, and that takes less time and money to build.

Businesses can reap similar benefits in the realm of security by using no-code security automation tools to democratize their approach to security. When anyone can define security requirements and implement tools to meet them, security becomes more efficient, more scalable and better tailored to the needs of each user or group.

When we discuss cybersecurity and the threat of cyber attacks, many may conjure up the image of skillful hackers launching their attacks by way of undiscovered vulnerabilities or using cutting-edge technology. While this may be the case for some attacks, more often than not, vulnerabilities are revealed as a result of careless configuration and inattention to detail. Doors are left open and provide opportunities for attacks. The actual exposure in our systems is due to phishing schemes, incorrectly configured firewalls, overly permissive account permissions, and problems our engineers don’t have time to fix.

This article will introduce you to an actionable strategy to protect your environment using Cloud Security Posture Management (CSPM). We’ll describe what CSPM is and why it’s essential for your organization to implement it. We’ll also cover some of the reasons why organizations fail to implement such a strategy effectively. Finally, we’ll explore practical and straightforward approaches that your organization can pursue right away to protect your digital assets and your consumer’s data.

What Is Cloud Security Posture Management (CSPM) and Why Is It Important?

When compared with a traditional data center, the cloud offers significant advantages. Unfortunately, our approach to securing a conventional data center doesn’t translate well to the cloud, so we need to recalibrate how we think about and enforce security. CSPM or Cloud Security Posture Management is the process of automating the identification and remediation of security risks across our ecosystem.

Cloud providers such as Amazon Web Services (AWS) and Google Cloud provide an expansive range of services and capabilities. While the cloud host takes care of patch management and ensuring availability, it’s the user’s responsibility to protect their data and services from malicious actors. In recent years, several high-profile data breaches have come about due to improperly configured storage buckets or through accounts with more access than required. 

Why Is CSPM Challenging and What Does It Cover?

The public cloud offers more than simply virtual servers and databases. Modern applications are composed of a multitude of services, each with unique permissions and access-control policies. The age of DevOps requires development teams to have access to a wide range of permissions and the organization’s trust that they’ll use that responsibility carefully. Unfortunately, mistakes happen; and especially in a model where distributed user accounts and systems constantly evolve, configurations and changes require a monumental effort to manage and monitor these accounts.

Visibility would be the core principle if we had to simplify the challenges of protecting your digital ecosystem into a single concept. A comprehensive CSPM strategy consists of providing visibility into all aspects of your environment. This visibility includes:

• Account and Permission Management
• Service Configuration
• Patch and Security Update Management
• Effective and Efficient Problem Resolution
• Vulnerability Scans of Applications and Third-party Libraries.

A CSPM solution provides visibility into each of these aspects, and tracks anomalies and suspicious changes as they happen. A CSPM automatically remediates potential problems and threats where possible, and raises appropriate alerts if automatic remediation isn’t available.

Implementing a CSPM Strategy

Implementing a successful CSPM strategy may seem a little daunting given the scope of what the solution needs to cover and the importance of achieving comprehensive coverage of your entire ecosystem. Most of the large cloud providers have services that can monitor changes within their environments. While they effectively monitor most services within their domain, they are limited to those same services. Ideally, you want to partner with an organization that has invested time and resources into CSPM solutions that can span the breadth of your organization.

Equally important to the coverage of the solution is the capacity for automation. Automated processes can be used for monitoring, analyzing, and remediation when possible. Given the dynamic nature of most environments, manual tracking may not be able to keep up with changes as your organization grows. Additionally, as with configuration and operational tasks, there is always the chance for human error, resulting in missed alerts or worse problems that are identified and then forgotten, as additional tasks and issues arise.

A successful CSPM solution uses automation extensively, monitoring and detecting problems and automatically remediating such problems or isolating them until the appropriate personnel can address them.

Practical CSPM Use Cases

Implementing an automated CSPM solution will alert you to potential vulnerabilities in your systems, misconfigured resources, and potentially harmful changes. Still, there is more to a CSPM solution than just detection and reporting.

Once the CSPM solution discovers an issue with your environment, a well-designed system will also assist with managing issues, performing such tasks as:

• Filtering issues by priority and severity so that you can devote resources to the most critical issues first.
• Organizing related issues and ensuring that issues aren’t duplicated across multiple systems.
• Periodically performing additional scans and tests to determine whether vulnerabilities and issues have already been addressed.
• Managing the assignment of issues to the appropriate owner within the organization and escalating tickets that might not be receiving proper attention.

In a nutshell, your CSPM solution should remove much of the guesswork associated with security scans, configuration management, and issue resolution. The system should handle many mundane tasks and only engage your engineers when necessary. This approach will free you and your organization to focus on delivering additional value to your customers and improving your existing offerings.

Learning More

As leaders in the field of automation, Torq is uniquely positioned to help you find and implement a CSPM solution that addresses your organization’s needs. Reach out to Torq to learn more about the services they offer and how they can work with you to improve the security of your systems and manage your cloud environments.

Recently, I started to read the invaluable book Software Engineering at Google. It’s a great book by Google, describing their engineering practices across many different domains.

One of the first chapters discusses the matter of making a “scalable impact,” which I find very interesting, and something that I believe has been overlooked by many organizations.

What is Scalable Impact?

Creating “scalable impact” is making a change that will improve your organization’s engineering practices without investing unnecessary effort for each new team member.

First, let’s review some examples that don’t demonstrate “scalable impact”.

What Hinders Scalable Impact?

1. Code Reviews

Code reviews have many advantages. Code reviews allow teams to share knowledge, catch design flaws, enforce common patterns and practices. Seems like a good idea, right? Well, the problem is —these don’t scale. The larger the team, the larger the effort, and this scales linearly with each new developer.

2. Manual QA

Similar to code reviews, manual QA for each release doesn’t scale. As a team grows, release velocity increases. As release velocity increases, more releases require manual QA —creating a bottleneck and single point of failure.

3. Manual deployment approvals

In many organizations, only a small, dedicated team can perform the actual deployment to production. Just as with manual QA, increased release velocity brought on by team growth turns this into a function that blocks scale.

4. Excessive documentation

Documentation is useful —it allows teams to share knowledge in-house and publicly without having to be there to personally explain things. But, as you create more and more documentation, there are two downsides: 1. You have to keep it up to date 2. Devs need to read it. And we DEVs, (or we as human beings…) can be lazy. We don’t like to do things that require a ton of effort; we love to take the easy way, if possible. We don’t read the docs and we definitely don’t update the docs if we change something. So in many cases, the end result is a waste of time, or an old and out-of-date document that no one even reads. In the end, the conventions you created may not be used anywhere.

How to Make Scalable Impact

Okay, so how exactly do you make scalable impact then? At Torq, we’ve adopted a number of practices that help us realize scalable impact and set our team up for successful growth. I’ll highlight each of these examples below, and talk through the details of them in a future post.

1. Centralized Linting

Let’s say that one day you decide all your developers have to avoid using errors.Wrapf and instead use fmt.Errof. At that point, most organizations tend to create a new convention page and write that down there. Later, a nice Slack message will be sent to the #rnd channel. Something like this:

“Hi there, we decided to stop using errors.Wrapf, please use only fmt.Errorf from now on. See the conventions here: …”

How many of you are familiar with this practice? If you’re familiar with it, you probably also realize this won’t work. 

Why, you ask? Because human beings don’t work well with rules, unless they’re reinforced. That wiki page describing the newest convention? It’s already depreciated the moment you wrote it.

So how do you solve that issue, then? My advice: Come up with a centralized linting solution. By centralized, I mean one that immediately affects all new builds, without any changes to your projects.

Returning to the example above, with centralized linting, you change your global linting rules. That means you immediately avoid any new usages of the old convention. No questions asked, and nothing to remember. It’s as simple as that — the PR won’t be mergeable unless the new convention is used. No documentation to maintain, no convention to teach new recruits. Your documentation is now the linting rules code. 

There you have it: Scalable Impact.

At Torq we use ReviewDog to achieve this, which I’ll describe in detail in a later post.

2. Unified/Reusable CI pipeline

Another story you may all be able to relate to: One day your CTO reaches out and asks for the full list of dependency licenses used across ALL your codebase.

So then you start googling and you find an awesome tool doing exactly that. But now you’re stuck. You have to run that tool and collect the results for ALL your projects, and we’re talking about minimum 50+ (or more for larger organizations).

Here’s the (happy!) twist: With unified CI Pipelines, this task becomes easy.

By unified, I mean maintaining a common baseline for all your CI pipelines. One that you can change from a single location, by doing only a single change.

To solve the above issue you will add that logic for license extraction to your common base and execute that as part of your CIs. Then, just let your CI do the rest.

Another (real) example: Let’s say you want to change your unit-testing runner.

You decided that gotestsum is the real deal, and your teammates chime in: “That old go test is useless. We MUST move to the new shiny tool.”

More opportunity for scalable impact: Just change the test part of your unified CI, and all your projects will use gotestsum instead of go test. 

To achieve this, we use Makefile inheritance and CircleCI orbs. Again, I’ll dig into this in a future post.

3. Automated E2E Tests

Nothing new here —each and every deployment should pass the same test suite. Again, every deployment.

Green -> deployed

Red -> rolled back

No “sanity suite”,  no “Ah, this one is flaky, you can go ahead and deploy”. No user intervention. Of course, this means your complete E2E suite should be fast and reliable (I use under 5 minutes as a rule of thumb).

Adopt the “Beyonce Rule”

“If you liked it then you shoulda put a ring on it!” said the mighty Beyonce in her famous song, Single Ladies (Put a Ring on It).

Later, malicious DEVs took that line and rephrased it to “if you like it, put a [test, lint, e2e, ticket] on it!”

Put plainly, new investments or changes require you to put the right framework in place to make them scalable. Getting started with this requires having the right tools; but after that, it’s easy to adopt the practice.

Found a new issue that can be caught by a listing rule? Easy! Add the lint rule to your centralized linting solution.

Want to add a new tool that tracks the test coverage? Simple! Change the unified CI configs.

The upfront investment here helps the entire team grow, and delivers returns (in reduced toil, and increased velocity) over time.  Applying the Beyonce Rule turns your team from Danity Kane to Destiny’s Child. It becomes super easy to add/change the existing conventions and processes. The Beyonce Rule is cost-effective and can be easily adopted.