Splunk User Behavior Analytics vs Vectra AI comparison

Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.

Vectra AI offers advanced hybrid network and identity security, detecting threats traditional tools miss. It uses AI to identify lateral attacks and credential misuse, providing a proactive defense for enterprises.

Vectra AI enhances security by using AI-driven detection across network, cloud, and identity layers, surpassing EDR and SIEMs by offering real-time threat detection. It ensures continuous observability and automates SOC workflows to minimize manual efforts, creating an efficient security environment. Its AI-powered approach significantly reduces noise, focusing on true threats, and provides insights into complex threat landscapes, with seamless integration into environments like EDR and Office 365.

• AI-driven detection: Identifies lateral movement and credential misuse across networks.
• Continuous observability: Monitors data centers, cloud, SaaS, and OT environments.
• SOC automation: Reduces manual processes, lowering analyst fatigue.
• Attack Signal Intelligence: Filters noise to deliver relevant alerts quickly.
• Network visibility: Provides insight into encrypted traffic and unmanaged assets.

• Improved threat detection: Faster identification of potential threats.
• Efficiency in response: Automated processes free resources for high-impact tasks.
• Reduced alert fatigue: Intelligent alerts reduce false positives.
• Operational integration: Works seamlessly with existing platforms and tools.

Vectra AI is utilized across industries for comprehensive network and anomaly detection. Organizations deploy it for threat hunting and incident response, monitoring both on-premises and cloud activities. By placing sensors across sites, they optimize security practices and streamline their detection processes.