I'm currently looking for a free AI-based Splunk add-on or tool that can automatically detect suspicious IPs based on traffic patterns. Since a single IP may represent multiple users (due to NAT or proxy), the tool should ideally be able to handle such scenarios intelligently.
I'm exploring the Splunk Machine Learning Toolkit (MLTK) at the moment. Are there any other useful AI or anomaly detection tools — preferably free or open-source — that integrate well with Splunk and can help identify suspicious IP behaviour ?
Thanks for your concern and you are right.
I understand that AI-based add-on tools in Splunk may not always deliver perfectly accurate results, and there's a possibility of false positives. However, I'm looking for a solution that can still provide reasonably accurate detection — ideally around 70% accuracy — for identifying suspicious IPs based on traffic patterns.
Are there any Splunk-compatible tools, preferably free or open-source, that can help achieve this level of detection? I'm currently exploring the Machine Learning Toolkit (MLTK), but I’d appreciate suggestions for any other effective options.
I'm sorry, I know it is not helping you in any way but why do you expect a hard or even impossible problem to be to be solvable just because you throw in "AI" into the sentence?
Do you even know how such tool should work? Or do you just assume that adding "AI" into a sentence fixes everything?