The best feature is the CLI part. If you want to execute any command or something like that, it is very easy. You can get a tab, and you just type the command there, and it will run. The playground feature is very good. You don't need a separate development environment; you can use it directly within XSOAR. These are the things that make XSOAR stand out compared to other products. For orchestration, the processes are very user-friendly. Even if I'm not an XSOAR admin, I can quickly become proficient with it. You just have to navigate through the various options in Palo Alto Networks Cortex XSOAR, and it becomes easy to manage. For instance, if you are a SOC analyst and want to start using XSOAR, it's very easy to access and retrieve the details you need. To put it in simpler terms, using XSOAR is like using a Fire Stick, where you have all your OTT platforms available. Similarly, in XSOAR, you get all the related alerts, whether from SIEM, EDR, or XDR, all consolidated in one place. You can analyze the data, make decisions, and even automate certain processes based on the data you receive. XSOAR assists in automating workflows, making decision-making processes easier. The orchestration in XSOAR is significantly easier compared to other SOAR tools I've used, like Siemplify, Splunk Phantom, and FortiSOAR. The processes are much more streamlined in XSOAR, which is what I appreciate most about it. So, when it comes to automation and playbooks, it is very easy. XSOAR is the only platform that supports three scripting languages: Python, JavaScript, and PowerShell. So you don't have to worry much about compatibility. If someone knows Python, they can easily create a playbook for automation. They can write the automation scripts and handle everything. Even if you're like me, coming from a Windows background and only familiar with PowerShell scripting, you can still create automation within XSOAR. This flexibility is something that XSOAR provides, unlike other tools that only support Python. XSOAR uses machine learning and generative AI, particularly in threat intelligence. In security, threat intelligence is the only area where AI and machine learning are truly effective. Aside from that, whatever vendors are claiming about AI is often just marketing hype. They might suggest that AI can be used everywhere, but security compliance is a crucial factor. For example, if I request AD admin access, it's unlikely anyone would grant it due to security concerns. This demonstrates the limits of AI in certain aspects of security. They may have chatbots and other features, but their necessity is questionable. For instance, if I need details about a particular IP or URL, I can retrieve it myself by running a command. Human intervention is still necessary in these cases. We can definitely use AI in incident response, but the major thing is in managing case notes. We recently initiated a project focused on ensuring that case notes added by analysts follow a proper format. We can then utilize generative AI to improve this process. For example, if an alert is related to a DNS query, we can create different templates. Based on the best keyword match, AI can make decisions, which is part of our plan.
