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.
An AI security app uses machine learning to detect, prioritize, or remediate security issues. Here is what the category actually delivers and how to judge one.
A container image audit inspects every layer of an image - base OS packages, application dependencies, secrets, and configuration - to find what an attacker could exploit before you deploy.
An AI cybersecurity company uses machine learning to detect, prioritize, and remediate threats faster than rules alone. Here is how to evaluate one honestly.
The aws-amplify npm package is a large, capable SDK that touches auth, storage, and API calls. Here is a practical security review of what to watch for and how to use it without widening your attack surface.
Real CVEs, a supply-chain hack that hit 360,000 sites, and bundled-library blind spots: what WordPress plugin security actually requires in 2026.
A framework for comparing software supply chain security solutions across the four capabilities that matter, SBOM generation, dependency scanning, provenance verification, and CI/CD gating.
MCP-led agent workflows hand real tools to a language model. That power is also the attack surface. Here is how tool poisoning works and how to defend against it.
Two developer-first SCA tools, one honest comparison: vulnerability data, fix automation, noise levels, pricing models, and where each one actually fits.
SAST vs DAST vs IAST vs RASP comes down to when each technique looks at your application — source code, a running test instance, instrumented runtime tests, or production traffic — and picking the wrong stage leaves real gaps.
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