Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How Cato Uses Large Language Models to Improve Data Loss Prevention

Cato Networks has recently released a new data loss prevention (DLP) capability, enabling customers to detect and block documents being transferred over the network, based on sensitive categories, such as tax forms, financial transactions, patent filings, medical records, job applications, and more. Many modern DLP solutions rely heavily on pattern-based matching to detect sensitive information. However, they don’t enable full control over sensitive data loss.

Microsoft Azure Red Hat OpenShift (ARO) and Trilio Data Protection: Uniting Cloud-Native Excellence

With the exponential growth of cloud adoption and the widespread shift to Kubernetes as the de facto orchestration platform, Red Hat OpenShift emerges as a leading solution. Coupled with the robust cloud infrastructure of Microsoft Azure, Red Hat OpenShift on Azure (ARO) is a managed service that offers OpenShift clusters on Microsoft Azure. It is jointly engineered and operated by Microsoft and Red Hat with an integrated support experience.

Trustwave Embarks on an Extended Partnership with Microsoft Copilot for Security

Trustwave today announced it will offer clients expert guidance on implementing and fully leveraging the just-released Microsoft Copilot for Security, a generative AI-powered security solution that helps increase the efficiency and capabilities of defenders to improve security outcomes.

Keeper 102 - How to Set Biometric Login in Keeper on iOS

Biometric login, especially when paired with Keeper, is a time saving, convenient feature that allows you to login to Keeper with biometrics such as “Face ID”. To enable biometric login, navigate to the Settings screen in the Keeper app and toggle “Biometric Login”, “on”. Next time you want to log in to Keeper, simply tap the Face ID icon to initiate face recognition. Please note, Face ID must be configured in your device's settings before using it to login to Keeper.

Firewalls for AI: The Essential Guide

As the adoption of AI models, particularly large language models (LLMs), continues to accelerate, enterprises are growing increasingly concerned about implementing proper security measures to protect these systems. Integrating LLMs into internet-connected applications exposes new attack surfaces that malicious actors could potentially exploit.