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.
A single static severity score cannot tell you which vulnerability to fix first. Modern prioritization is a function of reachability, exploitability, and business context — and CVSS is only one input.
Maven Central's move from GPG to Sigstore is genuinely underway in 2026. Here is where the transition actually stands and what Java shops should do now.
The Safeguard Research team measured how often AI coding assistants hallucinate non-existent packages, how sticky those hallucinations are, and what defenders should do.
A closer look at the enterprise accounts, verticals, and delivery capabilities that make Sify Technology (USA) an interesting partner for Safeguard.
AI incidents are not the same shape as traditional security incidents. The playbooks need to be specific to how AI systems actually fail.
Gemma is built for efficiency. Can a small open-weight model replace Griffin AI for lightweight scanning workflows, or does the engine still matter?
The real cost of a scanner is not the subscription. It is the engineer hours lost to false positives, bad remediations, and noisy queues. We do the math.
What happens when the bug does not match any known CWE? A study of how grounded and pure-LLM scanners perform on genuinely novel vulnerability patterns.
A look at the container breakout vulnerabilities disclosed in 2024 and 2025, what they actually required to exploit, and what that pattern tells us about the defense model.
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