This post was previously published on The New Stack

Regardless of which role a person has in an organization, they will always need access to one or more databases to be able to perform the functions of their job. Whether that person is a cashier at McDonald’s or a technical account manager supporting a Fortune 500 company, data entry and retrieval is core to the services they provide. 

In this article, we will explore some of the benefits that automation brings to an organization’s data security. We will explain how introducing automation into existing database access-control methods can increase efficiency and consistency, and we will also discuss how security-focused automation adds extra layers of protection, like improved data integrity and privacy controls, that help your business stay secure.

Removing Direct Access to Databases

Before modern technologies, all client information was readily available to everyone in the office in a nearby filing cabinet. Later, that same concept was transferred to electronic databases where everyone looks up everything in “the system.” 

This model is arguably easier to build, but it’s not scalable since all the data in each system has to be available to all employees — all of the time. It also increases the amount of manual cross-checking that people need to do between systems. And, don’t forget the risk of data drift as well as the heightened risk of a data leakage.

There are many benefits to automating data access between the people who ask for it and the actual databases themselves. Automated workflows can create a full view and flow of your data by pulling the requested pieces of information from their sources of truth, automatically. 

For example, when you pull an employee profile from an automated system, contact information comes from the HR system, information about currently assigned projects comes from a tool like Jira and the list of corporate assets that the employee has signed out is pulled from a tool like Service Now.

In addition, automated database access-control methods can reduce duplicate data entry, which can in turn reduce errors and drift. In the aforementioned employee profile, for example, the contact information always comes from the HR system, so the payroll system doesn’t need to have its own copy, nor does the helpdesk solution.

The Principle of Least Privilege

Adding a proxy between people and data by using automated workflows also allows you to embed security best practices and other controls. The principle of least privilege is at the core of these data access controls. 

For example, if someone is in a certain sales group, the automated solution can filter out all data that isn’t relevant to their needs. The same goes for people who pick orders in the warehouse; they don’t need to see how much every item costs or which credit cards are being used. You can make this as fine-grained as you want, but it requires that you put data access controls in place to support the safeguards.

A second approach that some organizations take is to log everything and audit it against what people are supposed to be doing rather than block access to the areas that people don’t need to access. This is technically easier to build, but it requires more people to run.

Data Access Approval Requests

The beauty of using security automation as a data broker is that it has the ability to validate data-retrieval requests. This includes verifying that the requestor actually has permission to see the data being requested. 

If the proper permissions aren’t in place, the user can submit a request to be added to a specific role through the normal request channels, which is typically the way to go. With automated data access control, this request could be generated and sent within the solution to streamline the process. 

This also allows additional context-specific information to be included in the data-access request automatically. For example, if someone requests data that they do not have access to within their role, the solution can be configured to look up the database owner, populate an access request and send it to the owner of the data, who can then approve one-time access or grant access for a certain period of time. A common scenario where this is useful is when an employee goes on vacation and someone new is helping with their clients’ needs while they are out.  

Audit Trails

As we mentioned above, some organizations might opt to log everything to track who is doing what. Any good data security automation solution will have the capability of creating extensive audit logs. This audit capability can – and should – be used to track both positive and negative events. A positive event would be like granting Fen permission to see the data that she is requesting, while a negative event would be like refusing Vijay access to the data of a patient who is seen at a different branch of the clinic.

Both types of events can be mined for trends. Every time Netflix alerts you that you’ve logged in from a new location, for example, it’s because its solution logged a positive authentication event and the backend solution then did something with that event when it arrived.

Automated Data Access Workflows

As we outlined above, incorporating secure data-access workflows that are run within automation frameworks into your existing business processes improves the integrity of the data being moved and ensures better privacy controls by showing only the data that is required. It also exposes more metrics, which can be tracked to find more areas that can be optimized and more places where additional automation might add more value. Companies like Torq can help organizations introduce data security automation into their infrastructure. Torq’s solutions are designed to address common scenarios as well as high-value use cases.

This post was previously published on The New Stack

You’ve secured your cloud identities. You’ve hardened your cloud security posture. You’ve configured strong cloud access controls. But there’s still one more thing you need in order to secure your cloud environment: a cloud workload protection platform, or CWPP. 

Cloud workload protection platforms secure the workloads that run on your cloud — which are distinct from the infrastructure, user identities and configurations that form the foundation of your cloud environment.

This article unpacks why a CWPP is a critical ingredient in any cloud security strategy. It explains how CWPPs work, identifies examples of workloads that you can secure with CWPPs  and discusses the importance of automation within the context of a CWPP.

What Is Cloud Workload Protection?

Cloud workload protection is the practice of securing workloads that you deploy in the cloud. In other words, cloud workload protection mitigates risks that exist at the workload level of your cloud environment, as opposed to the infrastructure or configuration level.

The workloads in question could be software, data or a combination thereof that your organization hosts in the cloud. For example, cloud workload protection could apply to the operating system and application running in a cloud-based VM instance, or it could secure the data inside an object storage bucket.

What Is a CWPP?

Tools that provide cloud workload protection are often called cloud workload protection platforms, or CWPPs. Protecting cloud workloads is important because most other types of cloud security practices don’t address workload risks.

Cloud security posture management, or CSPM, alerts you to problems within cloud infrastructure configurations that could create security issues, like IAM policies that provide public access to sensitive data. But CSPM doesn’t cover configuration risks within workloads, such as a lack of encryption for data as it moves within an application.

Likewise, you can track cloud metrics and logs to identify potential security threats. But that data originates mostly from cloud IaaS providers, not individual applications, so it does little to reveal security risks that are specific to applications or data you’ve deployed in the cloud.

CWPP solutions fill these gaps by ensuring that you can protect the code and data that actually run on your cloud, not just the underlying cloud environment.

It’s also worth noting that cloud workload protection platforms help you secure workloads across multiple clouds. Because CWPPs focus on your workload rather than the cloud that hosts it, you can use cloud workload protection to identify security risks in any type of cloud-based workload, even as it moves across clouds.

CWPPs at Work: Some Examples

To contextualize cloud workload protection further, consider how it applies in the following domains.

Containers

When you deploy cloud workloads using containers, you must address special security challenges. You need to make sure that containers can’t run in privileged mode, for example. You must also scan container images for malware.

Cloud workload protection for containers ensures that you have the specific processes in place that are required to protect containerized workloads, independent of other security processes that you apply to your cloud environment.

Kubernetes Security

Kubernetes, too, poses a variety of special security challenges that can only be addressed at the workload level. You must ensure that Kubernetes role-based access control policies and security contexts are configured properly, for instance. You should also use Kubernetes audit logs to monitor for potential security risks that arise within your Kubernetes environment.

Virtual Machine Security

Even if your cloud VM service is properly configured, security issues may lurk inside your VMs. The images you use could contain malware, or just configurations (like the absence of a kernel hardening framework) that lead to a weak security posture. Cloud workload protection alerts you to these risks.

Vulnerability Scanning

Vulnerabilities can arise in any number of places across a cloud environment — within applications, within operating systems, within container images and so on.

Cloud workload protection lets you scan for vulnerabilities across all components and layers of your workloads. Think of it as one-stop shopping for vulnerability discovery and management at the workload level, regardless of which workloads you run or which clouds host them.

Serverless Security

Serverless functions abstract applications from the underlying server environment, which reduces potential attack surfaces. But the functions themselves could still contain vulnerabilities. They could also be configured in ways that increase risks. Cloud workload protection automatically discovers problems like these within serverless functions.

Application Security

Cloud-based applications come in many forms, but they can all contain security risks — such as malware, vulnerable software components and a lack of security controls like encryption. By scanning applications for risks like these, cloud workload protection helps ensure application security across your cloud environment.

Choosing a Cloud Workload Protection Platform 

When integrating cloud workload protection into your cloud security strategy, strive to implement a solution that is:

• Fully automated, because you can’t feasibly manage workload-level security risks by hand.
• Cloud-agnostic, so you can deploy to secure any workload on any cloud.

A service such as Torq.io meets both of these requirements. It lets anyone – not just cybersecurity experts, but any member of your organization – define security rules that workloads must meet. Then Torq automatically and continuously scans your cloud workloads for deviation from these rules.

The result is fully secure and automated cloud workload protection, no matter how your cloud environment is configured or what you run on it.

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.