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 acceleration is compressing both software delivery and attacker tradecraft. A security look at what changes when AI speeds up your pipeline and theirs.
Practical security for Docker containers: minimal base images, non-root users, image scanning, and runtime hardening you can apply to any Dockerfile today.
CVSS alone is a bad prioritisation signal in 2026. Reachability plus EPSS gives teams a defensible order to fix the vulnerabilities that actually matter.
Training data is a supply chain component. Knowing what went into a model is the precondition for knowing what could come out of it. Few tools track this; the few that do matter disproportionately.
Container compliance means proving your images and runtime meet the controls auditors ask for, continuously, without turning every deploy into a manual review.
Securing Docker containers is less about one setting and more about a chain of defaults: slim base images, non-root users, scanned layers, and locked-down runtime privileges.
Enterprise MCP deployments need more than a static API key. The protocol is evolving toward OAuth 2.1 and dynamic client registration, and understanding which pattern fits which workload decides whether your rollout survives the first audit.
Poolside's on-prem code AI is a credible enterprise offering. For security-specific workflows, Griffin AI's grounding architecture targets different ground.
Dependency confusion is older than most of the AI tooling trying to detect it. The attacks have adapted to the defences — detection needs to keep up.
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