Why developers stop trusting AI-generated vulnerability fixes
Trust in AI-generated code fell to 29% in 2025, yet 84% of developers keep using it anyway — the gap is a UX problem, not a model problem.
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.
Trust in AI-generated code fell to 29% in 2025, yet 84% of developers keep using it anyway — the gap is a UX problem, not a model problem.
A step-by-step rotation runbook for security teams exposed to the Shai-Hulud npm worm — what to revoke first, how to verify a credential is dead, and how to prevent a repeat.
A practical buyer's guide to SSDLC platforms in 2026 — evaluation criteria, an honest roundup of six real vendors, and where Safeguard fits in.
Bolting a scanner on before release doesn't count as shift-left. Here's where security actually needs to sit across the SDLC, and why mobile testing is often the weakest link.
You cannot fund an application security program on fear forever. Here is how to measure AppSec ROI with metrics executives believe — cost avoided, MTTR, and the leading indicators that predict both.
Most security dashboards count findings and prove nothing. A 2026 guide to the DevSecOps metrics and KPIs that show real risk reduction — MTTR, escape rate, coverage, and DORA-aligned measures.
Log4Shell sat in most Java codebases for years before Dec 2021 — shift-left tooling alone didn't stop it. Culture, placement, and incentives are what make it work.
A backdoor sat in xz-utils 5.6.0 and 5.6.1 for weeks before Andres Freund caught it — stable distro channels, not luck, kept it out of most production systems.
Google's SRE teams have spent an error budget on reliability since 2016 — applying the same model to security turns blanket blocking into risk-weighted gating.
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