We are currently running a proof of concept and simulating usage with a select group of users as required by local bank licensing. It is utilized for vulnerability management. Up to this point, there have been minor incidents with no risks higher than moderate. Despite not needing immediate reaction, we have automation in place within your SOC and development team to respond in case of any recognized incidents.
One of the most beneficial features of Wazuh, particularly in the context of security needs, is the machine learning data handling capability. Although it has yet to be fully implemented into production and is currently in a test environment, the decision to choose Wazuh was influenced significantly by this feature. It helps us streamline and automate the assessment of security incidents. We can organize response plans proactively, even before certain incidents occur. It is the most critical aspect for us.
There were initial challenges with the real-time alerting team due to the many systems-generated alerts. It took about three months to fine-tune the system configuration, focusing on capturing only the alarms relevant from a security perspective. Despite the initial difficulties, Wazuh worked seamlessly, and there were no notable issues with configurations, handling, or investigations. The challenges primarily occurred from system-related aspects rather than issues with Wazuh.
I do not have direct experience with scalability requirements, but the implementation has been seamless. No challenges are scaling up, especially regarding adding more machines to handle the same load. The challenge is delivering logs so that Wazuh can collect, read, and analyze them effectively. We were able to overcome major issues without the need for extensive support.
Wazuh has been integrated with an intrusion prevention system (IPS) solution, Suricata, also an open-source tool. This integration adds a layer for security monitoring. The integration process is quite straightforward, especially due to the community's availability of shared use cases.
I rate the product a seven out of ten.