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 explainability is the ability to understand why a model produced a given output. In security, it is the difference between an alert you can act on and one you cannot.
The MSI breach exposed Intel BootGuard private keys and OEM signing infrastructure. A look at firmware-level supply chain risk and the gaps that remain.
Checkmarx CxSAST is one of the longest-running static analysis engines in the enterprise appsec market. Here's what it actually scans, how it's typically deployed, and where teams run into friction.
AI accelerators are the specialized chips that make model training and inference fast, and they bring their own attack surface: memory leakage, driver stacks, and firmware you did not write. Here is what to secure.
The average enterprise runs dozens of security tools that barely talk to each other. This guide maps the categories, explains why consolidation is accelerating, and shows how to evaluate a platform.
AI agents can now open pull requests that patch vulnerabilities on their own. Without guardrails — scoped permissions, test gates, human merge approval — they can also break builds and introduce new flaws at machine speed.
MCP gives AI agents real tools, real credentials, and real blast radius. Here is a hardening guide for running MCP servers in production without torching your environment.
Prototype pollution lets attackers corrupt Object.prototype via unsafe merges, turning a data bug in lodash, jQuery, or minimist into RCE.
CI/CD runners are a top attacker target. Here's a concrete zero-trust blueprint using OIDC federation, pinned action SHAs, and short-lived identities.
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