Security Incident and Event Management (SIEM) solutions have been in use for almost two decades, but the promise of SIEMs and other log search solutions remains unfulfilled (e-Security, arguably the first SIEM company, was founded in 1999 in Vienna, Virginia). SIEMs deliver analytics tools with search capability, but these tools remain limited to to providing responses to manually created questions / queries / correlations by human analysts and have not evolved beyond rule-based correlations. SIEMs have made claims about increased complexity and sophistication of such correlations through the use of wildcards, Boolean logic, RegEx, and other techniques. However, the SOC analyst remains constrained to receiving responses about his or her specific query and the correlation must be very specific in order for the signal-to-noise ratio to be acceptable. As a result, SIEMs lead to alert overload, generating thousands or millions of false positives for analysts to manually filter, investigate, and take action. In addition to being a huge drain on resources, this workflow often misses true risks (false negatives) in the deluge of alerts.