Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
MCP stands for Model Context Protocol, the open standard that lets AI assistants talk to your tools and data. Here is what it is and where the security risks live.
A practical framework for deciding which AI-enabled tools you should actually adopt, weighed against the data-exposure and supply chain risks they introduce.
When a vendor's incident affects you, the coordination work between their IR team and your ops becomes its own project. How to run it well.
Field notes on running Tetragon, Falco, and Cilium eBPF controls in production Kubernetes clusters, with observed overhead, policy traps, and kernel constraints.
Bedrock Guardrails now span prompt filtering, contextual grounding checks, and tool-use policies. We trace how they fit into a supply chain threat model for production agents.
An audit trail is only useful if you can answer questions from it. Quality is not about volume — it's about the ability to reconstruct decisions after the fact.
A vulnerability that passes through a working sanitizer is not a vulnerability. Detecting that sanitizer accurately is the difference between actionable findings and noise.
From AI-generated code risks to regulatory enforcement and package manager security evolution, here are the trends that will define software supply chain security in 2025.
AI Python code correctors fix syntax and obvious bugs fast, but they miss the security and correctness issues that matter most. Here is where they help, where they fail, and how to use them safely.
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