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.
SAST catches insecure code before deploy; DAST tests running apps after. We compare both against JFrog's Artifactory-first model and Safeguard's supply-chain-native approach.
AI-assisted "vibe coding" is reshaping how much code ships and how little of it gets truly reviewed. Here's what the data shows and how AppSec teams should respond.
REST API breaches from T-Mobile to Optus trace to a handful of recurring mistakes. Here's how to fix authorization, auth, injection, and rate limiting.
AI now writes up to half of production code. Here is why traditional code review breaks down on AI output, and what teams need to change.
DevOps vs DevSecOps isn't a mindset shift — it's specific new artifacts, gates, and ownership. Here's what changes, contrasted with JFrog's artifact-first model.
AI writes most new code, but few CI pipelines scan it before merge. Here's why the AI code scanning adoption gap exists — and what closes it.
A good code guide teaches you to read code, not just write it. This walkthrough covers how to review code for the security flaws that automated tools and casual readers miss.
A verifiable comparison of Safeguard and JFrog Xray on scan coverage, data sourcing, reachability analysis, and CI/CD integration for vulnerability scanning.
A security review of @angular-eslint/schematics: what the package does, its install-time behavior, dependency footprint, and how to adopt it safely in an Angular workspace.
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