Vectra for the Financial Services Industry


How a Global Financial Services Firm Stops Cyberattacks


Identify Attack Scenarios Common in Financial Services

  • Expose attacker behaviors without relying on signatures, to easily spot suspicious use of Ammyy, VNC, PuTTY and other remote administration tools
  • Identify Carbanak and other hidden attacks that target financial services and banking organizations
  • Reveal attacker communication in encrypted traffic and hidden HTTPS tunnels without requiring decryption
  • Support specific cybersecurity assessment categories under the Federal Financial Institutions Examination Council (FFIEC)

“Vectra empowered our team to do in minutes what normally requires days.”

“Vectra empowered our team to do in minutes what normally requires days.”

John Shaffer


Greenhill, an independent New York-based investment bank

Vectra empowers financial services and banking firms to detect and respond faster to in-progress cyberattacks – even in encrypted traffic and without using decryption. Driven by AI, Vectra stops data theft and breaches with unprecedented speed across cloud, data center, IoT, and enterprise networks.

Automate threat detections

AI-based machine learning models detect attack behaviors in real-time, prioritize the highest-risk threats, and show exactly where and how to respond and remediate.

Empower threat hunters

Launch deeper and broader investigations into incidents detected by Vectra as well as other security stack controls, and hunt more efficiently for hidden cyberthreats attempting to breach your financial services network.

Visibility into the attack surface

Visibility into threat behaviors in all network traffic – cloud/data center workloads, user/IoT devices, and encrypted HTTPS hidden tunnels – without using decryption.

Capture and enrich metadata

Capture, analyze and enrich metadata from all network traffic with context about attacks, relevant logs and cloud events for faster threat hunting and investigations.

AI-driven Network Detection and Response (NDR)

Attacker behavior detection

Self-learning threat behavior models from data science and security research automatically identify malicious activity, fortify key security attributes and security patterns, normal patterns, precursors, account scores, host scores, and correlated attack campaigns.

Real-time threat hunting

Metadata extracted from all network traffic is enriched with security insights so you know where and what to hunt. SOC teams increase productivity and reduce attacker dwell time by integrating Vectra with your current security ecosystem for end-to-end response automation.

AI and machine learning

AI and ML scale-up to analyze and prioritize huge volumes of threat events to give SOCs the right information at the right time. High-fidelity alerts about in-progress attacks enable faster, informed responses and quick, decisive enforcement actions for a superb ROI.

CDM DEFEND: See What’s Happening on the Network

Aligned with Continuous Diagnostics and Mitigation (CDM) Dynamic and Evolving Federal Enterprise Network Defense (DEFEND) Phase 3, Vectra shows what’s happening in federal and government agencies' cloud, data center, and IoT networks to harden security posture.

Vectra addresses critical elements of Phase 3:

  • Protect: Automatically detect,  triage and prioritize threats that evade boundary protection, enabling faster  mitigation of high risk attacks.
  • Manage: Integrate with your existing security ecosystem – from endpoint detection and response to  orchestration and security information event management – for end-to-end threat management.
  • Respond: Automatically share  critical threat behavior data – including context about attack campaigns and  forensic evidence.
  • Improve: Advanced machine learning algorithms derived from AI continuously learn, becoming more intelligent and operationally effective over time.

How to Detect, Prioritize, and Respond to Federal and Government Cyberattacks











Vectra US Federal & SLED Contract Holder