Top 5 Open Source UEBA Tools to Enhance Data Security

Open-source frameworks with user and entity behavior analytics (UEBA) allow users to build their own solutions, offering the flexibility to customize and expand them to fit specific use cases.

These frameworks enable you to:

• Collect user or machine data from multiple sources to develop baseline behaviors.
• Utilize machine learning to identify unusual behavior patterns.

Based on the above use cases and market presence, I identified the top 5 open source frameworks/tools that you can build your user and entity anomaly detection model:

Market presence and feature comparison

What is UEBA?

UEBA aims to identify any unusual behavior—deviations from routine daily patterns.

For example, if a user typically does not download any files from the company database but suddenly starts downloading large files, the UEBA system will flag this as an anomaly. It will then alert an IT administrator or block the user from the network.

UEBA can also analyze data emerging from machines. For example, if a company device suddenly receives hundreds of server access requests in a day, UEBA will detect the deviation. 

Traditional security solutions, such as web gateways, firewalls, intrusion detection technologies, and VPNs, can no longer defend an enterprise from intrusions (e.g. using fragmented packets to bypass detection systems). 

Sophisticated cyber attack vectors will find a way into a system, thus detecting and monitoring user and machine data patterns at the tiniest level is critical. 

UEBA aims to identify every possible instance of abnormal behaviors and prevent a little phishing campaign from turning into an enterprise-wide data breach. 

Top 5 open source UEBA software analyzed

OpenUBA

OpenUBA is a SIEM-agnostic UEBA framework. It operates independently of your SIEM and can pull data from any data store.

OpenUBA utilizes Spark and Elasticsearch engines, to handle data processing and ingest data from multiple sources, all at scale.

Additionally, OpenUBA features a Model Library/Registry, similar to Docker Hub. This allows developers and security analysts to search a model repository and collaborate by sharing their models with the ecosystem.

Apache-Metron

Apache Metron is a cyber security application framework that allows enterprises to ingest, process, and store data streams to detect cyber deviations (e.g. abnormal user behaviors) and respond to them.

Apache-Metron leverages big data technologies, integrating elements of the Hadoop ecosystem to provide security analytics. It is built on top of Apache Storm, Apache HBase, and Apache Kafka.

It supports the integration of new enrichment services for additional context (e.g. provides pluggable extensions for threat intelligence feeds).

Apache-Metron’s features include:

• log aggregation from multiple sources (e.g. servers)
• behavioral analytics, 
• threat intelligence

Analysts can leverage Apache Metron for:

1. Telemetry capture, storage, and normalization: Apache Metron can ingest and distribute it to multiple processing units for analytics. 
2. Threat enrichment: As telemetry is collected, Metron applies enrichments like threat intelligence, geolocation, and DNS information. This adds critical context (who, where, and what) for deeper investigation and situational awareness, helping analysts respond faster.
3. Logs and telemetry storage for different uses:

• Data mining and analysis for security visibility.
• Machine learning for anomaly detection by scoring incoming data against previously stored models.

HELK

HELK is a machine learning-powered threat-hunting platform with behavioral analytics. It aims to offer a data science stack to improve the testing and development of threat-hunting cases.

Users can leverage Jupyter notebooks and Apache Spark on top of an ELK stack to identify unusual behavior patterns. 

Wazuh

Wazuh is a unified XDR and SIEM solution. It can help secure workloads in on-premises, virtualized, containerized, and cloud environments.

The Wazuh solution comprises an endpoint security agent placed on the monitored systems (e.g. servers, computers) that gathers and analyzes data.

Wazuh can be integrated with the Elastic Stack, offering an open source search engine and data visualization tool to help users navigate their security alerts.

Wazuh security events:

Source: Wazuh

Key features:

• Intrusion detection: Wazuh detects malware and hidden files in monitored systems. It uses a signature-based approach to analyze log data for indicators of compromise. For more see: IPS tools.
• Log data analysis: Wazuh reads operating system and application logs and forwards them to a central manager for rule-based analysis. 
• File integrity monitoring: Wazuh monitors file systems for changes in content, permissions, ownership, and attributes. It tracks user and application actions, ensuring compliance with standards like PCI DSS.
• Incident response: Wazuh offers incident response capabilities, such as blocking threats and running system queries to identify compromise indicators (IOCs).

Apache-Spot

Apache Spot is open source SIEM software for leveraging insights from flow and packet analysis. 

Apache Spot offers anomaly detection capabilities to help organizations:

• Detect lateral movement, where attackers move through a network to escalate their privileges.
• Identify data leaks, where data is covertly transferred out of the organization.
• Uncover insider threats and other forms of abnormal behavior.
• Analyze network flows and DNS replies to help reduce security risks across various data channels.

The majority of security technologies offer UEBA or UEBA-type capabilities. While UEBA may be utilized without any integrations, leveraging it as a cybersecurity toolkit can help enhance security.

UEBA is frequently used with, or incorporated into, the following tools:

Security information and event management (SIEM)

SIEM systems combine security event data collected by multiple internal security technologies into a single log and analyze it to detect unusual activity and potential attacks.

UEBA’s insider threat detection and user behavior analytics capabilities can help improve SIEM visibility into the network. Several modern SIEM tools feature UEBA (e.g. ManageEngine Log 360). For more see: UEBA tools.

Endpoint detection and response (EDR)

EDR solutions scan system endpoints like laptops, printers, and devices for detecting unusual activity that might indicate a threat. When risks are recognized, the EDR automatically resolves them.

By monitoring user activity on these endpoints, UEBA supplements—and is frequently used in conjunction with—an EDR solution.

For example, a suspicious login may result in a low-level alert to the EDR, but if the UEBA discovers that the endpoint is being used to access private information, the notification will be escalated. For more see: EDR tools.

Identity and access management (IAM) 

IAM technologies help ensure that correct users and devices have access to the necessary applications and data.

By monitoring for evidence of compromised credentials or misuse of authority by authorized users, UEBA-integrated IAM solutions can provide an additional layer of security. This is especially useful for companies with employees that have specific role-based access to systems. For more see: Open source RBAC tools.

Further reading

External Links