Bar Klinghofer

If you asked most security leaders where all of their data is flowing, which workloads and AI services are accessing it, and whether it's exposed, only a few could answer with confidence, and almost none would have the answer in real time.Not because that data is not available, but because it's scattered across multiple cloud…

Cloud security teams do not have a visibility problem anymore. They have a context problem. Modern cloud environments generate endless findings across vulnerabilities, identities, APIs, data, configurations, threats, workloads, and exposure. The challenge is not just knowing what exists. It is understanding what matters, why it matters, and what to do next. That is where…

After teams identify the risks that matter, the next challenge is proving which ones are actually exploitable. Severity scores, exposure labels, and long lists of findings can point teams in the right direction, but they do not always show whether an attacker has a viable path to impact. In cloud environments, that path often depends…

The AI threat landscape is moving faster on both sides. Attackers are using AI to scale campaigns, accelerate exploit development, and move faster from discovery to execution. Defenders need AI that helps them keep pace without adding noise or pulling teams away from the work that matters most. Prioritization helps teams focus on the risks…

Cloud security works best when teams can move from context to action in one place. Upwind already brings together runtime-powered security context across cloud infrastructure, applications, identities, workloads, APIs, and AI systems. Now, the Upwind Agentic Pack helps teams use that context faster across investigation, validation, and remediation workflows. Grounded in Upwind’s runtime-first platform, the…

Security teams already have enough findings to sort through. Vulnerabilities, misconfigurations, and alerts pile up every day, but only a limited number create real risk in production. The harder problem is knowing which issues are exposed, active, and worth fixing first. The Upwind MCP Server connects MCP-compatible clients to selected Upwind context and capabilities, helping…

Originally, organizations moved to the cloud to be agile. With abstracted architecture, fewer provisioning delays, and on-demand scalability, developers found themselves free from the usual constraints of legacy IT.  But the quicker deployments born of easy experimentation and no more waiting on hardware that organizations desired weren’t always in reach. Instead, they found their assets…

The container revolution has swept up a generation of workloads. Containerization is often the default choice because it offers efficiencies that other architectures can’t match: lightweight resource usage, rapid spin-up times, and seamless portability across environments. Docker, in particular, popularized the modern container model by making it easy to package applications with all their dependencies…

The rise of artificial intelligence (AI and its rapid adoption across the enterprise landscape have brought about both unprecedented opportunities and profound challenges, particularly in the realm of data security. On one hand, AI-driven solutions powered by large language models (LLMs) are unlocking new levels of automation, enhancing how organizations approach cybersecurity. But as AI…

Generative artificial intelligence (GenAI) systems are increasingly ubiquitous — and central to business. Protecting them lags behind their development, leaving organizations exposed to rapidly evolving vulnerabilities unique to GenAI.  After all, large language models (LLMs) can be targets for data exposure, prompt injections that manipulate the model’s behavior, and model poisoning. They’re also public-facing black…