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Insights on Data Security & Threat Intelligence
Regulations require documented controls. Auditors ask for evidence those controls worked. The gap between the two is where most data security programs...
Most MCP servers act as bridges: they expose tools and pass calls through. Vaikora Guard MCP does something different at the protocol layer. Before any...
Twelve lines of YAML can block an AI agent from calling a destructive tool before the call ever reaches the target system. That is the practical premise...
Threat intelligence is only useful if it is fresh enough to matter and specific enough to act on. Cyren's threat intelligence feed addresses both problems...
Most external attack surface findings land in a queue with no context about whether the exposed asset is actively targeted, who owns it, or what the...
Regulated data sits in places most security teams have never audited: old file shares, cloud storage buckets, email archives, databases with broad access,...
Six months ago, the AI runtime control category didn't really exist. Today there are at least eight vendors, three open-source projects, two ongoing industry standards efforts, and a Q3 2026 AWS Marketplace category dedicated to the space.
When one AI agent calls another AI agent, you have a problem that didn't exist a year ago. The first agent generates a request based on its reasoning. The second agent acts on that request. Neither agent has any guarantee about what the other will actually do.
The OWASP Top 10 for LLM Applications (2025 edition) is the closest thing the AI security industry has to a consensus threat model. It enumerates the ten categories of weakness that show up most often when production LLM systems go wrong.