TECHNOLOGY

AI Engine

Battle Tested, Purpose-built, AI

Go beyond alerts – detect and respond to Incidents. Industry leading Machine Learning (ML) algorithms detect threats in the enterprise. Stellar Cyber’s AI engine is like a team of world class security experts working around the clock at massive scale to make your team faster and more effective.

AI That Delivers Results

The output of Stellar Cyber’s AI Engine can be simplified down to generating two types of data
for security teams: alertsand incidents. Together,alerts and incidents provide the depth and holistic
view teams need to make rapid decisions

Novel Alerts

Alerts are instances of specific suspicious or high risk behavior and are the building blocks of Incidents. Stellar Cyber ships with 200+ Alert Types out of the box; no configuration required. Alert Types are mapped to the XDR Kill Chain, to enable prioritization and correlation. Individual Alerts have a generated, human readable description of what happened, and recommended remediation for fast response.
Example alert types include:
  • External Scanner Behavior Anomaly
  • Internal RDP Brute Force Attack
  • Internal SMB Username Enumeration
NDR platform
SIEM platform

Automatically Correlated Incidents

Incidents are correlated sets of Alerts and other supporting data including signals, assets, users and processes. Incidents represent an entire attack or sequence of high risk actions. In real time, as new Alerts are generated, Alerts are assigned to relevant Incidents so that attacks can be detected and responded to before completion. Incidents in Stellar Cyber are mutable, meaning they can get updated, and are not limited to any certain time window so they can pick up complex attacks.
Real-world incidents detected in Stellar Cyber:
  • Darkside Ransomware attack
  • Sunburst attack

How Stellar Cyber’s AI Engine Works

SIEM replacement

Key Features

AlienVault alternatives

Accurate

Alert Fatigue is a serious problem. Not every anomaly is
a security incident. Security analysts should stop sifting through
countless anomalies and focus on the real threats. Core to
Open XDR, Stellar Cyber’s AI Engine leverages
state-of-the-art machine learning algorithms to implement
the best accuracy for detection. It analyzes time series and
peer groups with unsupervised learning, performs complex
behavior analysis through modeling relationships with Graph
ML, and generalizes known attack patterns with supervised
learning. It also correlates and builds context with advanced
Graph ML, so that we can present the high priority attacks with
rich context.
Automated SOC

Real Time

It may take minutes for hackers to infiltrate your system and
steal valuable information. You need virtual security experts to
continuously work around the clock and detect threats in real
time. Stellar Cyber’s AI Engine performs ML inference in real
time and provides detailed reasons for its output.
cloud detection and response

Unified

Our single advanced AI Engine powers Stellar Cyber’s Open
XDR
technology and works on various data sources after
normalization regardless of data types such as logs or
network traffic. When a new data source is ingested, all
existing detections will be directly applied. For example, our
machine learning can perform user behavior analysis based
on behavior data from different data sources. Machine
learning inference is natively embedded in our data
processing pipeline without the need to send data outside.
Endpoint detection and response tools

Adaptive

Stellar Cyber goes wherever you need it to go – on-premise,
in the cloud or hybrid. Multi-tenancy is built in from the
beginning to ensure flexible, secure operations for any
organization. Multi-site allows data to stay resident in its own
region to be compliant and scalable in complex operating
environments.
Extended detection and response

Explainable And Actionable

The ultimate goal for detection is to take action to stop attacks
and to keep your environment safe. Action-taking is a serious
decision; security analysts need to fully understand the situation
in order to make an informed decision regarding what is the
best action to take. With the latest explainable AI, instead of
being a black box, the AI Engine provides human-friendly
evidence and easy-to-digest-details from ML models to ease
decision-making. With that, security analysts can easily
understand the reasons and evidence for any detection in order
to block an attack with high confidence without mistakenly
interrupting protected users or applications.