Best User and Entity Behavior Analytics (UEBA) Software for GitHub

Graylog Security integrates artificial intelligence, machine learning, and behavioral analysis to empower teams in identifying and addressing threats that conventional rules often overlook. Its User and Entity Behavior Analytics (UEBA) continuously evolves by learning the typical behaviors of users, hosts, and applications, allowing it to adjust to emerging behaviors and risks. By connecting anomalies with log data, asset information, and threat intelligence, Graylog effectively identifies significant threats—like insider threats or credential misuse—while minimizing false alarms. The platform's AI-driven summarization and structured investigation processes provide analysts with clear insights and expedite the triage process, enabling them to translate intricate data into prompt, informed decisions.

ActivTrak is a cloud-native workforce intelligence platform that transforms work activity data into actionable insights for employee monitoring, productivity and performance management, and workforce planning capabilities that deliver measurable ROI. Deployment is quick and easy — start collecting data in minutes.

Reveal Security ITDR detects identity threats - post authentication - in and across SaaS applications and cloud services. Powered by unsupervised machine learning, it continuously monitors and validates the behavior of trusted human users, APIs and other entities, accurately detecting anomalies that signal an in-progress identity threat.

Acceptto observes user behavior, transaction patterns, and application interactions to build a comprehensive user profile tailored to each application environment, allowing it to assess whether access attempts are valid or pose a security risk. The system operates without relying on traditional passwords or tokens. By leveraging its risk engine, Acceptto evaluates the legitimacy of access attempts by monitoring user and device posture before, during, and after the authentication process. In a landscape where identities face continuous threats, we provide a seamless, step-up authentication procedure complemented by real-time threat analytics. The risk score generated by our advanced AI and machine learning algorithms determines a dynamic level of assurance (LoA) for each access attempt. Our innovative strategy automatically identifies the most effective policy for every transaction, optimizing security while reducing user friction through AI-driven insights. This ensures a streamlined user experience that upholds robust security standards across the enterprise. In essence, Acceptto redefines security by integrating advanced technology with user-centric design.

Rezonate automatically detects and corrects access configurations, risky activity, and weak security practices across all your identity providers and IaaS, reducing your identity risk. Rezonate continually synthesizes all of your cloud applications, resources, as well as your human- and machine identities. It gives you a single identity storyline that provides a comprehensive view of all your access risk and identity. Rezonate's Identity Storyline goes far beyond the traditional graph views. It tells you the story behind every identity, threat and exposure so that you can confidently identify, prioritize, and take action to eliminate access risks. Identity Storyline provides a detailed explanation of every threat, exposure, or active threat that is detected and how it got there, as well as the potential consequences. You can now see every activity and change across your cloud identity attack surface in real-time, beyond the periodic configuration scans.