Splunk User Behavior Analytics and Cynet compete in the advanced security analytics and endpoint protection category. Splunk appears to have an advantage for large-scale data environments due to its robust data analysis capabilities, while Cynet stands out for its comprehensive security approach with competitive pricing.
Features: Splunk offers robust data aggregation, advanced searching, and modular capabilities for integration across platforms. It is noted for its powerful querying ability and quick response time. Cynet excels in comprehensive endpoint protection, advanced threat detection, and user behavior analysis. It is valued for autonomous threat blocking and ease of deployment.
Room for Improvement: Splunk could improve its correlation capabilities, reduce complexity, and provide better integration options. It also faces criticism for its pricing model. Cynet could benefit from better mobile support, improved third-party integrations, and reducing false positives. Enhancing detailed reporting and network integration are additional areas for Cynet to focus on.
Ease of Deployment and Customer Service: Splunk supports on-premises and public cloud deployments but is often seen as complex. Its customer support is satisfactory but can be improved in cost-effectiveness. Cynet offers flexible deployment, including private and hybrid clouds, with highly responsive customer service praised for its support quality.
Pricing and ROI: Splunk's pricing model is complex and perceived as expensive, while users report productivity gains as a result of its usage. Cynet is praised for its competitive pricing and flexible licensing, offering substantial ROI with extensive security features at a lower cost compared to competitors, making it attractive to organizations.
Their SOC side support, when a threat is detected, is excellent.
Their technical support can be improved in terms of speed when opening a ticket.
I was very satisfied with their technical support.
I would rate the support at eight, meaning there's some room for improvement.
The solution is highly scalable.
Cynet is very scalable.
Splunk User Behavior Analytics is a one hundred percent stable solution.
Sometimes issues occur when handling long-term data.
There should be more options than deploying solely through group policy, as the assumption that GPO is working isn’t always the case.
Integration with local Active Directory, not only Azure AD, is a must.
Having a DLP feature would also add value.
I encountered several issues while trying to create solutions for this advanced version, which seem unrelated to query or data issues.
Advanced reporting could see enhancements as there are some issues with latency.
I think the pricing of Cynet is fair and one of the better options in the market.
The SOAR function, deception, and forensics are very useful.
The most effective features of Cynet are its ransomware protection and lateral movement deception.
The valuable aspects of Cynet are its EDR and XDR components, which are available at a reasonable price point.
I also utilize it for anomaly detection and behavior analysis, particularly using Splunk's machine learning environment.
Features like alerts and auto report generation are valuable.
Cynet provides endpoint protection, threat detection, and response. It helps companies secure files, devices, and networks from zero-day threats, reducing the need for extensive support staff through its continuous monitoring, antivirus, and anti-malware functionalities.
Cynet offers comprehensive security features, including EDR, NGAV, and MDR, suitable for cloud, on-premises, and hybrid environments. Organizations benefit from its 24/7 SOC services, seamless integration with other cybersecurity systems, and intuitive graphical interface. Features like autonomous malware blocking, scalability, detailed network user behavior analysis, and rapid policy deployment ensure robust security operations.
What are Cynet's most valuable features?Cynet is implemented across industries like finance, healthcare, and retail due to its comprehensive cybersecurity capabilities. Organizations in these sectors benefit from detailed network user behavior analysis, data aggregation, automation, and incident response, ensuring robust protection for critical infrastructure and sensitive data.
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.
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