Как UEBA Cynet выявляет инсайдерские угрозы

In today’s digital world, where cyber threats are becoming increasingly sophisticated, it is crucial to pay attention not only to external attacks, but also to internal security risks. One of the most effective ways to identify such threats is to use User and Entity Behavior Analytics (UEBA) technology. Cynet, a leading provider of cybersecurity solutions, actively uses UEBA to protect organizations from potential insider attacks and other anomalous activities.

What is UEBA and Why is it Important?

User and Entity Behavior Analytics (UEBA) is a technology that uses machine learning and behavioral analytics to identify anomalies in the behavior of users and other entities (e.g., devices, applications, servers) within an organization’s network. Unlike traditional security systems that focus on signature-based detection of known threats, UEBA allows you to detect unknown and non-traditional attacks that may be missed by traditional methods.

Why is this so important? The fact is that attackers often use compromised accounts or become insiders to gain access to sensitive data. Their actions may look like normal user activity, making them difficult to detect by traditional means. Identifying anomalies in user behavior becomes critical to preventing data breaches, financial losses and reputational damage.

How Cynet Uses UEBA to Protect Against Insider Threats

Cynet integrates UEBA into its cybersecurity platform, providing organizations with a comprehensive solution for detecting and responding to insider threats and other anomalous activities. Cynet UBA (User Behavior Analytics) provides a number of benefits:

  • Full Visibility: Cynet collects data about the behavior of users and entities from various sources, including endpoints, the network, cloud applications, and event logs.
  • Automatic Anomaly Detection: The system uses machine learning to create baseline profiles of user behavior and automatically detects deviations from these profiles. Identifying anomalies in user behavior is carried out in real time.
  • Incident Prioritization: Cynet prioritizes incidents based on the severity and likelihood of the threat, allowing security teams to focus on the most important issues. With anomaly detection from Cynet, you can significantly reduce incident response time.
  • Automated Response: Cynet offers automated incident response actions, such as blocking user accounts, isolating compromised devices, and removing malicious files.

Benefits of Using Cynet UEBA

Implementing Cynet UEBA allows organizations to significantly increase their level of cybersecurity and protect themselves from a wide range of threats. Let’s consider the main advantages:

  • Improved Insider Threat Detection: Cynet UEBA allows you to identify malicious insider actions that may be invisible to traditional security systems. For example, the system may detect a user who suddenly starts accessing files that they do not normally access. Detecting insider threats has become much easier with Cynet.
  • Reduced Incident Response Time: Thanks to automated detection and incident prioritization, security teams can respond to threats faster and prevent potential damage.
  • Improved Protection Against Complex Attacks: Cynet UEBA helps detect complex attacks, such as targeted attacks and APTs (Advanced Persistent Threats), that may be missed by traditional defenses.
  • Compliance: Cynet UEBA helps organizations comply with regulatory requirements such as GDPR and HIPAA, which require the protection of sensitive data.

Examples of Using Cynet UEBA

Here are a few examples of how Cynet UEBA can help organizations protect themselves from cyber threats:

  • Compromised Account Detection: Cynet can detect a user account that is being used to access resources from an unusual location or at an unusual time of day, which may indicate that the account has been compromised.
  • Data Theft Detection: Cynet can detect a user who is downloading a large amount of data to a USB drive or sending confidential information via email to an external address.
  • Unauthorized Resource Access Detection: Cynet can detect a user who is trying to access resources to which they do not have access rights.

How Cynet Implements UEBA: Key Technologies

Cynet’s user behavior analysis solutions are based on several key technologies that ensure high threat detection efficiency.

UEBA защита от инсайдерских угроз

Machine Learning

Cynet uses machine learning algorithms to create baseline profiles of user and entity behavior. These profiles are constantly updated and adapted to changes in user behavior. Machine learning allows the system to automatically detect anomalies that may be missed by traditional methods.

Behavioral Analytics

Cynet uses behavioral analytics to analyze data on the behavior of users and entities. This analytics includes:

  • Access Time Analysis: Cynet analyzes the time when users access resources and identifies anomalies, such as accessing resources at an unusual time of day.
  • Location Analysis: Cynet analyzes the location from which users access resources and identifies anomalies, such as accessing resources from an unusual location. For example, if an employee normally works from an office in Kyiv, and suddenly activity begins to appear from a New York IP address, this is a reason for verification.
  • Data Volume Analysis: Cynet analyzes the amount of data that users access and identifies anomalies, such as downloading a large amount of data to a USB drive.
  • Application Analysis: Cynet analyzes the applications that users use and identifies anomalies, such as launching unknown or suspicious applications.

Event Correlation

Cynet uses event correlation to combine information from various sources and identify complex attacks. For example, the system may combine information about suspicious activity on an endpoint with information about suspicious network traffic to identify a targeted attack.

Typical Mistakes When Implementing UEBA and How to Avoid Them

Implementing UEBA can be a difficult task, and there are several typical mistakes that can reduce the effectiveness of the system. It is important to consider the following points:

  • Insufficient Data: UEBA requires a large amount of data about user and entity behavior to work effectively. If there is not enough data, the system may issue many false positives or miss real threats. Make sure Cynet has access to all necessary data sources.
  • Incorrect Threshold Settings: Anomaly thresholds should be configured to suit the specific needs of the organization. If the thresholds are too low, the system will issue many false positives. If the thresholds are too high, the system may miss real threats.
  • Insufficient Integration with Other Security Systems: UEBA should be integrated with other security systems, such as SIEM (Security Information and Event Management) and EDR (Endpoint Detection and Response), to provide comprehensive protection against cyber threats. Cynet provides close integration with its own solutions and with solutions from other manufacturers.

Tips for Effectively Using Cynet UEBA

To make the most of Cynet UEBA, follow these recommendations:

  • Define Your Goals: Before implementing UEBA, define what threats you want to detect and what goals you want to achieve. This will help you configure the system correctly and choose the most appropriate use cases.
  • Configure Anomaly Thresholds: Configure anomaly thresholds to suit the specific needs of your organization. Review thresholds regularly to ensure they remain effective.
  • Integrate UEBA with Other Security Systems: Integrate UEBA with other security systems to provide comprehensive protection against cyber threats.
  • Train Your Employees: Train your employees on how to use UEBA and how to respond to detected threats.

Identifying anomalies in user behavior using Cynet UEBA is an important element of a modern cybersecurity strategy. This technology allows organizations to detect and prevent insider threats, complex attacks, and other anomalous activities that may be missed by traditional defenses. Thanks to Cynet, companies get a powerful tool to protect their sensitive data and maintain business continuity.

To learn more about how Cynet can help your organization protect against cyber threats, contact us

Frequently Asked Questions About: How Cynet UEBA Detects Insider Threats

  • What is UEBA and why is it important for cybersecurity?

    UEBA (User and Entity Behavior Analytics) is a technology that uses machine learning and behavioral analytics to identify anomalies in the behavior of users and other entities on the network. This is important because it allows you to detect internal threats and sophisticated attacks that traditional security systems may miss.
  • How does Cynet use UEBA to protect against insider threats?

    Cynet integrates UEBA into its platform, providing full visibility, automatic anomaly detection, incident prioritization, and automated response. Cynet UBA (User Behavior Analytics) collects data from various sources and uses machine learning to identify deviations from the normal behavior of users and entities.
  • What are the benefits of implementing Cynet UEBA?

    Cynet UEBA provides improved insider threat detection, reduced incident response time, improved protection against complex attacks (APTs), and compliance with regulatory requirements such as GDPR and HIPAA.
  • Provide examples of how Cynet UEBA can be used to detect cyber threats.

    Cynet can detect compromised accounts (e.g., access from an unusual location), detect data theft (downloading large amounts of data to a USB drive), and detect unauthorized access to resources.
  • What key technologies does Cynet use to implement UEBA?

    Cynet uses machine learning to create baseline behavior profiles, behavioral analytics (analysis of access time, location, volume of data, used applications), and event correlation to combine information from various sources and identify complex attacks.
  • What are the typical mistakes made when implementing UEBA and how to avoid them?

    Typical mistakes are insufficient data, incorrect configuration of anomaly thresholds, and insufficient integration with other security systems. It is important to ensure access to all necessary data sources, correctly configure thresholds, and integrate UEBA with SIEM and EDR systems.
  • What tips for effectively using Cynet UEBA can you give?

    Define the goals of implementation, configure anomaly thresholds in accordance with the needs of the organization, integrate UEBA with other security systems, and train your employees to use the system and respond to detected threats.
  • Can Cynet UEBA help detect APT attacks?

    Yes, Cynet UEBA helps detect complex attacks, such as APTs (Advanced Persistent Threats), which may be missed by traditional defenses, by identifying anomalous behavior characteristic of such attacks.
  • What is Cynet UBA?

    Cynet UBA (User Behavior Analytics) is a user behavior analytics module within the Cynet platform that uses UEBA to detect insider threats and anomalous activity.
  • How often should anomaly thresholds in Cynet UEBA be reviewed?

    Anomaly thresholds should be reviewed regularly to ensure they remain effective and meet the changing needs of the organization and the threat landscape. The frequency of review depends on the dynamics of the business and infrastructure, but it is recommended to do so at least once a quarter.