Best Threat Intelligence Platforms for Kubernetes
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Compare the Top Threat Intelligence Platforms that integrate with Kubernetes as of August 2025
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This a list of Threat Intelligence platforms that integrate with Kubernetes. Use the filters on the left to add additional filters for products that have integrations with Kubernetes. View the products that work with Kubernetes in the table below.
What are Threat Intelligence Platforms for Kubernetes?
Threat intelligence platforms are tools that enable organizations to collect, analyze, and act on cybersecurity threat data to proactively defend against potential attacks. These platforms aggregate information from a variety of sources, including internal security systems, open-source intelligence, commercial threat feeds, and government alerts, to provide a comprehensive view of the threat landscape. By processing and correlating this data, threat intelligence platforms identify emerging threats, track attacker tactics, and provide actionable insights that can be used to strengthen defenses and inform decision-making. Many threat intelligence platforms also integrate with other security systems, such as Security Information and Event Management (SIEM) tools, to automate threat detection and response. Overall, these platforms enhance an organization’s ability to respond to and mitigate cyber threats quickly and effectively. Compare and read user reviews of the best Threat Intelligence platforms for Kubernetes currently available using the table below. This list is updated regularly.
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Blue Hexagon
Blue Hexagon
We’ve designed our real-time deep learning platform to deliver speed of detection, efficacy and coverage that sets a new standard for cyber defense. We train our neural networks with global threat data that we’ve curated carefully via threat repositories, dark web, our deployments and from partners. Just like layers of neural networks can recognize your image in photos, our proprietary architecture of neural networks can identify threats in both payloads and headers. Every day, Blue Hexagon Labs validates the accuracy of our models with new threats in the wild. Our neural networks can identify a wide range of threats — file and fileless malware, exploits, C2 communications, malicious domains across Windows, Android, Linux platforms. Deep learning is a subset of machine learning that uses multi-layered artificial neural networks to learn data representation. -
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ThreatStryker
Deepfence
Runtime attack analysis, threat assessment, and targeted protection for your infrastructure and applications. Stay ahead of attackers and neutralize zero-day attacks. Observe attack behavior. ThreatStryker observes, correlates, learns and acts to protect your applications and keep you one step ahead of attackers. Deepfence ThreatStryker discovers all running containers, processes, and online hosts, and presents a live and interactive color-coded view of the topology. It audits containers and hosts to detect vulnerable components and interrogates configuration to identify file system, process, and network-related misconfigurations. ThreatStryker assesses compliance using industry and community standard benchmarks. ThreatStryker performs deep inspection of network traffic, system, and application behavior, and accumulates suspicious events over time. Events are classified and correlated against known vulnerabilities and suspicious patterns of behavior.
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