How Cylance Prevents Zero-Day Attacks and Insider Threats Using AI

By: GoBeyond Team

July 3, 2025

3 min read

AI case study for Cylance – zero-day threat prevention with AI

Quick Overview

Cylance employs AI to analyze file and application characteristics before execution, predicting and blocking malicious threats including zero-day malware. Behavioral analysis monitors user activity deviations to detect insider threats, leveraging a model trained on billions of data points.

Cylance (BlackBerry)

Company Size

~1,000 employees

Revenue Range

Estimated $200M+ annual revenue

Primary Challenge

Need to detect and block novel malware and insider threats before execution to prevent breaches

Key Metrics

\- High-precision threat prevention\- Blocked numerous zero-day attacks\- Reduced insider threat risks

The Problem

Traditional antivirus and detection methods were ineffective against sophisticated, previously unknown malware and insider threats.

The Solution

Utilized AI and machine learning models trained on vast datasets to predict malicious intent pre-execution and behavioral analytics to identify insider threats.

Results

\- Significant reduction in malware infections\- Early detection and prevention of zero-day attacks\- Improved insider threat visibility and mitigation\- Reduced security operations workload