Why UEBA Can’t Stop Modern Attacks

The UEBA Security Gap

UEBA identifies anomalous user and entity behavior, but it relies on predefined baselines and statistical models that attackers can evade. Sophisticated threats, insider attacks, and cloud-based compromises often bypass UEBA detections, leaving security teams with too many false positives and a lack of real-time visibility into attacker behavior.

How Attackers Evade UEBA

1. Slow & adaptive attacks 

Attackers blend into normal activity, slowly escalating privileges to avoid triggering anomalies.

2. Cloud & SAAS blind spots 

UEBA often lacks deep visibility into modern cloud and SaaS applications, where identity-based attacks occur.

3. Alert overload & false positives 

UEBA generates a high volume of alerts, making it difficult for SOC teams to focus on real threats.

The Real-World Consequences of UEBA Visibility Gaps

In the Scattered Spider scenario below, UEBA fails not because it’s irrelevant—but because it lacks the speed, scope, and specificity to detect attacker behavior in a modern hybrid attack. 

UEBA Detects Anomalies—Modern Attackers Adapt

UEBA analyzes behavior, but it lacks real-time detection and deep context into attacker movement across networks, cloud, and identities. Attackers who slowly change behavior or use stolen credentials can bypass UEBA entirely.

UEBA applies statistical modeling and behavioral baselining, but:

• What if an attacker escalates privileges slowly? UEBA might not flag incremental changes as malicious.
• What if cloud-based threats go undetected? UEBA often lacks deep integration with SaaS and hybrid cloud workloads.
• What if there’s too much noise? Security teams are overwhelmed by alerts that lack clear prioritization.

How Vectra AI Fills the Gap

UEBA identifies deviations from normal behavior, but it struggles to detect slow, stealthy, and cloud-based attacks. The Vectra AI Platform provides real-time threat detection that exposes attacker movement beyond behavioral anomalies.

• Detects active attacks: AI identifies real threats, not just statistical outliers.
• Monitors cloud & identity risks: Provides deep visibility into hybrid and SaaS environments where UEBA struggles.
• Reduces alert fatigue: Surfaces high-confidence detections, cutting through noise.

Vectra AI maps identity behavior over time, tracking what is considered normal for both human and non-human identities. This allows the system to detect privilege abuse, unauthorized lateral movement, and risky automation behaviors—all with 96% fewer alerts than traditional UEBA solutions.

How Vectra AI Compares to UEBA

UEBA identifies anomalies, while Vectra AI detects real threats beyond behavior deviations. Here’s how they compare: