Cloud Workload Protection

Vulnerabilities Hardened in a Heartbeat

Solution overview

 In a world where many companies are using public cloud computing, storage and networking services, there are different cybersecurity threats aiming to gain access to sensitive data and exfiltrate it from the cloud. Effectively detecting and intercepting malicious activity without impeding business processes is therefore the primary mission of every security leader in a cloud-centric environment.

CSPM (Cloud Security Posture Management) and CWPP (Cloud Workload Protection Platforms) solutions can detect and minimize excessive permissions and misconfigurations in the public cloud. This helps decrease cloud attack surface while continuously minimizing alert volume.


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Protecting Cloud Workloads from Data Breaches: Inside Radware's CNP


How Cloud Workload Protection Amplifies Security & Business

AI-Based Anomaly Detection

AI-Based Anomaly Detection

Most infrastructure attacks are built over time. To outsmart them, CSPM should quietly connect the dots, surfacing suspicious patterns while avoiding false positives.

Proactive, Automated Permission Hardening

Proactive, Automated Permission Hardening

Manual permission management at scale is hardly productive. An ideal solution keeps company assets safe while considerably reducing security workload.

Consolidated Visibility

Consolidated Visibility

Existing platform-specific point security products are ineffective at detecting complex attacks. A holistic solution flags anomalies across your entire cloud (or multi-cloud) infrastructure in a single dashboard.

Agile and Configurable

Agile and Configurable

Policy differentiation between teams and units is a crucial Cloud Workload Protection trait. It decreases false alerts, prioritizes actual threats, and enables critical workflows to run uninterrupted.

Implementing Cloud Workload Protection with GlobalDots

  • Less Alerts, Higher Accuracy

    Eliminate alert fatigue by putting an end to unimportant or unactionable alerts.We promote configurable, heavily-automated solutions which will proactively handle most scenarios, and will only flag what truly requires your attention.

  • Real-Time Indications & Suggestions

    Take no prisoners. Sophisticated, cross-infrastructure solutions mean early detection of attack attempts, applying smart correlation of seemingly unrelated, sporadic events along with suggestions for effective, timely remediation.

  • Critical Compliance Simplified

    Take one liability off your plate with quick, automated reporting, compliant with PCI DSS, ISO 27001, SOC2, and more, which apply to both enterprises and enterprise vendors.

  • Behavior Analysis

    ML-based solutions quickly adjust to “new normals” in terms of each team’s work practices, with little or no need to reconfigure. This means less workflow interruptions, and less daily maintenance for you.

Some Background

The Old Insider Is the New Outsider

Moving workloads to the cloud has led to organizations (and IT administrators) losing direct physical control over their workloads and relinquishing many aspects of security through the “shared responsibility model”. As a result, the insider of the old premise-based world is suddenly an outsider in the new world of publicly hosted cloud infrastructure. Employees such as IT administrators, developers and security teams are just like hackers now and have identical access to publicly hosted workloads,using standard connection methods, protocols and public APIs. As a result, the whole world becomes an insider threat. Cloud workload security, therefore, is defined by the people and machines who can access those workloads and the permissions they have.

Your Permissions = Your Attack Surface

Primary reasons for migrating to the cloud include decreasing time to market and streamlining business processes. As a result, cloud environments make it very easy to spin up new resources and grant wide-ranging permissions, but they also make it very difficult to keep track of which users have permissions and who uses them. All too frequently, there is a gap between granted permissions and used permissions. In other words, many users have too many permissions that they never use. Such permissions are frequently exploited by hackers who take advantage of them for malicious purposes. As a result, cloud workloads are vulnerable to data breaches (i.e., theft of data from cloud accounts), denial of service violations (i.e., completely taking over cloud resources) and resource exploitation (such as cryptomining).

In an ideal world, each developer or DevOps engineer would get the minimal amount of permissions to allow them to perform their job,. There is a fine line between the neverending task of reducing the attack surface of excessive permissions and allowing the business to be agile and move fast without the hurdles of security.

Continuous Smart (Mis)Configuration Hardening

To prevent attacks, enterprises must harden cloud workload configurations to address permission abuse, by applying continuous hardening checks. The goals are to avoid public exposure of data from the cloud and reduce overly- permissive access to resources by making sure communication between entities within a cloud, as well as access to assets and APIs are only allowed for valid reasons. Only smart configuration hardening that applies a “least privilege” approach enables enterprises to meet these standards. The process requires applying behavioral analytics methods over time, including regular reviews of entitlements and permissions, and a continuous analysis of each entity’s regular behavior to ensure users only have access to what they need, nothing more. By reducing attack surfaces, enterprises make it harder for hackers to move laterally in the cloud.

Secured Shouldn’t Mean Slow

When moving fast by consuming more cloud-native functions, you must also include smart security solutions that help you, as a security professional, to become an enabler of the business rather than the bad guy that keeps saying “no” to requests, or keep chasing down developers to close security holes that detract them from their core mission. An ideal cloud-native security solution should have an intelligent, AI-based learning component that can detect abnormal behaviors, correlate sporadic suspicious events into a coherent attack story, and provide prioritized, actionable recommendations to harden the cloud environment and permissions in the most time-efficient manner. Automated remediation can save a lot of time and effort, if done correctly with minimal false positives, and prevent attackers from moving laterally up the attack kill-chain. This balance between security, technology, and automation allows developers and DevOps personnel to focus on enabling accelerated business growth with minimum security headcount.

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