The recent Disney data breach highlights the ever-present risk malicious insiders present to organizations–especially in the cloud-based working world.
Whether on Microsoft Teams, Slack, or Google Workspace, almost all employees now rely on SaaS apps to carry out their work. In the process, they’re sharing, uploading, and downloading plenty of workplace data.
For the most part, that’s ok. But sometimes, that data contains sensitive employee credentials and customer information.
So, how do you stop an employee from downloading sensitive data, even when they have the right access privileges? And is there a way to detect malicious insiders before they strike?
Here are the steps to take.
How to combat the risk of malicious insiders
First things first, it’s crucial not to wait until after a malicious insider has struck to boost your insider threat detection mechanisms. You want the actions you take to be preventative, not remedial.
With that in mind, here’s how to boost insider threat protection in your organization, starting today.
Implement the principle of least privilege
While the principle of least privilege won’t stop every malicious insider, it goes a long way in minimizing the risks of data exfiltration. The idea is to ensure that employees only have access to the data they need to do their jobs, and nothing more.
For example, an IT administration will have very different IT requirements than a sales graduate. Your IT systems should cater to this accordingly.
Deploy a zero trust architecture
As we’ve discussed in our guide to zero trust, this concept refers to the idea that organizations should verify every person and device attempting to access their systems and data, whether they are inside or outside the network perimeter, before permitting access.
On the one hand, zero trust helps us to mitigate the risk of account hijacking, as employees will need to verify that they are who they say are in order to access data.
This approach also deters malicious insiders by adhering to the principle of “trust no one.” Zero trust continuously analyzes user behavior patterns for signs of unusual or risky activities. This ongoing monitoring and verification enables early detection of suspicious insider actions, allowing for swift intervention.
Embrace DLP for SaaS
The trouble with zero trust is that it’s not a singular technology; it’s more an underlying operating framework for organizations. To actually implement it, you’ll need the right tools that bring zero trust to your SaaS apps.
That’s where cloud-based DLP comes in. These tools actively monitor sensitive data and user behavior in your cloud applications, looking for potential risks to data security and compliance.
Train your employees with active learning
Active learning solutions provide training through prompts and nudges integrated into the employee’s workflow, utilizing applications like Slack, ChatGPT, and Microsoft Teams. These prompts appear throughout the workday in response to specific actions and triggers.
You can easily imagine what an effective deterrent active learning is to potential malicious insiders. When employees understand that their actions are being logged, analyzed, and corrected, they are far less likely to risk getting caught stealing sensitive data.
Unleash insider threat prevention with Polymer DLP
Wondering where you’ll find a solution that incorporates zero trust, DLP, active learning and privileged access controls all in one?
Meet Polymer DLP, designed to stop insider threats in their tracks. Here’s how:
- Monitoring for risky behavior: Polymer employs machine learning to continuously monitor user activities across SaaS applications. It analyzes behavior patterns deeply and automatically takes action if it detects risky actions. This includes redacting or blocking users while alerting your IT team for further investigation.
- Detection and prevention: The solution identifies and safeguards sensitive data within SaaS applications, ensuring that only authorized users can access and modify it. It can locate both structured and unstructured data across various cloud platforms, such as documents, chats, and databases. Using automation and a self-learning engine, it proactively protects data based on zero-trust principles.
- Discover high-risk employees: Polymer tracks the types of data employees handle and how they share it. This approach calculates metrics across SaaS platforms to generate a data exposure risk score, which highlights users with high-frequency and high-severity risks, enabling targeted interventions.
- Unlock educational reinforcement: Beyond traditional security training, Polymer’s SaaS DLP includes active learning features. It prompts users when they share sensitive data insecurely, providing continuous training and achieving tangible behavioral changes. Automated remediation adds an extra layer of protection.
- Boost SOC efficiency: Polymer minimizes the workload on your IT team by leveraging AI and machine learning to automate data discovery and protection processes. It only escalates the most critical incidents for human intervention, ensuring that unauthorized data interactions are swiftly addressed while maintaining operational efficiency in the background.
See Polymer in action for yourself. Request a demo now.
