Case Study: Auto Glass Distributor Company achieves ransomware prevention with Deep Instinct

Auto glass distributor chooses Deep Instinct for explicit ransomware prevention after their current endpoint solution fails to detect an attack

An auto glass distributor based in the US was infected by a ransomware attack, which their traditional antivirus solution failed to prevent. Seeking a more comprehensive security solution to protect its distribution chain, the company chose to evaluate and subsequently implement the Deep Instinct Threat Prevention Platform.

The Deep Instinct solution, which uses a deep learning-powered on-device agent, immediately revealed multiple threats. Within the first week, it detected 11 malicious files, including dormant WannaCry ransomware waiting to execute on five computers. In total, the deployment uncovered 152 unique malware campaigns that had evaded their previous security software, ultimately revealing that 38% of their devices were already compromised.