UEBA · Product Overview

Forensic CyberTech Pvt. Ltd.
UEBA

Catch the threats that look like normal users.

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Detection models working in one ensemble

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MITRE ATT&CK-mapped detection rules

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Behavioral features tracked per entity

Real-Time

Continuous behavioral monitoring & scoring

01 — Executive Summary

What is UEBA?

UEBA is a behavioral threat-detection platform. It continuously builds a behavioral baseline for every user and entity in your environment — logins, network activity, privilege use, devices — and scores each entity in real time against that baseline, its peer group, and a library of attacker techniques.

It is built for SOC teams, MSSPs, and security-conscious enterprises running Active Directory / Windows environments. These organizations are blind to the most damaging attacks — stolen credentials, malicious insiders, and lateral movement — because the attacker uses valid access. There is no malware signature to match and no firewall rule to trip.

What makes UEBA different: it does not rely on a single algorithm or a static rule set. It combines a 10-model detection ensemble, 93 MITRE ATT&CK-mapped rules, and per-user behavioral baselines — and then explains every alert in plain language, so analysts can act in seconds instead of guessing.

The Problem

What goes wrong without UEBA?

The perimeter is no longer where breaches happen. Today's most costly attacks come from inside — using credentials and access that look completely legitimate. Traditional tools see nothing wrong.

Stolen credentials bypassing traditional security defenses

Stolen credentials walk right past your defenses

The majority of breaches involve valid, stolen, or misused credentials. A firewall or antivirus cannot tell a real employee from an attacker using that employee's password — both look "allowed." The only signal is behavior that doesn't fit.

Insider threat behavior without malware signatures

Insider threats have no signature

A disgruntled employee or a compromised account uses access they are authorized to have. There is no malware to detect and no rule to write — only a change in how that person normally behaves can reveal it.

SOC overwhelmed by unexplained black-box alerts

Black-box alerts drown the SOC

Most analytics tools produce a risk score with no explanation, burying teams in alerts they can't trust or triage. Analysts waste hours per alert, and real threats get lost in the noise.

Key Features

What does UEBA do?

UEBA pairs deep machine learning with deterministic, attacker-technique rules — then makes every decision transparent to the analyst.

  • 10-model ensemble fused into one weighted risk score
  • 93 MITRE ATT&CK-mapped rules firing from day one
  • Every alert explained in plain language — no black box

10-Model Detection Ensemble

Core engine

93 MITRE ATT&CK-Mapped Rules

Day-1 detection

Per-User & Peer-Group Baselines

Adaptive

Explainable AI — Every Alert Justified

No black box

Real-Time Streaming Detection

Streaming

Natural-Language Investigation

AI-assisted
How It Works

Simple to run. Powerful under the hood.

UEBA ingests your existing logs, learns what “normal” looks like for every user and device, and continuously scores activity against that baseline — raising and explaining alerts the moment behavior drifts into attack territory.

What it watches
Logins & failed logins (who, when, from where)
Network connections & destinations
Privilege changes & group membership
Account creation, enable & deletion
Kerberos & authentication patterns
Audit-log clearing & defense evasion
Devices, sessions & time-of-day behavior
What it does
Scores every entity 0–100 in real time
Raises severity-graded alerts (low → critical)
Correlates related alerts into incidents
Explains each alert in plain language
Maps findings to MITRE ATT&CK
Streams alerts live to the dashboard
Use Cases

Who uses UEBA and how?

Use Case 01

Compromised account detection

An attacker logs in with valid stolen credentials, then behaves unlike the real user — new device, odd hours, sudden access to systems they never touch. UEBA catches the behavioral shift across multiple models, raises a high-severity alert with the exact evidence, and lets the SOC contain the account before damage spreads.

Use Case 02

Insider threat & data staging

A departing or disgruntled employee quietly accesses far more than usual. Cumulative-deviation tracking flags the slow, low-and-slow build-up that single-event rules miss.

Use Case 03

Lateral movement detection

One account suddenly authenticates across many internal hosts. The authentication-graph engine detects the fan-out pattern characteristic of an attacker moving east-west through the network.

Use Case 04

Privilege escalation monitoring

A non-admin account is added to a privileged group or starts performing admin actions. UEBA flags the escalation chain in real time, mapped to MITRE T1098 / T1548.

Use Case 05

Brute force & password spray

Repeated failed logins against one account — or one password tried across many accounts — are detected and distinguished from benign noise, with account-diversity checks that suppress false positives from stale credentials.

Why UEBA

What sets us apart.

10×

Ten models, one verdict — defense in depth, not a single guess

Most tools lean on one or two algorithms that can be evaded or that flood teams with false positives. UEBA runs ten complementary detectors — statistical, deep learning, density, boundary, graph, and deterministic rules — and fuses them into one calibrated, weighted score. A threat has to beat the whole ensemble, not a single model.

Explained

No black box

Every alert ships with a model-by-model breakdown and a plain-language analyst verdict — so teams trust and act on what they see.

Self-hosted

Your data stays yours

Deploy on-premise or in your own cloud with Docker. No per-gigabyte licensing meter, and sensitive logs never leave your environment.

FP-safe

Engineered against false positives

A baseline warm-up period, account-diversity gating, and evidence-based model calibration keep alerts meaningful instead of noisy.

ATT&CK

MITRE-native detection

Detections are mapped to MITRE ATT&CK techniques out of the box, so findings speak the language your SOC already uses.

Market Comparison

UEBA vs. the market

Enterprise UEBA suites are powerful but heavy — expensive per-GB licensing, cloud-locked data, and opaque scoring. UEBA delivers the same detection depth with transparency, deployment freedom, and a cost model that fits teams of any size.

CapabilitySplunk UBAMicrosoft Sentinel UEBAExabeamUEBA
Multi-model detection ensemble
Limited set
Limited set
Yes
10 models, one weighted score
Per-user & peer-group baselining
Yes
Yes
Yes
Per-user + peer, 1h–30d windows
Insider threat & lateral movement
Yes
Yes
Yes
Auth-graph + 93 rules
Low-and-slow / gradual drift detection
Partial
Partial
Yes
Cumulative deviation (7/14/30d)
Real-time streaming detection
Yes
Yes
Yes
Kafka streaming pipeline
Plain-language explanation per alert
Partial
Partial
Partial
AI analyst verdict on every alert
Natural-language investigation
Query language
Yes
Partial
Built-in NL log search
MITRE ATT&CK-mapped detections
Yes
Yes
Yes
93 mapped rules out of the box
Self-hosted, data stays on-prem
Yes
Cloud-first
Cloud-first
On-prem or your cloud
Deployment footprint
Heavy / complex
Cloud setup
Heavy / complex
Single Docker Compose stack
★ denotes a capability that is a particular strength of UEBA. Comparison reflects general product positioning as of 2026 and is based on publicly available information; verify current details directly with each vendor.
Getting Started

From deployment to detection.

UEBA installs as a self-contained stack and begins protecting your environment as soon as your logs start flowing.

Deploy the stack

Stand up UEBA on-premise or in your cloud with Docker Compose — databases, streaming, ML engine, and dashboard included.

Step 01

Connect your logs

Point UEBA at your Windows Active Directory / Event Logs, firewall, or SIEM. A universal parser ingests virtually any vendor format via REST, WebSocket, Kafka, or webhook.

Step 02

Learn the baselines

UEBA automatically builds per-user and peer-group baselines during a short learning period, while deterministic rules already catch known attacks from day one.

Step 03

Detect & alert

The ensemble scores every entity in real time as events stream in, raising severity-graded, MITRE-mapped alerts the moment behavior drifts into attack territory.

Step 04

Investigate & respond

Analysts triage from a single dashboard — every alert explained, correlated into incidents, and searchable in plain English. You're catching real threats, fast.

Step 05
Specifications

Architecture & performance

Detection engine capabilities and platform architecture for planning a production UEBA deployment.

Detection Engine

Detection models10-component weighted ensemble
Rule library93 MITRE ATT&CK-mapped rules
Behavioral features130+ per entity
Baseline windows1h / 6h / 24h / 7d (rolling)
Long-range drift tracking7d / 14d / 30d (low-and-slow detection)
Detection modeReal-time streaming

See UEBA on your own data.

Book a live demo and we'll show UEBA detecting real attack scenarios — brute force, lateral movement, privilege escalation — in minutes. No rip-and-replace, no per-GB surprises.

Request a Demo