How does it differ from a SIEM or EDR?

Vectra AI focuses on network-based detection and response, filling visibility gaps left by endpoint (EDR) and log-based (SIEM) tools. It detects attacker behavior and lateral movement across the entire network, even where agents can't be installed.

Does it require agents on every device?

No. Vectra AI is primarily a network detection and response (NDR) solution. It operates via network sensors (physical or virtual) that mirror traffic, providing agentless visibility. It can enrich this with identity data from cloud and on-prem sources.

Can it automatically respond to threats?

Yes. Its 360 Response module allows for enforced containment actions like quarantining a host, terminating a malicious session, or blocking traffic, directly from the platform.

What are the deployment requirements?

Deployment involves installing Vectra 'Brain' (analysis) and 'Sensor' (data collection) appliances—either on physical hardware or as virtual machines. Traffic mirroring from network taps or switches is required. Cloud deployments use virtual sensors for VPC visibility.

How accurate are the detections?

Vectra AI claims an alert fidelity of over 80%, meaning most alerts represent true positive threats. This high signal-to-noise ratio is achieved through continuous machine learning training on real-world attack data.

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Vectra AI

Vectra AI is an AI-driven cybersecurity platform that provides real-time network detection and response (NDR), identity threat detection, and cloud security posture management. Its core capability is Attack Signal Intelligence, which uses machine learning to analyze network, identity, and cloud traffic to detect and prioritize malicious behavior, reducing blind spots and analyst workload. The platform targets security operations teams (SecOps), CISOs, and managed detection and response (MDR) providers in enterprise environments, helping them stop sophisticated attacks like account takeovers and lateral movement across hybrid and multi-cloud infrastructures.

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Added on

Sep 17, 2026

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AI-driven NDRReal-time analyticsHybrid cloud supportIdentity threat detectionAutomated responseManaged MDR services

Product information

Everything worth knowing about Vectra AI

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Network Observability

Provides real-time visibility across on-premises and multi-cloud environments to continuously identify and reduce attack exposure risk.

Threat Detection & Response

Uses AI-driven Attack Signal Intelligence to detect, investigate, and stop cyber attacks at machine speed, with high alert fidelity.

Exposure Management & Posture Improvement

Tracks risk reduction, validates security controls, and delivers audit-ready proof in real time to strengthen security posture.

Managed Detection & Response (MXDR/MDR)

Offers managed services for threat detection and response, providing expert oversight and accelerated incident handling.

Technical capabilities

Attack Signal Intelligence

Proprietary AI analyzes network traffic and identity signals in real-time to pinpoint active compromises and malicious behavior.

360 Response

Enforced containment capability across identity, devices, and network traffic to stop attacker progression.

Must watch videos

41:20

Tutorial41:20

Designing the Agentic SOC

What happens when the attacker changes faster than the defenses built to stop them? In this episode of the Hunt Club Podcast, host Mark Wojtasiak, SVP of Research and Strategy at Vectra AI, talks with Padraig Mannion, Director of UX at Vectra AI, about why designing today’s defenses is as much a UX challenge as a technology challenge. Using the evolution of the star fort as a starting point, they explore why security operations must move beyond disconnected alerts and toward a clearer understanding of attacker behavior, movement, and full attack narratives. They discuss how AI-enabled attackers are changing the speed and scale of cyberattacks, what security teams need from an agentic experience, and why the goal should be effectiveness against real attacks—not simply processing more events faster. Read Padraig’s blog: When the Wall Stops Working: What Post-Fortress Architecture Teaches Cybersecurity UX: https://www.vectra.ai/blog/when-the-wall-stops-working-what-post-fortress-architecture-teaches-cybersecurity-ux Chapters 00:00 — Introducing Padraig Mannion and the UX perspective 01:00 — The star fort: when a once-modern defense stops working 07:00 — From security signals to understanding attacker movement 12:00 — AI-powered attacks at machine speed 16:00 — Designing a security experience for defenders and agents 24:00 — Why attack narratives matter more than individual events 29:00 — Designing for efficacy, not just efficiency 35:00 — Rethinking defense around how attackers actually operate 39:00 — Applying design thinking to the future of the SOC -- About Vectra AI -- Vectra AI is the AI-native security and observability company. We help organizations regain control of modern cyber risk by delivering unified observability, attack signal intelligence, and resilient control across on-premises, cloud, identity, AI agents, SaaS, edge, and IoT/OT environments. The result is reduced exposure, faster response, and stronger cyber resilience. For more information, visit www.vectra.ai.

Interview with Morgan Gardner, Security Analyst

17:39

Tutorial17:39

Interview with Morgan Gardner, Security Analyst

In this Hunt Club customer interview, Morgan Gardner, Security Analyst for a global organization, shares how her team is scaling security across six business units through better prioritization, correlation and a people-first approach to standardization. The goal is not perfect uniformity. It is helping each team focus on the entities that matter, with the context to make faster, more confident decisions across a complex environment. Watch the full conversation. -- About Vectra AI -- Vectra AI is the AI-native security and observability company. We help organizations regain control of modern cyber risk by delivering unified observability, attack signal intelligence, and resilient control across on-premises, cloud, identity, AI agents, SaaS, edge, and IoT/OT environments. The result is reduced exposure, faster response, and stronger cyber resilience. For more information, visit www.vectra.ai.

From Questions to Insights: Inside Vectra AI's Observability Dashboards

21:06

Tutorial21:06

From Questions to Insights: Inside Vectra AI's Observability Dashboards

In this product briefing, Zoey and Gearoid discuss how Vectra AI’s observability dashboards reveal real activity across an environment, support AI governance, post-quantum cryptography readiness, and segmentation validation, and turn security insights into actionable workflows. -- About Vectra AI -- Vectra AI is the AI-native security and observability company. We help organizations regain control of modern cyber risk by delivering unified observability, attack signal intelligence, and resilient control across on-premises, cloud, identity, AI agents, SaaS, edge, and IoT/OT environments. The result is reduced exposure, faster response, and stronger cyber resilience. For more information, visit www.vectra.ai.

Who uses it

Real use cases, no hype

Identity Attack Detection & Response

Detect and stop account takeovers, credential stuffing, and MFA bypass in real-time before data breach.

Lateral Movement Containment

Identify attacker progression within your network and enforce automated containment to stop ransomware spread.

EDR Gap Detection

Uncover threats and compromised assets that endpoint detection tools miss.

Cloud & On-Prem Observability

Gain unified visibility across hybrid environments to reduce attack exposure.

Automated Threat Investigation

Use AI to triage alerts and provide security analysts with prioritized, context-rich incidents.

Continuous Compliance Validation

Prove security posture and validate controls are effective for audits in real-time.

What's great

AI-driven detection reduces analyst workload by 38x
Excellent visibility into lateral movement and identity attacks
Strong Gartner Magic Quadrant leader for NDR
Rapid integration, with one client adding 50+ detections in a day

Technical strengths

Proprietary Attack Signal Intelligence (ASI) provides real-time, machine-learning-based threat scoring
Covers >90% of MITRE ATT&CK framework with AI models trained on 11+ years of threat data

Where it falls short

Enterprise pricing is not transparent; requires sales engagement
Complex deployment and configuration for optimal value
Dependency on their cloud-hosted platform for core analytics

Technical limitations

Optimal performance requires deployment of dedicated 'Brain' sensors or virtual appliances
Alert fidelity (80%+) can still produce noise requiring tuning for specific network contexts

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

Vectra AI uses its proprietary Attack Signal Intelligence (ASI) engine. This is a set of machine learning models that analyze network metadata to detect attack behaviors and compute a 'threat score' in real-time, distinguishing malicious activity from benign noise.