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Vectra AI Blog

AI-Driven Network Detection and Response: Insights from a 2026 Gartner® Magic Quadrant™ Leader Securing AI Adoption Starts with Visibility by Aakash Gupta The Missing Data Layer Behind SIEM and SOAR Why Most SIEM/SOAR Integrations Break — and How to Fix Them Shai-Hulud Part 2: When the Worm Forged Its Own Security Certificate Improve SIEM and SOAR Workflows with Better Security Signal by Gearóid Ó Fearghaíl ShinyHunters isn’t a group. It’s a pattern. How Vectra AI Secures the AI Enterprise AI agents: the new workforce — and attack surface. by Tiffany Nip How Vectra AI Scoring Helps Security Teams Focus on What Matters First What’s Next for the Enterprise After Two GenAI Tidal Waves? If An Identity was Compromised, Would We Know? Help Over Hype: Claude Mythos, Project Glasswing and the Real Questions CISOs Want Answered Azure Logging just Changed - Your Detections May be Missing it by Alex Groyz When the Defender Becomes the Door: BlueHammer, RedSun, and UnDefend in the Wild by Justin Howe 4 Ways to Improve SOC Efficiency with AI by Jesse Kimbrel Why triage alerts - when AI can do it for you? Attackers Don’t Hack In — They Log In: The MFA Blind Spot The rise of supply chain-driven data theft in SaaS environments by Lucie Cardiet AI-Assisted Search: Clarity at the Speed of a Question FortiClient EMS Zero-Day: When the Control Plane Becomes Initial Access by Lucie Cardiet Detecting Compromise After the Axios Supply Chain Attack. by Yusri Mohd Yusop Who’s Doing What on Your Network? by Mark Wojtasiak Breaking down the axios supply chain incident by Lucie Cardiet Detecting Sliver C2: When Advanced Beaconing Tries to Hide in Plain Sight Prompt Control: How Context Becomes the Command-and-Control Layer for AI Agents How Attackers Move Through Hybrid Networks After the Initial Breach How Attackers Establish Persistence in Hybrid Environments What the Stryker Incident Reveals About Handala’s Attack Playbook Why Cyber Resilience is Lagging in the AI Era 5-Minute Hunt: Six Queries to Detect Iranian APT Activity AI-Powered Attacks Are Here, But So Is AI-Powered NDR to Stop Them What is hiding in AI traffic AWS Compromised by AI Agents in Minutes The UX of Cybersecurity AI: Designing for Behavior at Machine Speed Molt Road and the Automation of Underground Marketplaces Moltbook and the Illusion of “Harmless” AI-Agent Communities From Network Detections to Understanding Risk: The Vectra AI Take on Gartner’s Redefinition of NDR From Clawdbot to OpenClaw: When Automation Becomes a Digital Backdoor Securing the AI Enterprise: How I’m Thinking About It as a CEO Cybersecurity Predictions 2026: AI, Agents, and SOC Defense OPSEC Failures: How Threat Actor Mistakes Help Defenders How Threat Actors Turned AI Into a Weapon CVE-2025-14847 MongoBleed in the Wild: Identifying MongoDB Exposure and Exploitation with Network Metadata by Fabien Guillot Pro-Russia Hacktivists Are Targeting Critical Infrastructure How Vectra AI Connects Network Detections to Endpoint Processes Automatically by Dale O’Grady How Vectra AI and CrowdStrike Deliver Complete Context Across Endpoint and Network by Tiffany Nip You are the Blackboard - AI Agent Assisted Bug Hunting TCP Reset Does Not Stop Modern Attacks – Here's Why Shai-Hulud: When a Supply-Chain Incident Turns Into a Worm How Typhoon APTs Infiltrate Infrastructure Without Leaving a Trace Think Your Microsoft Environment Is Resilient to Attacks? 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What We Learned from Analyzing Millions of Alerts
2026-04-13 · via Vectra AI Blog

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.  

Patterns We Saw

Without giving it all away (you’ll want to check out the full report), here are a few themes we uncovered:

  • After Vectra AI Agents’ triage, prioritization, stitching, and analysis, less than 0.1% of detections are real threats.  
  • Identity-based attacks are dominating, especially from places we often overlook.
  • Custom detections matter more than many realize, especially when it comes to surfacing high-value threats.

Why This Matters

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.  

Check out the full report: Reducing Noise, Elevating Threats