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 coding assistants read untrusted files as instructions, not data. Here's how prompt injection sneaks malicious code into your commits — and how to catch it before it ships.
LLM coding assistants inherit insecure patterns from their training data — from SQLi-prone snippets to hallucinated packages attackers exploit. Here's how the risk propagates.
AI governance frameworks like NIST AI RMF and the EU AI Act now govern AI-built software. Here's what they require, and where JFrog's artifact-first approach falls short.
A cybersecurity training platform is only as good as the behavior it changes. Here is how to evaluate one for developers in 2026, including AI-driven and hands-on approaches.
AI coding agents now open PRs, merge code, and touch secrets on their own. Here's why JFrog-style artifact scanning can't govern them, and what can.
Unvetted MCP servers already power tool poisoning and rug-pull attacks. Here's why package scanning like JFrog's isn't enough, and how to actually secure your MCP registry.
AI agent skills and MCP plugins are packages in disguise—executable, publicly registered, and largely ungoverned. Here's why they need npm-grade supply chain controls.
What should a "responsible AI" commitment from a security vendor actually contain? A breakdown of the regulations, disclosures, and JFrog comparison every buyer should check.
Anthropic shipped Claude Opus 4.8 on May 28, 2026, with sharper agentic coding and better honesty about its own work. Here is what it changes for vulnerability triage, fix-PRs, and the governance you need before it touches your pipeline.
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