Cosa abbiamo imparato dall'analisi di milioni di avvisi

Fact: Security professionals are drowning in detection noise.

This isn’t new, but it can get worse.  

As enterprises evolve into AI-driven environments, the volume of activity across identity, cloud, SaaS, and network has exploded. Every authentication, API call, workload interaction, and AI-powered process generates telemetry. And with that comes more alerts. This results in security teams being buried in signals but struggling to find what actually matters.  

So, we asked a simple question: What’s really happening underneath all that noise and how can teams investigate and respond faster?

To find out, we analyzed millions of detections across our managed services and Respond UX deployments to understand where real threats exist and how security teams can cut through the noise to investigate and respond faster.  

Modelli che abbiamo osservato

Senza svelare tutto (ti consigliamo di leggere il rapporto completo), ecco alcuni temi che abbiamo scoperto:

• Dopo il triage, la prioritizzazione, l'unione e l'analisi effettuati Vectra AI , meno dello 0,1% dei rilevamenti risulta essere una minaccia reale.  

• Gli attacchi basati sull'identità stanno diventando sempre più frequenti, soprattutto da luoghi che spesso trascuriamo.

• I rilevamenti personalizzati sono più importanti di quanto molti credano, soprattutto quando si tratta di individuare minacce di alto valore.

Perché è importante

Why noise slows you down

Every false positive wastes investigation time, delays real threat response, and increases analyst fatigue. And in today’s AI-driven environments, where human and non-human identities are multiplying and constant, noise only scales. Meanwhile, attackers are accelerating with AI.  

How to investigate and respond faster

• Prioritize real signal: use AI to surface the small fraction of activity that indicates real risk

• Focus on identity: most modern attacks are identity-driven so this is where the context lives

• Connect the dots: correlate activity across the modern network to see the full attack

• Automate investigation: eliminate manual stitching so analysts can act immediately  

You don’t investigate faster by working harder. You investigate faster by reducing noise, elevating real threats, and acting on high-confidence signals. Because speed comes from knowing what matters, not seeing everything.  

Leggi il rapporto completo: Ridurre il rumore, aumentare le minacce