Risky Business: Can User Classification Reveal Risk Insights?

Discover how user classification empowers organizations to assess and mitigate identity risks. Learn strategies to align governance and risk reduction efforts.

In today’s ever-changing cybersecurity landscape, understanding the risk posed by different types of users is critical to effective threat management. Cybercriminals constantly evolve their tactics and organizations must stay ahead by maintaining a deep understanding of their risk landscape. By categorizing users based on their roles, behaviors, and relationships to the business, organizations can better enforce security, reduce vulnerabilities, and implement identity security strategies that align with risk mitigation goals.

But can user classification truly reveal meaningful insights that help reduce security risks? The answer is yes, especially when organizations leverage tools to track user interactions and focus on understanding the nuances of different user relationships.

What Is User Classification?

User classification is the process of categorizing individuals who interact with an organization's systems, based on factors like their role, relationship with the organization, and access needs. This can include employees, contractors, partners, and third-party vendors. By classifying users into specific categories, organizations can implement more targeted and appropriate security measures, ensuring that each user group has the right level of access to the right systems at the right time. Proper classification enables businesses to mitigate security risks more effectively by aligning security protocols with the level of sensitivity and access each user requires.

The Importance of Understanding User Risk

Organizations typically engage with many types of users with varying levels of access to sensitive systems and data. These users can range from employees with direct pay relationships, to revenue generating partners, third parties and even individuals. Each type of user brings a different level of risk depending on their access needs and frequency of system interaction.

One of the most significant factors in managing user risk is distinguishing between user types. Employees who are directly compensated and onboarded through HR systems tend to have deeper access to critical business systems. In contrast, third parties and partners usually have more restricted access, limited to specific tasks or roles. However, both types of users can pose unique security risks, and understanding these distinctions is key.

For example, employees might access highly sensitive internal data regularly, while third-party contractors may only need access to a specific set of resources for a limited time. Classifying users accurately enables organizations to tailor security measures according to the specific risks each type of user presents.

The Role of User Classification in Risk Reduction

User classification provides valuable insights that help organizations make data-driven security decisions. It allows businesses to identify risks and apply customized governance efficiently. Here's how user classification plays a crucial role in risk reduction:

• Prioritize Access for High-Risk Users: Employees with access to sensitive data and systems can be high risk, particularly when considering the type of access they have, especially if they leave the organization or change roles. In contrast, external users—such as contractors, partners, and third parties—may have more limited access but still pose a higher risk due to the volatility of their relationships with the organization. These external users may have access that is not regularly reviewed or updated, and their roles or projects can change without timely communication. By classifying users based on their access level and relationship to the business, organizations can quickly identify high-risk groups and apply appropriate security controls. For example, users with elevated privileges should be subject to more rigorous controls, while external users should be monitored more closely and given access on a just-in-time basis.
• Leverage Last Login Data to Minimize Unused Access: One of the key tools available is tracking last login data. By understanding when users last accessed systems, organizations can identify dormant accounts that are no longer in active use. Users who have not logged in for extended periods can be flagged for immediate access removal or a review of their accounts. This simple step helps reduce the exposure associated with accounts that are no longer necessary, especially for external partners or contractors whose access needs may change over time.
• De-duplicate Identities for More Accurate Risk Assessment: Another powerful strategy is de-duplicating identities. Many organizations face the challenge of users having multiple identities across various systems, which can lead to fragmented access management and obscure risk profiles. By correlating all access for a person—across systems, devices, and roles—organizations can gain a unified view of their access footprint. This approach reduces risk by ensuring that no access is overlooked, and any potential vulnerabilities associated with multiple identities are consolidated for better monitoring and management.
• Tailor Security Measures by User Relationship: Understanding the nature of a user’s relationship with the organization helps tailor security controls. Employees with direct pay relationships are typically more integrated into the internal systems, protected by multi-factor authentication (MFA) and frequent password updates. Partners and third parties, however, may only need limited access to specific tools or data, which calls for a different approach—perhaps more focused on granular role-based access controls (RBAC) and automatic or just-in-time access provisions.
• Support Zero Trust Initiatives: In a Zero Trust framework, the principle is to never trust any user, regardless of their role or location. Classification helps apply Zero Trust principles by ensuring users only have the permissions necessary to perform their roles. This reduces potential attack surfaces by applying the least-privilege model to all users, regardless of their perceived trustworthiness.

Challenges of User Classification

While user classification offers numerous benefits, there are challenges in ensuring that classifications are accurate and continually updated. For example, organizations must ensure that their criteria reflect the real risks associated with different user types, avoiding both over- and under-classification. Misclassifying a user could either leave an organization vulnerable to attack or unnecessarily restrict a user’s access, causing workflow inefficiencies.

Organizations also need to regularly review classifications as users’ roles or relationships change over time. A partner who once had limited access to a project may need broader access for an upcoming initiative, or a former employee may still have lingering access privileges. Regular audits and reviews of user access are essential in keeping security measures up to date.

Best Practices for Leveraging User Classification in Risk Reduction

To maximize the value of user classification, organizations should adopt the following best practices:

1. Define User Categories Based on Business Relationships: Engage your line of business (LOB) stakeholders to help categorize users into logical groups—such as employees, partners, and third parties—and define specific access needs for each group following the principle of least privilege (PoLP). External partners who only interact with customer-facing systems can be granted access to those specific assets, while providing direct-pay employees with the broader system access they need to do their work. 
2. Track Last Login Activity: Use last login data to identify inactive accounts. Accounts that have not been accessed for extended periods are prime candidates for access removal, particularly when dealing with third parties or temporary contractors whose roles may have changed.
3. De-duplicate and Correlate Identities Across Systems: To ensure a complete view of access, eliminate identity duplication and consolidate user accounts across different systems and roles. This makes it easier to identify risks and prevent gaps in security.
4. Review User Classifications Regularly: As users move between roles or contract engagements come to an end, assess whether their access levels are appropriate. Classifications should reflect both their current role and their potential security risk to the organization.
5. Educate Users on Security Risks and Best Practices: Regardless of classification, all users should be educated on security best practices. Ensuring employees, contractors, and partners are aware of the risks associated with poor security hygiene helps mitigate human error and reduces the likelihood of breaches.

User classification is a powerful tool for managing and mitigating identity risks. By understanding the relationships between users and their level of access to business-critical resources, organizations can apply more targeted security measures that reduce vulnerabilities. Additionally, leveraging tools like last login data to remove unused access, de-duplicating identities to correlate all access for a person, and tailoring security controls by user relationship further enhances risk management strategies. Whether dealing with employees, partners, or third parties, classification helps organizations take a more informed and precise approach to security, reducing exposure and aligning with broader risk reduction goals.

Learn more about how to secure your extended enterprise with Saviynt’s Identity Cloud.