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.
HTTP security headers are your first line of defense against XSS, clickjacking, and data injection attacks. Here is a practical implementation checklist with correct configurations.
Everything you need to know about Software Bills of Materials -- what they are, why they matter, and how to start generating them for your projects.
Hardware travels through dozens of hands before reaching your data center. Understanding and enforcing trust boundaries across the hardware supply chain is essential for building secure systems.
An unauthenticated RCE zero-day in Confluence Server was being actively exploited before Atlassian even knew about it. The vulnerability affected virtually every on-premise Confluence installation.
Software provenance answers the question: where did this code come from, who built it, and can I trust it? In 2022, provenance tracking moved from academic concept to practical necessity.
When choosing between open source packages that provide the same functionality, security factors should weigh as heavily as features. Here is a practical evaluation framework.
A working engineer's review of CyberSecEval, the Meta-originated benchmark that has quietly become the default sniff test for AI-for-security claims. What it actually measures, what it misses, and how to read its scores without fooling yourself.
The NIST SSDF attestation form asks structured questions with structured answers. A chat transcript is not an answer. We explain how Griffin AI produces the evidence auditors expect, and why Mythos-class tools struggle.
Griffin AI runs on Anthropic's Claude models under the hood. Here's what the engine context, eval harness, and workflow scaffolding actually buy you over calling Claude directly.
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