cside
cside is the leading client-side intelligence platform. Protecting organizations from advanced client-side threats such as script injection, data skimming, and browser-based attacks, risks often overlooked by traditional security measures. Leveraging client-side intelligence to provide evidence to fight chargeback fraud cases. It also addresses the growing challenge of web supply chain risk, ensuring real-time visibility and control over third-party scripts running in user environments. cside provides proactive, proxy-based protection that helps organizations meet compliance requirements like PCI DSS 4.0.1, safeguard sensitive data, and uphold user privacy, all without compromising performance.
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SOCRadar Extended Threat Intelligence
SOCRadar provides a unified, cloud-hosted platform designed to enrich your cyber threat intelligence by contextualizing it with data from your attack surface, digital footprint, dark web exposure, and supply chain.
We help security teams see what attackers see by combining External Attack Surface Management, Cyber Threat Intelligence, and Digital Risk Protection into a single, easy-to-use solution. This enables your organization to discover hidden vulnerabilities, detect data leaks, and shut down threats like phishing and brand impersonation before they can harm your business.
By combining these critical security functions, SOCRadar replaces the need for separate, disconnected tools. Our holistic approach offers a streamlined, modular experience, providing a complete, real-time view of your threat landscape to help you stay ahead of attackers.
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Mindgard
Mindgard is the leader in ai red teaming, helping enterprises identify, assess, and mitigate real-world security risks across AI models, agents, and applications. Founded on pioneering research in AI security, Mindgard was built on the insight that traditional application security approaches cannot protect systems that are probabilistic, adaptive, and deeply embedded into business workflows.
As organizations deploy GenAI and agentic systems at scale, risk increasingly emerges from how AI behaves, what it connects to, and how attackers can manipulate those interactions. Mindgard addresses this challenge with an attacker-aligned approach that mirrors how real adversaries perform reconnaissance, map attack surfaces, exploit system behavior, and pivot through tools, data, and infrastructure. Rather than testing models in isolation, Mindgard evaluates full AI systems in context to surface vulnerabilities with real security impact.
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