Stop Chasing Anomalies and Alerts

SecBI Detects Full Scope Incidents

The tools that hackers have today are extremely sophisticated and utilize distributed architecture. Instead of communicating with a single node, domain or IP, they use a stealthy network that is always changing. As a result, existing detection tools fail to identify more than 90% of forensic data related to malicious activity, yet generate thousands of time-consuming alerts — many of which are false positives.

SecBI is an advanced threat detection software solution that ingests log data from network security gateways, and applies unique clustering and detection algorithms to detect threats that other vendors miss. Because SecBI’s machine learning technology analyzes every piece of incoming and outgoing log data, it is able to cluster related forensic evidence into a single incident and provide a full narrative of the attack, including all users, devices, communication patterns, and more. This process eliminates fragmentation, investigation fatigue, and excessive searching.


(SecBI analyzes massive amounts of log data from network security gateways to rapidly detect threats that other vendors miss.)
SecBI uses proprietary unsupervised clustering algorithms to provide complete detection across network security gateways. While other solutions focus on individual anomalies that may or may not be genuine attacks, SecBI’s algorithms rapidly review all data to piece together clusters of suspicious activity into single incidents.


Rather than bombarding the user with thousands of spurious alerts, SecBI’s machine learning analyzes and clusters all related forensic evidence, including infected devices, and their users, malicious C&C servers, compromised infection points, and the drop-point with which they communicated. Manually searching for forensic evidence, comparing multiple devices activities, writing complex queries – is a thing of the past. SecBI will detect, cluster, summarize, and present all the relevant evidence in your data.


SecBI delivers a single, full narrative of the attack – from infiltration to propagation and exfiltration. By piecing together all this information into a comprehensive incident report, SecBI reduces breach response time, optimizes mitigation, and helps security teams focus on what is important.


SecBI takes a new machine-learning approach that combines unsupervised clustering and cluster-wide detection to provide full scope detection otherwise not possible for sophisticated cyber attacks.

SecBI’s machine learning technology is specifically designed to empower cyber security analysts by analyzing billions of network event logs, performing autonomous investigation via dynamical clustering to uncover hidden patterns across multiple computers, prioritizing the threats, and summarizing each threat into an intuitive and interactive report. The analyst receives a summarized incident alert compiled of one or one-million events, without any manual dumpster-diving through the logs.

SecBI is entirely data-driven. There is no need for manual configuration, writing static detection rules or endless tuning and updating. As new evidence arrives, SecBI updates each incident with the new, relevant evidence, ensuring that users always see the most accurate analysis.


Reduce time to breach detection

Eliminate ‘False Positive Fatigue’

Capture the full story of a cyber security incident