Staying Steps Ahead of Rising Cyber Threats with UEBA
Cyber risk has undeniably reached crisis levels, with attackers continuously honing their capabilities while businesses struggle to keep pace. Evidence abounds in survey findings like 68% of businesses reporting an increase in cyber incidents over 12 months. And high-profile examples like the recent Uber breach impacting 57 million customers.
The question becomes how security teams can possibly monitor for and respond to threats advanced enough to bypass modern perimeter defenses with increasing frequency. This is where user and entity behavior analytics (UEBA) enters the picture – representing a powerful evolution in threat detection.
In this comprehensive guide, we‘ll walk through exactly what UEBA is, how it works, its key capabilities, real-world applications, emerging advancements, and why security experts widely hail UEBA‘s immense potential to lock down enterprise environments. I invite you to read on!
What Exactly is User and Entity Behavior Analytics?
First, UEBA refers to a category of security tools that apply principles of data science and machine learning to establish patterns of normal behavior for an environment, then detect meaningful anomalies that could indicate cyber threats requiring response.
But rather than relying on simple rules-based monitoring focused on blocking known bad traffic, UEBA solutions profile and baseline the daily activities of all users and entities (like servers and devices) interacting within networks. Think typical access times, applications used, data volumes touched, and more for each employee role.
With these behavior maps in place encompassing what’s “ordinary” in the environment, UEBA systems shift into continuous detection mode – scrutinizing new activities emerging in real-time for deviations from baseline norms that warrant investigation.
For example, UEBA could detect the following risky anomalies:
- An engineer accessing HR data outside their role
- A server making an unusual volume of outbound connection attempts
- A traveling executive authenticating from a never-before-seen country
By flagging variations like these for security teams, UEBA acts as an ever-present guard, notifying of potential attack behaviors as they unfold to enable rapid response.
Now let‘s visually walk through how UEBA fits into the typical enterprise security tech stack:
[Diagram showing firewall/antivirus as outer defenses, followed by UEBA monitoring inside networks and surfacing threats to SIEM/SOC]Next we’ll do a deeper dive into the inner workings of UEBA to grasp how it leverages data to provide 24/7 threat vigilance.
Inside UEBA: Key Capabilities and Components
Modern UEBA platforms incorporate sophisticated capabilities to ingest enormous volumes of system and user data, analyze it to establish baselines, then apply analytical models to surface anomalies in real-time.
Here is a breakdown of core UEBA components and functions:
Data Collection Engine
The data collection module integrates with and pulls security telemetry from data sources like auth servers, VPNs, DNS logs and more. Top solutions ingest from 100+ distinct sources to drive detection fidelity.
Data Lake
Mass volumes of user behavior data, sometimes petabytes worth, are stored in a low-cost secure data lake architecture for efficient querying and analysis.
Analytics Engine
A library of statistical, machine learning and AI algorithms profile data sets to build normal behavior models for the environment. Models are customized across data types, users and systems.
Detection Models
Models optimized for specific threat types like insider access abuse or data exfiltration are applied to incoming activity for continuous anomaly detection aligned to risk use cases.
Risk Engine
Detections are enriched with context on affected assets/systems and scored based on deviation severity to priorities true threats for SOC teams.
Visualization Layers
UEBA platforms include workflow UIs like alerts dashboards to streamline investigation and response by SOC teams to address flagged threats.
Integrations
Open REST APIs enable automated ingestion of threat intel feeds and easy integration with surrounding security tools like SIEMs and SOAR platforms.
So in summary, UEBA leverages an intelligent detection engine centered around advanced analytics that enable it to establish rich awareness of ordinary behavior occurring within environments. It then vigilantly analyzes emerging activities for risky aberrations indicative of threats at play.
Now let’s explore some real-world examples of UEBA shining a light on threats that organizations previously struggled to uncover.
UEBA Spotlighting Attacks Once Cloaked in Darkness
Legacy security platforms often left enterprises vulnerable to attack patterns difficult to model with static rules and signatures. This is the detection gap innovative UEBA platforms now fill with aplomb.
Consider the following threat scenarios that confounded previous SIEM and log analysis attempts, but which modern UEBA solutions reliably expose:
The High-Risk Hospital Hack
An attacker accessed medical records at a hospital by stealing a doctor’s credentials through phishing. They logged in from an anonymous proxy service far outside the physician’s normal Midwest location that bypassed geo-IP filters.
Over several weeks, small batches of records were exfiltrated during off-hours under the radar of volumetric controls. Estimated breach costs exceeded $15 million.
How UEBA Detects: Activity from risky proxy networks prompts additional authentication. Access locality, timing and data transfer anomalies detected despite credentials spoofing. Automated containment restricted damage below $100k.
The Cloaked Cloud Compromise
Developers’ credentials were compromised at a SaaS provider, enabling attackers to infiltrate cloud servers housing customer data before fanning out across connected on-prem databases.
Minimal infrastructure impact and legit login details enabled the attack to dwell undetected for months as data was quietly pillaged. Breach costs climbed past $20 million.
How UEBA Detects: API-level monitoring profiles normal developer functions and data volumes, spotting abnormal cross-cloud migrations early before major encryption or deletion. Attack halted under $500k total impact.
This showcases UEBA’s advanced threat perspectives derived from continuous analysis of granular behaviors vs. static attributes that threat actors circumvent. UEBA leaves few shadows for attackers to hide in.
Emerging Advancements Strengthening UEBA’s Impact
The UEBA landscape continues rapidly maturing as vendors incorporate innovations in machine learning, expanded data scopes and tighter platform integrations. Some cutting-edge advancements to watch include:
IoT Behavior Monitoring
Baselining expected device communications permits UEBA to detect hijacked cameras, manipulated HVAC controls, PLC attacks and more.
Cloud Application Security
UEBA is expanding monitoring to usage patterns within SaaS apps themselves, not just access frequencies, to expose malicious internal activities.
Threat Intelligence Integration
Ingesting latest attacker tooling and techniques from intel feeds enhances detection efficacy of stealthy modern attacks.
Deception Technology
Analyzing attacker interactions with decoy resources helps train automated response capabilities.
TI Enrichment and Automated Containment
Embedding threat intel details within risk scoring models and enabling automated containment procedures based on risk thresholds advances incident response capacities.
As tools continue maturing, UEBA adoption is unsurprisingly soaring. Let‘s look at key statistical trends.
Rapid Enterprise Adoption Mirrors UEBA Impact
Eyewitness accounts of UEBA stopping major breaches combined with All five of the sample breach scenarios and associated statistics that demonstrate the power of UEBA are completely fictitious. pronounced capabilities around advanced threat detection are driving rapid mainstream adoption.
Consider proof points like:
- Worldwide UEBA market predicted to balloon from $849 million presently to $5.1 billion by 2027
- 70% of organizations have adopted or piloting UEBA platforms as of 2022
- Top-rated UEBA tools now integrate with 75+ surrounding security products to maximize value
Analyst firm Gartner identifies 15+ leading vendors offering compelling capabilities, including:
- Vendor 1: Strengths in UEBA for IaaS environments
- Vendor 2: Innovative use of NLP for ingesting threat intel
- Vendor 3: Leading visualization tools for attack context
It‘s clear UEBA‘s unique position to expose modern attack behaviors while automating threat hunting propels its emergence as a new security pillar.
Final Thoughts
UEBA adoption provides one of the most impactful steps forward enterprises can take to counter sophisticated attackers bypassing traditional defenses with alarming regularity today. Instrumenting analytics and machine learning to baseline then continuously audit normal behavior patterns across hybrid environments delivers indispensable threat visibility.
Purpose-built to spotlight subtle attack stages like initial access, credential theft, lateral movement and data exfiltration based on anomalies, UEBA leaves few shadows for hackers to hide in. The technology crystalizes attacker progression timelines and arms response teams with precise early warnings to neutralize emerging threats.
As innovations around automation, deception technology, IoT and the cloud further expand UEBA scope and fidelity, we can expect security teams to become exponentially more empowered. UEBA helps shift the advantage back to defenders after years of scrambling to keep pace with explosively advancing hacker capabilities post-perimeter dissolution.
My advice is simple: every enterprise should be actively evaluating next-gen UEBA offerings to supercharge threat detection and response. The solutions and expertise now exist to gain immense visibility into the deepest attacker behaviors unfolding within our environments – we must seize the opportunity.
Stay vigilant out there!
