We primarily use the solution for SIEM alerts triage automation and MITRE detection playbooks. We have hundreds of alerts from various detection tools fed into our SIEM. Correlation within the SIEM is difficult for us since our SIEM only supports simple filtering and one level of data sources correlation. Managing and updating correlation rules is a pain. We are now propagating alerts fed into the SIEM directly to LogicHub via a webhook. Within the LogicHub, we have playbooks that automatically enrich the alerts, baseline checking the alerts, risk weighing and scoring the alerts, and then stack ranking the riskiest and impactful ones to be escalated into a case so our analyst can be the human in the loop before we fire off any automated response.
What is our primary use case?
How has it helped my organization?
We no longer need to spend time on false positives. It has improved my detection coverage in areas lacking by the SIEM. A very nice case management system to track and automate tasks. With some of the playbooks automated, our analysts are now spending their time defining newer playbooks either for triage or detection. With the MITRE-based playbooks, we can just import and tweak the detection on areas where our SIEM vendor lacked rules. Our analysts only look at cases, which are less than a handful each day. Our analysts are not looking at alerts, which are 100+ per day.
What is most valuable?
The ability to analyze data automatically to make decisions automatically is what I like the most.
It is also fully integrated with hundreds of other tools.
Our SIEM has the search capability but it cannot save the dataset for me to merge with the result set of another query. In LogicHub, to join two resultant datasets is super easy because they use SQL operators that I can do left join, right join, inner join, or full cross join. Besides some reporting tools that I used in the past, no other SOAR can do this easily. We automated that whole analytic logic so I don’t need to repeat.
What needs improvement?
UI coloring can be improved. The UI resembles an IBM or HP software tool suite. The UI is not fancy like some of the others, however, it does work. The platform is designed for someone who has a logical mindset. The Logic needs to be planned out like any good design.
The dashboards can be improved. There are basic table, pie, line, and bar data widgets, yet no geo-mapping widget. However, the dashboard does have the good feature of a funnel chart that I can show volumes of alerts vs cases that our team is handling each day.
For how long have I used the solution?
I've used the solution for five years.
What do I think about the stability of the solution?
The stability is good. We haven’t had any major outage yet - fingers crossed.
What do I think about the scalability of the solution?
LogicHub says they use Apache Spark as their core. I am familiar with Apache Spark as we also have Databricks implemented by other teams in-house on our big data projects.
How are customer service and support?
We have a customer success manager assigned to us that I have a biweekly meeting with.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
How was the initial setup?
The setup is easy. It’s a cloud-based solution.
What about the implementation team?
We handled the setup in-house.
What was our ROI?
I do not know for sure what our ROI is. The platform is doing the work of two or more security analysts. We are paying the cost of about one analyst.
What's my experience with pricing, setup cost, and licensing?
LogicHub was the most cost-effective among the three other solutions we looked at.
Which other solutions did I evaluate?
What other advice do I have?
LogicHub engineers took the best of Demisto (CSOAR) and Splunk Phantom and added a threat section and hunting automation to their platform.
Which deployment model are you using for this solution?
Public Cloud
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