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.
From the CrowdStrike outage to state-sponsored npm campaigns and regulatory milestones, 2024 was the year supply chain security went from niche concern to operational necessity.
Debian's Reproducible Builds project has been at it for over a decade. Here's what they've learned, what still isn't reproducible, and why it matters.
Using AI for stock trading means applying models to signals, screening, and execution, but the security and reliability risks are as important as the strategy. Here is a grounded look.
A practical framework for deciding which AI-enabled tools you should actually adopt, weighed against the data-exposure and supply chain risks they introduce.
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 container image vulnerability tool scans the layers, packages, and metadata inside an image so you catch known CVEs before they ship to production. Here is how to pick and use one well.
A container image scanner inspects the layers, packages, and configuration inside an image to find known vulnerabilities before you ship it. Here is how the scan works and what separates a good tool from a noisy one.
AI cybersecurity software uses machine learning to spot anomalies, triage alerts, and prioritize risk faster than humans can. Here is what it genuinely helps with and where it still needs a human.
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.
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