Both IT teams and end users are afflicted by password reset tickets. IT teams will often push more urgent issues down the queue to ensure that users don't have their work put on hold while their passwords reset. Password reset tickets can be costly if they aren't addressed promptly. Nearly 30 percent of all help desk tickets were caused by forgotten passwords. It is not surprising that large companies have spent more than $1 million to resolve password-related help desk requests. It is a good habit to change passwords regularly, as it helps prevent cyberattacks caused by stolen credentials. Security experts recommend that administrators ensure that users change their passwords regularly and have password expiration policies in place.
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Predict360, by 360factors, is a risk and compliance management and intelligence platform that automates workflows and enhances reporting for banks, credit unions, financial services organizations, and insurance companies.
The SaaS platform integrates regulations and obligations, compliance management, risks, controls, KRIs, audits and assessments, policies and procedures, and training in a single cloud-based SaaS platform and delivers robust analytics and insights that empower customers to predict risks and streamline compliance.
Happy with your current GRC but lacking a true analytics and BI tool for intuitive executive and Board reports? Ask about Lumify360 from 360factors - a predictive analytics platform that can work alongside any GRC. Keep your process management workflows intact while providing stakeholders with the timely reports and dashboards they need.
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KubeArmor
KubeArmor is an open-source, cloud-native security engine that provides runtime enforcement for Kubernetes clusters, containers, and virtual machines, using eBPF and Linux Security Modules such as AppArmor, BPF-LSM, and SELinux. It protects workloads by restricting behaviors like process execution, file operations, networking, and resource consumption, all enforced through customizable, Kubernetes-native policies. Unlike traditional post-attack mitigations that react after malicious activity occurs, KubeArmor’s inline enforcement blocks threats proactively without requiring changes to containers or hosts. Its simplified policy descriptions and non-privileged daemonset architecture make it easy to deploy and manage across diverse environments, including multi-cloud and edge networks. The platform logs policy violations in real time and supports granular network communication controls between containers. Installation can be done effortlessly using Helm charts, with detailed documentation and video guides available. KubeArmor is listed on AWS, Red Hat, Oracle, and DigitalOcean marketplaces, demonstrating broad industry acceptance. It also offers specialized features for IoT, 5G security, and workload sandboxing, making it a versatile choice for modern cloud-native security.
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Azure Kubernetes Fleet Manager
Efficiently manage multicluster environments for Azure Kubernetes Service (AKS) that involve tasks such as workload distribution, north-south traffic load balancing for incoming requests to various clusters, and coordinated upgrades across different clusters. The fleet cluster offers a centralized management system for overseeing all your clusters on a large scale. A dedicated hub cluster manages the upgrades and the configuration of your Kubernetes clusters seamlessly. Through Kubernetes configuration propagation, you can apply policies and overrides to distribute resources across the fleet's member clusters effectively. The north-south load balancer regulates the movement of traffic among workloads situated in multiple member clusters within the fleet. You can group various Azure Kubernetes Service (AKS) clusters to streamline workflows involving Kubernetes configuration propagation and networking across multiple clusters. Furthermore, the fleet system necessitates a hub Kubernetes cluster to maintain configurations related to placement policies and multicluster networking, thereby enhancing operational efficiency and simplifying management tasks. This approach not only optimizes resource usage but also helps in maintaining consistency and reliability across all clusters involved.
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