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.
Autonomous AI agents are gaining real access to production systems — and real incidents, from deleted databases to fabricated refunds, show what happens when they act outside intended boundaries.
A practical, no-hype comparison of secrets scanning tools for CI/CD: what gitleaks, TruffleHog, and GitGuardian catch, and where each one falls short.
Researchers estimate roughly 3% of public Docker Hub images carry malicious payloads. Here's what's inside them, how they spread, and how to defend your pipeline.
Attackers are exploiting the trust between humans and AI agents — hidden prompt injections, hallucinated packages, and over-trusted autonomy are now supply chain risks.
A practical, no-hype comparison of secrets detection tools for source code repos — evaluation criteria, five real vendors reviewed fairly, and how Safeguard fits in.
A look at why Docker Hub's most-pulled base images still ship hundreds of known CVEs, and how reachability analysis cuts the noise down to what's actually exploitable.
One compromised agent can poison an entire pipeline in seconds. Heres how cascading failures spread through multi-agent AI systems, and how to contain them.
A fair comparison of SLSA compliant build systems—GitHub Actions, Cloud Build, GitLab, Tekton Chains—with real strengths and limitations for Build Level 3.
Cryptomining malware keeps resurfacing in public Docker images. Here's how attackers hide miners in plain sight — and how to catch them before they run.
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