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.
AI information security is the practice of protecting the data that flows through AI systems, training sets, prompts, outputs, and the models themselves, from disclosure, poisoning, and misuse. Here is a working model of the risks and controls.
The CVEs that hurt clusters lately live at the edges: admission controllers, ingress, and image supply chains. What the recent record says about where to harden first.
adm-zip is a popular pure-JavaScript zip library for Node.js, and its history of path-traversal flaws makes safe extraction non-optional. Here is what went wrong and how to use it correctly.
Tool-using agents have become a viable exfiltration channel. The patterns showing up in incident reports, and the controls that contain them.
AI endpoint security uses machine learning to detect threats by behavior rather than signatures. Here is what it actually does, where it helps, and its limits.
How Argo CD Image Updater works, the security tradeoffs of automated image promotion, and the configuration patterns that prevent supply chain incidents.
CVE-2022-42889 (Text4Shell) is a 9.8-severity RCE in Apache Commons Text 1.5-1.9. Learn affected versions, timeline, and remediation steps.
A 2026 hardening guide for Azure DevOps Pipelines: service connections, workload identity federation, approval gates, agent isolation, and SLSA integration.
AI cybersecurity tools in 2026 split into three real categories — AI-augmented detection, AI-specific application security, and autonomous response — and most vendors only actually cover one.
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