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  • SaaS data sprawl refers to the ongoing proliferation of sensitive data in cloud apps like Slack, GitHub, Microsoft Teams and more.
  • It’s a big problem for organizations across industries. Risks include data leakage, data theft and, of course, consequent compliance fines.
  • In-built security tools in the likes of Slack and GitHub aren’t granular enough to discover sensitive information in all its formats, which contributes to the issue.
  • To get a handle on SaaS data sprawl, use a cloud-based data loss prevention (DLP) solution that leverages natural language processing and automation. 
  • This is the best way to discover, classify and secure sensitive data contextually and in all formats across different cloud apps.

Software-as-a-service (SaaS) platforms are wonderful for boosting employee productivity and collaboration. Apps like Slack, Microsoft Teams and Google Workspace are essentially a prerequisite in the modern workplace, facilitating remote and hybrid work setups, while empowering employees to enhance efficiency. 

However, while executives and employees love SaaS, security teams often have a different opinion. These apps are notoriously difficult to secure from a data standpoint. Just look at the recent data breaches involving Uber, AstraZeneca and Dropbox. All these incidents stemmed from SaaS apps! 

Unfortunately, the nature of cloud apps also tends to be their downfall when it comes to data security. Effortless collaboration, uploading and downloading, and remote access make it extremely difficult for security teams to find and keep track of sensitive data in the cloud–especially in organizations that use multiple SaaS platforms. 

We call this phenomenon SaaS data sprawl. Below, we’ll teach you how to get a handle on it. 

What is SaaS data sprawl?

SaaS data sprawl refers to the ongoing proliferation of sensitive data in cloud apps like Slack, GitHub, Microsoft Teams and more. It’s a problem that’s been growing for years, accelerated by the COVID-19 pandemic. These days, employees rely almost exclusively on cloud apps to upload, edit and share information with their colleagues, partners and other third-parties

Often, they share this data in unstructured formats, meaning low-grade security tools can’t detect it. Over the years, the problem of exposed sensitive information in cloud apps has exploded. Research shows that most companies have a $28 million data breach risk from sensitive information left unsecured in SaaS apps. 

What are the risks of SaaS data sprawl? 

SaaS data sprawl is a big problem for organizations across industries. If you don’t know where your sensitive data is, you can’t protect it effectively. Information like PII or PHI could potentially be exposed to the public in a Google Sheet or GitHub repository, or shared inappropriately with unauthorized parties. 

Should a malicious actor get their hands on this information, they could use it as the basis for fraud or more complex attacks on your organization. We have to remember, too, that apps like Slack and Teams are a hot target for attackers. In fact, Slack published news of a successful breach attempt just last month! 

Attackers aren’t just trying to break into Slack’s infrastructure, they’re also using legitimate employee accounts to break into your cloud apps. Research shows that 80% of data breaches leverage weak and compromised passwords. The very nature of SaaS apps—that they can be accessed anywhere, at any time—makes them perfect for these kinds of attacks. 

Then, of course, we need to think about compliance. Under laws like HIPAA, CCPA, GBLA and GDPR, organizations must abide by specific rules to protect the confidentiality, availability and integrity of information. SaaS data sprawl inherently undermines this, putting organizations in a position where they can’t say with confidence that their sensitive information is secure. 

Native security solutions aren’t enough

Clearly, getting a handle on SaaS data sprawl is vital to maintaining a solid cloud security posture. However, if you think that the likes of Slack and GitHub’s in-built security controls are enough to uncover sensitive information in your SaaS apps, you need to think again. 

Unfortunately, these applications’ native security tools are foundational in nature. They tend to produce a lot of false positives and miss out on sensitive information in unstructured formats. Sure, they can go a little way to improve data security, but they won’t give you the granular visibility and control you need to truly get SaaS data sprawl under control. 

Moreover, in-built security tools only work within their own platform, meaning you’ll have to deploy and manage a whole host of disparate tools across your different SaaS applications. This approach is not only cumbersome, but it’s extremely error-prone. 

After all, even the most seasoned security expert would find it difficult to learn and use numerous different security consoles – especially as the major SaaS providers frequently release updates that change the admin interface and configurations. 

How to overcome SaaS data sprawl 

While SaaS data sprawl is undoubtedly a huge issue for organizations, there is a way forward. By leveraging the right strategy, combined with the right tools for the job, you can bring much-needed visibility to your cloud apps and finally get control over your sensitive data.

Here’s how to do it. 

  1. Embrace data discovery 

As the name suggests, data discovery is the process of discovering sensitive information across your cloud apps. Discovery should be a continuous process, rather than a one-off. Use tools that leverage automation and natural language processing (NLP) to discover data in all its formats, instead of traditional database fingerprinting solutions. 

  1. Classify your sensitive information 

Data classification tools enable you to categorize your information based on its risk score and sensitivity. There are numerous data discovery and classification tools out there, each with different approaches. Some, for example, use regexes to assign sensitive information to a category, but these solutions tend to result in a high number of false positives. 

Polymer data loss prevention (DLP), on the other hand, uses machine learning and NLP to intelligently discover and classify sensitive information across your SaaS apps, based on pre-built policy templates for common compliance regimes like HIPAA, GBLA and GDPR. The result is data classification you can count on, with high degrees of accuracy and precision.

3. Secure your data 

Ideally, you’ll have leveraged a tool that can discover, classify and secure your data all in one. Once you’ve put the tool into action, watch as it autonomously starts safeguarding your sensitive information in SaaS apps: preventing employees from sharing it unsafe ways, blocking suspicious users from accessing it, and redacting information that’s not legally allowed to be in your cloud apps. 

Quickly, your tool will begin to chip away at SaaS data sprawl, empowering you to maintain control over your sensitive data so you can meet compliance objectives and avoid a costly data breach. 

Curious about the state of SaaS data sprawl in your cloud apps? Try a free risk scan today to discover the extent of at-risk sensitive data in Slack, Teams or Google Workspace.

Polymer is a human-centric data loss prevention (DLP) platform that holistically reduces the risk of data exposure in your SaaS apps and AI tools. In addition to automatically detecting and remediating violations, Polymer coaches your employees to become better data stewards. Try Polymer for free.


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