The 5 SaaS Data Loss Prevention Best Practices You MUST Implement

Data loss prevention: What you need to know

Data loss refers to when a company’s internal data is accidentally exposed to the public. This could happen in a number of ways, such as via social engineering or phishing attacks, insiders acting nefariously, or a classic brute-force cyberattack that sees bad actors penetrate your company’s systems and steal information.

The term data loss prevention (DLP) refers to cybersecurity strategies that organizations can implement to ensure that sensitive data, such as financial information, customer details, trade secrets, and other critical assets, are kept secure. Generally speaking, DLP solutions detect and notify security teams about potential breaches, and can help prevent sensitive data from being extracted or exported.

Data loss prevention is especially important in SaaS environments, because SaaS solutions allow users to access, view, and share data quicker than ever before. While this is amazing when it comes to streamlining workflows and easing collaboration, it also means that more and more data is being shared between users on a near-constant basis - and that’s often not happening in a secure way.

It’s clear that in today’s digital landscape, companies must prioritize robust, effective data loss prevention, or risk the disastrous consequences that accompany a data breach.

Putting the following data loss prevention best practices into place at your business can help secure your SaaS data, ensuring that your business stays in compliance, retains customer and investor trust, and keeps your internal data safe from bad actors.

At a glance, data loss prevention best practices include:

1. Use comprehensive data classification frameworks
2. Aim for near real-time detection and alerts
3. Involve the end user
4. Check for (and fix!) any misconfigurations
5. Follow the anomalies

But what do these mean, practically speaking?

Let’s break down how to implement these data loss prevention best practices within your business.

1. Use comprehensive data classification frameworks and tools

In order to protect your data, you need to define and identify it. You can’t safeguard data if you’re unaware of exactly where it’s located, nor do you know just how sensitive that data is.

There are two main aspects to comprehensive data classification:

Assess data sensitivity accurately

It’s critical to correctly classify sensitive data. Sensitive data discovery tools can help you locate and label assets which contain critical internal information, but not all of these solutions are created equal.

When assessing sensitive data, it’s crucial to minimize misidentifications stemming from false positives and false negatives. Otherwise, you can end up bogged down in the time-consuming process of sorting out false alarms from real concerns, and even miss existing sensitive data exposures.

Assess potential impact if this data is compromised

The level of sensitivity of a specific data set is a major factor in how swiftly you need to respond. For example, the exposure of employees’ starting dates at your company is problematic - but improper sharing of an asset with customers’ social security numbers and birthdays requires a much more immediate correction. 

You need to assess in a way that helps you prioritize where protection is most needed, and establish automated remediation protocols that provide immediate action in scenarios where every minute counts.

2. Aim for near real-time detection and alerts

When it comes to data, when you snooze, you lose. The longer that an exposure goes undetected, the higher the chances that your company will face serious problems stemming from a breach. 

When it comes to SaaS, you need to ensure that detection of potential exposures happens as quickly as possible. But it’s important to note that within a SaaS environment, instant, real-time detection is impossible.

Why?

Real-time detection of sensitive data exposures requires an agent or proxy DLP, which essentially serves as a checkpoint between your device and the cloud. Just like checkpoints on the road, they cause data to slow down when passing through them - which is a major drawback in a Saas environment.

Agent or proxy DLP solutions slow down SaaS solutions, to the point where their lightning-fast nature is compromised and users’ workflows are hindered. The whole reason why organizations have embraced SaaS apps is the way they make sharing data and collaboration fast and easy, so DLP solutions that use agents or proxies are out of the question for most enterprises.

On the other end of the spectrum, DLP solutions that rely on API pings and log ingestion are far too slow to be effective. While they don’t impact user experience while working, they fail to inform security teams in a timely manner or flag potential issues quickly enough for decisive, corrective action.

You need an event-based API DLP solution, with push notifications that let your security team know when there’s an urgent exposure that needs to be corrected or trigger a corrective workflow to take care of the exposure without the need for human involvement.

3. Involve the end user

An incredible number of data exposure issues can be traced not to external cybercriminals, but to your own employees. Oftentimes, a user shares data in a risky way, without understanding the potential ramifications of their actions.

Your employees are your first line of defense against data leaks and breaches. Educating your teams on why a share was risky, then involving them in the remediation process, creates a security culture of accountability.

This user-based approach helps your business teams understand the ground rules that will help them act wisely in the future, preventing and minimizing data loss risk from insiders. 

When your employees understand the reasons why they should share data on a strictly need-to-know basis, as well as gain critical perspective into the potential results of a data breach, they are far more likely to proceed with caution in the future.

4. Check for (and fix!) any SaaS misconfigurations

Even if you do all the above, a SaaS misconfiguration can prove to be the fatal mistake putting your business’ sensitive data at risk. For example, if your SaaS is mistakenly configured to allow non-signed-in access, you just left a backdoor wide open to allow cybercriminals and other bad actors to access, view, and share your crucial internal assets.

Configurations are important for all organizations, but they are especially critical when it comes to businesses working in highly regulated industries, such as healthcare or finance. Many companies operating in these sectors are obligated to stay in compliance with strict data protection regulations - and misconfigurations may mean that they are in violation of said requirements.

It’s essential to check for misconfigurations against industry best practices, compliance regulations, and other standards for the space in which your business operates. It’s also important to remember that misconfiguration monitoring isn’t a one-time task; you need to constantly review to ensure that in your dynamic, fluid SaaS environment, new misconfigurations aren’t being created.

5. Follow the anomalies

If an insider at your organization is behind a data loss threat, they will be significantly more difficult to detect and prevent than an external cybercriminal. Unlike an outside bad actor, an insider at your business does enjoy legitimate access to your systems and at least some of the sensitive data within your SaaS environment.

Protecting your organization from insider threats is predicated on detecting and identifying anomalies. This means responding to red flags raised by users engaging in suspicious or unusual patterns of activity. Some questions you can ask to detect insider threats include:

• Is the user doing more public/external sharing of sensitive data than usual?
• Is a particular sensitive asset being interacted with more than usual?

Business context is the key to effective anomaly detection. Take, for example, the context of a user who was just given notice. If you see them engaging in a burst of public sharing, you can understand that this action is far more suspicious than if it was coming from a user who isn’t leaving your organization anytime soon.

DoControl’s SaaS Data Loss Prevention solution utilizes a number of advanced technologies, including NLP and context-based detection, to swiftly inform you about potential data breaches and exposures. To learn more, talk to us today or schedule a demo.