Turn your data into knowledge.

Understanding your network is the key to security.

Our Cyber Knowledge Graph system and analytics provides intuitive and simple access to the right data at the right time necessary to understand what, why, and how entities on your network are interacting.

About

Technologies and Services


Empower your analyst workflow with graph analysis

We enable analysts to seamlessly search and analyze the relationships between all of their data sources from a single interactive no-code UI.

Search

Our unified search provides the simple yet powerful capability to search across all data sources for entities and relationships of interest.

Analyze

Analyze the graph relationships by exploring and pivoting through entities and relationships to understand the big-picture.

Triage

Automatically contextualize and rank security alerts for review leveraging our Graph AI algorithms capable of identifying the most critical data.

Detect

Leverage the Graph AI and analytic outputs for detecting unusual activity and risky entities for proactive remediation.

Save time, money, and stress

Our novel approach to cybersecurity increases efficiency and efficacy of analysts, resulting in less time wasted, and more attacks detected.

+80%

Time Savings

When analysts used our system to triage alerts, we found that they spent on average 80% less time to perform a similar analysis.

+90%

Accuracy

Our experiments show we can detect highly sophisticated APT scale attack scenarios with our behavioral graph-based anomaly detection with extremely high accuracy.

10x

Data Coverage

On average our users are able to ingest more than 10 unique heterogeneous data sources into the Cyber Knowledge Graph providing instant correlation and access to Graph AI analysis.

How It Works


Simple & seamless integration with your existing tools

Cloud native, UI and API driven installation and configuration means you won't burden your team with tool management and maintenance.



Automatic Log Parsing

Graph data models are extremely flexible, which means we can ingest all of your logs into a single source of truth for your environment. This process is as simple as determining what logs you want ingested and configuring the appropriate data connector.


Graph AI Analysis

Once your data is converted into a Cyber Knowledge Graph, we apply a host of Graph Analytics and Graph AI algorithms that are designed to learn patterns of relationships between entities in the graph. This knowledge is then leveraged to assign risk scores to activity, as well as aid data exploration and alert triage / incident response.


Visual Analysis Platform

Explore and analyze the Cyber Knowledge Graph with our intuitive visual analysis platform. Perform complex analysis tasks with simple search terms and intuitive graph transformations that can be done with little-to-no code.


Founding Team

Researchers with a passion for Graph Theory, Data Science, and Cybersecurity.

Howie Huang, Ph.D.

Chief Executive Officer

In addition to his role as CEO of Cybermonic, Dr. Huang is also a Professor in the Department of Electrical and Computer Engineering at the George Washington University, where his GraphLab works on graph analytics, machine learning, and cybersecurity applications. His research has been supported by roughly 20 grants of close to $7M from NSF, DARPA, DoD, and companies including Raytheon, IBM, NVIDIA and Comcast.



Benjamin Bowman, Ph.D.

Chief Technology Officer

Benjamin is a cybersecurity expert ranging from source code analysis to APT detection based on novel graph-based systems and algorithms. Before pursuing his PhD and subsequently founding Cybermonic, Benjamin was a software engineer for AT&T where he was developing a defensive cyber security appliance used to protect and monitor the AT&T enterprise network.

Research

Our team has a proven track record from DARPA funded research programs focusing on application of graph systems and algorithms to various cybersecurity problems

Our work published in RAID leveraging Graph AI for lateral movement detection.

Our position paper published in ACM SIGOPS justifying the increased use of graph analysis for cyber.

Our work published in EuroS&P utilizing graph analytics for detecting vulnerable source code.

Careers

Join our team!

We are looking for talented & motivated individuals with a passion for entrepreneurship, cybersecurity, and deep technology. Our current job postings are listed below.

Cybersecurity Software Marketing Executive - Details