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  • SaaS security refers to the deployment of solutions, protocols, and protective measures that safeguard SaaS environments. 
  • Challenges hindering effective SaaS security include improper security controls, the insider threat and cloud misconfigurations.
  • To bolster SaaS security, organizations should implement API-based DLP along with an active learning solution.

SaaS apps like Slack, Microsoft Teams, and Google Workspace are integral to workplace productivity. But they’re also a security headache.

According to recent research, most companies have a $28 million data breach risk lurking in their SaaS apps, stemming from issues like unsecured data, compromised credentials, and data loss.

To combat these threats, security vendors have released a new breed of SaaS cybersecurity tools, specifically designed to secure data in the cloud apps employees use day in and day out. 

Here’s what you need to know. 

Introduction to SaaS security

SaaS security encompasses the deployment of solutions, protocols, and protective measures aimed at safeguarding SaaS environments against threats like data loss, unauthorized access, and malware incursions.

As a cloud consumer, ensuring the security of cloud data within SaaS applications, such as Slack, Microsoft Teams, and Google Workspace, falls under your remit.

A robust SaaS security strategy typically revolves around:

  1. Safeguarding and ensuring compliance of data across all cloud applications.
  2. Implementing the principle of least privilege to restrict data and application access to authorized users only.
  3. Enhancing visibility across cloud environments to mitigate the risks associated with shadow IT and data leakage.

Understanding the SaaS security landscape 

The SaaS security landscape has evolved a lot in the last 10 years. Here, we’ll take a look at the evolutions it has undergone: 

Proxy-based security 

First, there were proxy-based security solutions. Essentially, these tools act as a middleman between users and cloud-based resources, allowing security teams to monitor and control access. 

Initially, these solutions were groundbreaking, addressing the urgent need for visibility in the rapidly expanding SaaS landscape. However, over time, their limitations have come to light.

For one, user friction is a significant concern because implementing proxies often requires intrusive agent installations on endpoint devices. This leads to productivity slowdowns and heightens the risk of employees seeking to bypass security measures.

Compatibility issues also exacerbate the situation. Some applications, notably Microsoft Office 365, struggle with proxy-based security, leading to performance glitches and, in some cases, glaring security gaps.

Moreover, deploying and managing proxy-based solutions is no small feat. It involves intricate technical configurations and ongoing maintenance, diverting resources from other crucial security tasks.


In response to the pitfalls of proxy-based solutions, two new SaaS security tools emerged: SaaS security posture management (SSPM) tools and specialist cloud-based data loss prevention (DLP). 

SSPM is all about reducing risks in the SaaS apps your employees use every day. These tools plug directly into your various SaaS app interfaces, with the aim of reducing the likelihood of misconfigurations in your SaaS apps in line with compliance mandates. 

A good SSPM tool will alert the security team to a misconfiguration or, better still, auto-remediate it to help your organization maintain compliance. However, it’s by no means a silver bullet. 

Firstly, SSPM tools often lack comprehensive visibility across cloud applications. While they plug directly into individual app admin portals, they operate more tactically than strategically. This means they excel at spotting misconfigurations within specific applications but fall short in unifying and simplifying overall app management.

Secondly, compliance coverage provided by SSPM tools may not be exhaustive. While they leverage compliance policies to identify and address configurations, crucial areas like intellectual property may remain inadequately protected, leaving potential security gaps.

Another significant hurdle is the dynamic nature of SaaS environments. With applications easily customizable and vendors frequently rolling out updates, SSPM tools struggle to keep pace. 

This results in a phenomenon known as ‘configuration drift,’ where administrators constantly chase misconfiguration errors across diverse applications, creating a challenging cycle of maintenance.

Plus, even when misconfigurations are rectified, there remains a risk of employees mishandling sensitive data within applications. 

SSPM does not extend its influence over how users interact with, upload, download, and share sensitive information. Consequently, organizations remain vulnerable to insider threats and credential compromises, highlighting a crucial gap in security coverage.

Cloud DLP 

Cloud DLP is a less singular tool and more a harmonization of several capabilities. With cloud DLP, features like data classification, natural language processing, machine learning, and encryption work simultaneously in your cloud apps to discover, monitor, and protect sensitive data in real-time. 

The overall aim of cloud DLP is to ensure that only verified, genuine, authorized users access sensitive information in SaaS apps and, moreover, only use it in a compliant, secure way. 

Unlike their predecessors, API-based DLP tools seamlessly integrate with the APIs of platforms like Slack and Teams, eliminating the need for agents or intricate coding. They reside within your cloud applications, quietly enforcing security policies based on predefined rules and compliance templates.

Users accessing cloud resources won’t encounter the delays typical of proxy-based solutions. In fact, they may not even realize the API-based tool is active until a security policy violation occurs, prompting an alert and action block.

Moreover, API-based solutions are agentless and work across all user devices, from BYOD to mobile to laptops. This ensures continuous monitoring and control over data access regardless of location or time, providing 24/7 visibility.

Unlike the complex deployment and management of proxy-based solutions, API-based DLP tools like Polymer DLP are ‘no-code,’ enabling swift installation in minutes. Additionally, by integrating natural language processing (NLP) and artificial intelligence (AI), these tools autonomously safeguard data, reducing the risk of SaaS data exposure without requiring manual intervention.

Top cybersecurity challenges for SaaS apps

If you’re wondering whether you need to invest in a SaaS security tool, the answer is a resounding yes. Here’s a closer look at the top security risks associated with SaaS apps.

Unrestricted enterprise access

The flexibility of cloud technology allows employees to tap into corporate resources from anywhere, using any device with appropriate login credentials. However, some organizations extend this accessibility to the extreme, granting employees broad permissions to manipulate critical data.

This practice carries dual risks. Firstly, inadvertent mishandling or leakage of mission-critical data poses a huge threat to security and compliance—a threat that could lead to catastrophic consequences if an attacker breached an employee’s cloud account, giving them unfettered access to sensitive information.

Additionally, enterprise-wide access exasperates the risk of the insider threat, especially when it comes to offboarding or resignations. While one might assume that deactivated accounts are no longer active, the failure to proactively decommission ex-employee accounts can leave a window open for unauthorized access to corporate resources.

The insider threat 

SaaS applications facilitate seamless document and data sharing among employees. But with the ease of sharing comes the heightened possibility of employees inadvertently or intentionally distributing the wrong documents to unintended recipients.

In essence, these applications can be ‘black boxes’. The IT team lacks visibility into the data being shared and its recipients, rendering compliance audits and data security enforcement challenging. This opacity raises concerns about meeting compliance standards and fulfilling data security requirements effectively.

Misconfiguration hazards

Cloud data leaks occur when sensitive company data, intended for private storage within a cloud environment, is inadvertently shared with the broader internet. Given that the cloud operates on the internet, such mishaps are not uncommon. The cloud essentially represents a concealed space accessible solely with appropriate credentials and authorization levels.

A single misconfiguration or error can lead to a plethora of sensitive data becoming accessible to anyone on the internet, constituting a significant breach of compliance regulations.

Broadly speaking, there are two types of individuals who actively search for cloud leaks: altruistic security researchers and malicious cybercriminals. Even if a security researcher discovers your leak and notifies you, it can be exceedingly challenging to ascertain whether hackers have also gained access.

Shadow IT

Shadow IT refers to the use of IT systems such as hardware, software, and cloud applications without the explicit knowledge or authorization of a company’s IT department.

According to Microsoft research, a staggering 80% of employees utilize applications that have not been sanctioned by the IT team. 

From the standpoint of employee productivity, the allure of unsanctioned applications is understandable. Personal preference, efficiency, and collaboration are common drivers prompting employees to seek alternatives to workplace apps.

However, from a security perspective, the proliferation of shadow IT presents a glaring risk of data leakage. Simply put, IT administrators cannot protect what they are unaware of. The lack of visibility and control over these unsanctioned applications, along with the data shared within them, poses a significant security challenge for organizations.

Compliance fines 

All of the above risks can, of course, lead to compliance fines. If customer or employee data is unlawfully shared or accessed, this is an immediate penalty under compliance mandates like the GDPR, CCPA, HIPAA and GBLA–depending on the sector within which you operate it. 

Native SaaS security features and tools 

Effectively managing SaaS data sprawl is essential for maintaining robust cloud security. However, relying solely on the built-in security controls of platforms like Slack and GitHub may lead to a false sense of security.

Unfortunately, these native security tools are rudimentary at best. They often generate numerous false positives and fail to identify sensitive information in unstructured formats. While they offer some level of data security enhancement, they lack the nuanced visibility and control required to effectively manage SaaS cybersecurity.

Furthermore, these in-built security tools operate within their respective platforms, necessitating the deployment and management of disparate tools across various SaaS applications. This fragmented approach not only adds complexity but also increases the likelihood of errors.

Even seasoned security experts would find it challenging to navigate and utilize multiple security consoles, especially considering that major SaaS providers frequently update their admin interfaces and configurations. 

AI and SaaS security

The integration of AI technology into SaaS platforms is changing the nature of cybersecurity yet again. On the one hand, AI can streamline operations, elevate customer experiences, and secure competitive advantages.

However, the journey to AI adoption is not without its challenges. Let’s delve into some of the key hurdles and risks associated with embracing AI in SaaS environments:

  • Shadow AI: Similar to the concept of shadow IT, shadow AI arises when employees utilize generative AI tools without proper authorization. This unauthorized usage exacerbates cybersecurity risks, introducing opacity in data processing and increasing the likelihood of data exposure.
  • AI-based attacks: With a notable 86% of Chief Information Security Officers (CISOs) acknowledging AI-infused attacks as imminent threats, the specter of malicious actors leveraging generative AI to refine phishing attacks and execute sophisticated tactics looms large.
  • Regulatory changes: The regulatory landscape surrounding AI is undergoing a significant overhaul, with initiatives like the EU’s AI Act and California’s AI Privacy Rule reshaping compliance requirements for SaaS providers.
  • Data leakage: Generative AI tools analyzing user queries risk leaking sensitive data, posing significant concerns regarding data privacy and security, particularly with personally identifiable information (PII) and proprietary source code.
  • Pilot failures: Despite the promise of AI, a substantial 80% of AI projects fail to meet their objectives, often due to exaggerated claims regarding capabilities and unrealistic expectations.
  • Bias: Bias in AI models, stemming from biased or incomplete training data, poses a pervasive threat. This leads to skewed results, perpetuation of systemic inequalities, and compromised security measures.

Best practices for securing SaaS applications

Whether the SaaS applications your company uses are infused with AI or not, there are some key steps to take to ensure you protect against data security and compliance issues.

Here’s what to do. 

Implement SaaS DLP

Cloud or SaaS DLP solutions are instrumental in discovering and safeguarding sensitive data in SaaS apps, ensuring that only authorized users can access and modify it. 

By leveraging APIs, cloud DLP solutions seamlessly integrate into cloud environments, scanning for sensitive data across applications. Best-in-breed tools like ours even extend data protection capabilities to generative AI applications like ChatGPT, offering holistic protection against data loss and misuse. 

Utilize multi-factor authentication

Implementing MFA is a simple yet effective method to mitigate the risk of credential compromise in SaaS applications. 

We strongly recommend enabling MFA across your SaaS platforms, and where feasible, deploying single sign-on solutions to bolster security without compromising user experience.

Adopt active learning

Traditional methods of teaching data security and compliance, such as annual away days, often yield limited results. 

Active learning offers a more engaging approach to foster better decision-making among employees. By incorporating automated feedback loops, such as active learning nudges and end-of-day reports within popular apps like Slack and Teams, employees receive real-time insights into potential security and compliance violations. 

This approach holds users directly accountable for their actions, fostering a culture of trust and privacy organization-wide. After all, data security is a collective responsibility that requires the active participation of every member of the organization.


Ultimately, SaaS apps are the bedrock of the modern working world. However, we’re also in a time where data privacy and security are under the magnifying glass. Just one data breach or leak can wreck havoc on a company’s bottom line–and the most likely avenue for these incidents stems from SaaS applications.

Of course, forbidding SaaS apps isn’t an option. They’re simply too integral to employee productivity and efficiency. That’s why it’s pivotal to ensure you have the correct security controls and processes in place to secure the SaaS environment. 

And that’s where we come in. Polymer DLP is an active learning and data security solution that safeguards sensitive data from leakage and unauthorized access in apps like Microsoft Teams, Google Workspace, and ChatGPT. 

Curious to learn more about the real-world benefits of Polymer DLP for SaaS? Read our latest case study or request a demo now.

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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