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Data assets are often a company’s primary asset. If they become lost, stolen or exposed, however, they almost immediately turn into a liability that can cost millions to remediate.
SaaS systems in particular are prone both to rapid accumulation of data assets and to inadvertent or intentional exposure of those assets. In a 2023 analysis we did of our client base, companies with 1000 employees or more averaged 22.8M SaaS assets, with 189% YoY asset growth. It is for this reason that SaaS DLP (data loss prevention) is so critical.
This post will take a closer look at SaaS DLP: its importance, challenges, best practices, compliance considerations and what to look for in order to choose the right SaaS DLP solution for your organization.
What is SaaS Data Loss Prevention?
SaaS DLP is a set of strategies, tools and processes designed to protect the sensitive data found in your SaaS applications from unauthorized access, exposure or loss. SaaS DLP is a comprehensive approach that includes the identification of sensitive data, monitoring the use and movement of data, and enforcing relevant security policies.
Why is SaaS DLP important?
SaaS DLP is important because the loss or exposure of sensitive data contained within your SaaS ecosystem can have negative ramifications for your organization on the legal, financial, reputational and strategic levels.
Legal ramifications - if the data is subject to industry regulations and standards for which compliance is mandatory, its exposure can result in audits, class action suits, legal penalties and fines from regulatory bodies.
Financial ramifications - in addition to fines resulting from regulatory compliance violations, the loss or exposure of sensitive data can cause both direct and indirect financial consequences, including the costs incurred to restore the data, deal with or otherwise compensate for the loss.
Reputational ramifications - when an organization needs to admit to sensitive data loss or exposure, their reputation automatically takes a hit. Both current and potential customers, clients and partners will be more cautious when it comes to entrusting their data to this organization.
Strategic ramifications - the loss of IP or the exposure of a confidential go-to-market strategy can ruin or detract significantly from the organization’s ability to implement its current business strategy.
Common Challenges in SaaS DLP Adoption
When organizations make the move to adopt SaaS DLP, there are several common challenges they encounter. They include:
Pervasive user access to and control of data assets
The design of SaaS systems makes it easy for end users to access, modify and share data assets. This ease is intentional, because SaaS applications’ value lies in the productivity they make possible. But that can make control over SaaS data assets feel like a tug-of-war between users and the SaaS DLP policies.
The major challenge to SaaS DLP adoption here is finding a way to implement SaaS DLP such that it prevents data exposure without preventing smooth user workflow.
Prevalent false positives and negatives in data classification
The first step in effective SaaS DLP is accurate identification of data that needs protection. But sensitive data discovery tools often have issues with accuracy. On the one hand you have tools based on regular expressions. Those “discover” a statistically significant percentage of false positives: flagged as sensitive when it wasn’t really sensitive. False positives become false alarms that take up your information security team’s time and resources - and contribute to alert fatigue.
On the other hand, tools that use exact data match or fingerprinting can run into the opposite issue: false negatives. The net is cast too narrowly, and real sensitive data is missed and not protected, becoming a security hazard.
This challenge makes it difficult to prove that SaaS DLP is delivering value, and not just sending security team members off on wild goose chases or encouraging them to sleep at their posts.
Distinguishing between acceptable business use and threat actions
No organization has a SaaS DLP policy that states: “users cannot share sensitive information.” Of course users need to share sensitive information over the course of a normal business day:
- the marketing team needs to pass the names and phone numbers of potential leads to sales
- nurses need to share their patient observations with doctors
- an enterprise’s accounting department needs to send relevant financial documents to an external audit team
So how can you tell which modification and/or sharing of sensitive data assets is for the organization’s benefit or detriment?
These fine distinctions are critical to the process of SaaS DLP. Crack down on what turns out to be acceptable business use - and you’re shooting yourself in the foot. Look away from what turns out to be a data breach - and your inaction puts your organization at serious risk of multiple kinds of damage.
But making these distinctions is a significant challenge for a SaaS DLP system that can only identify user identities and their behaviors, but not their intent.
What are the best practices for SaaS DLP?
To have your SaaS DLP actually succeed in preventing data loss, apply the following best practices:
Balance real-time protection with maintaining business flow
SaaS DLP that is truly real-time would need to check all data modifications and shares before they are implemented. This is the equivalent of a security guard standing at the exit to a store, checking every shopper’s bag before they leave to make sure they haven’t stolen anything. That may be relevant for a small boutique shop without too many customers, but if you tried to prevent shoplifting that way at Target, Walmart, or any high-traffic, large-purchase store, you would have a perpetual traffic jam at the exit, and customers would be very, very unhappy..
SaaS works the same way. Data flow in SaaS is large-scale, high-volume and rapid. Businesses implement SaaS in order to streamline workflows and increase productivity. Really real-time DLP solutions do exist (they’re usually called ”agent-based” or “proxy-based”), but because they are checking every bit of data before they let it through, they can’t cope with the speed and volume of SaaS data flow.
The closest you can get to real-time without a perpetual data traffic jam and very, very unhappy users is “near real-time.” This you’ll find in API-based DLP solutions that are event-based, meaning that the SaaS application lets the DLP solution know as soon as an interaction with a data asset happens. Action can be taken right away to evaluate the interaction and, if found necessary, to remediate.
Take business and HR context into account
Sometimes the exact same SaaS asset interaction can be either a security breach or necessary for business, depending on the context. Take an employee who shares sensitive company financial data with an external party. If this external party is a competitor, the share is a security red alert. If, however, this external party is a firm doing due diligence before starting an acquisition process of your business, then the share is mission-critical to your business goals.
How do you know the difference? This requires a SaaS DLP solution that can draw on and use business and HR context. Is the user interacting with the SaaS asset just hired, or departing the company? What department are they a part of? In which geographic location? All of this contextual data is needed to properly respond to the SaaS asset interaction.
Involve and educate end users
The most effective type of mitigation is prevention. When end users develop a keen awareness of SaaS security concepts and your company’s data security policies, they make far fewer mistakes that would need to be caught and remediated by SaaS DLP.
SaaS data security awareness or education programs are a good start, but because the information is concentrated and detached from users’ day-to-day work, it often doesn’t stick as well as you might want. More effective is a SaaS DLP solution that informs users immediately about any of their problematic data interactions, explains the problem and how it violates the organization’s security policies, and ideally has them play an active role in the problem’s remediation. This direct involvement enables real integration of data security concepts.
How do I choose the right SaaS DLP solution?
The first step of choosing the right SaaS DLP solution for your organization is identifying which primary SaaS applications you need to protect. Do you use Microsoft 365, Google Workspace, or both? Do you use Slack? Do you store and share files in Box or Dropbox? Make a list of your business-critical SaaS applications. The SaaS DLP solution you choose should have comprehensive coverage for these systems.
Next, define the threats you are concerned about in regards to your data. Do you suspect external threat actors of posing the most risk - or malicious insiders seeking to leverage company data for personal benefit or to avenge a grievance? Maybe you’re most concerned about end users who are ignorant of company information security policies, or those who know about the policies but disregard them? Check that the SaaS data loss prevention technology you’re considering has the capacity to deal with the threats that most concern you.
Once you’ve established that a SaaS DLP solution meets the basic parameters of what you need to protect, it’s time to consider how well it will protect it. The basic question here is one of accuracy: can it effectively identify what data needs protection? As mentioned in the section above on Common Challenges to SaaS DLP Adoption, false positives and false negatives are problems with many types of DLP classification methodologies.
The last critical step to choosing the right SaaS DLP solution for your organization is evaluating the potential speed of its response. After all, if a solution takes several days to review and come to the conclusion that data is sensitive, even if that conclusion is always 100% accurate, chances are you’ll lose control of a lot of your data in the intervening days.
Just to sum up, in order to select the right SaaS DLP solution for you, investigate and define:
- The primary SaaS applications you need to protect
- The primary threats that concern you in regards to your data
- How effective it is at accurate sensitive data identification
- How rapidly it will be able to respond and implement protection in given situations
Compliance Considerations for SaaS DLP
If your organization deals with sensitive data (and today it’s hard to find an organization that doesn’t), then likely there are regulations that mandate how you treat that information. Protection from loss or exposure is mandatory in most localities when it comes to PII, health data, financial information or governmental data.
If you keep data of any of those types in your SaaS systems, implementing SaaS DLP is an important step in protecting yourself from regulatory violations and the resulting harm to your organization that would follow.
FAQs
What industries benefit most from SaaS DLP?
Industries that benefit most from SaaS DLP are those in which organizations tend to have a large SaaS app stack, many SaaS users and/or numerous SaaS assets. The heavier and more extensive the use of SaaS within an organization, the higher the chances that sensitive data within those SaaS apps could become exposed.
How does SaaS DLP differ from traditional DLP?
SaaS DLP (Data Loss Prevention) is designed to protect data in cloud-based applications by monitoring and controlling data access, sharing and storage across multiple cloud environments. It focuses on securing data in transit and at rest within SaaS platforms. Traditional DLP, on the other hand, is primarily focused on protecting data within on-premises systems and networks, often using endpoint agents and network monitoring to prevent unauthorized data transfer and leakage in a more static environment.
What are the potential risks of not using SaaS DLP?
Potential risks of not using SaaS DLP include the loss or exposure of sensitive data assets and the resulting legal risk of regulatory compliance penalties, financial risk of costs incurred to recover from the loss, business risk of revealed confidential IP or secret strategies and reputational risk.
Can SaaS DLP integrate with other security tools?
Yes, SaaS DLP can and should integrate with other security tools for comprehensive SaaS data security. Other SaaS data security tools include data access governance (DAG), identity threat detection and response (ITDR), insider risk management, connected SaaS application discovery and remediation, and misconfiguration management solutions. All of these tools working smoothly together are essential for SaaS security posture management (SSPM).
DoControl Solution for SaaS DLP
DoControl’s SaaS DLP solution utilizes advanced data classification technologies, including NLP and context-based detection, to accurately identify sensitive data. Inclusion of IdP, EDR and HRIS contextual information is used to distinguish between acceptable business use and security issues, dramatically reducing the likelihood of false positives.
The event-based solution provides near real-time identification of potential data breaches and exposures. DoControl’s automated remediation workflows then enable immediate alerting of information security team members or direct remediation of the issue.
DoControl’s SaaS DLP also interacts directly with the users involved, including them in the remediation process if possible. This boosts security awareness and reduces the likelihood of incidents in the future.
Keep Your Data Safe
With data as your primary asset, preventing its loss or exposure is a business-critical mission. The scale and speed of data asset change in SaaS can be daunting, but with the right SaaS DLP solution, you can achieve accurate, in-time protection for your sensitive data assets.
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