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.
You cannot secure an LLM application by reading its code alone. You have to attack it the way an adversary will — with language, with poisoned content, and with the goal of making it do something it should not. Here is how to run an AI red team.
MCP is the USB-C of AI integrations — one open standard for connecting models to tools and data. It also standardizes a fresh attack surface, so understanding both halves matters.
AI agents can browse regional pricing, compare tiers, start a Stripe checkout, and verify activation — the entire Safeguard procurement journey now runs through the MCP server.
Stanford researchers found developers using AI coding assistants wrote more security bugs — and felt more confident in them. Here's how to adopt AI safely.
GitHub reports its Copilot Autofix suggestions resolve two-thirds of flagged vulnerabilities with little or no editing — but the other third is where merges go wrong.
319 LLM patches for 64 real CVEs were graded in 2026: only 24.8% were both secure and functional. Speed without validation just merges bugs faster.
GitHub has disclosed that Copilot suggestions match training-set code verbatim about 1% of the time — and a class action over it is still being argued in 2026.
Developers using AI coding assistants wrote less secure code in 4 of 5 tasks in a 2023 Stanford study — and were more confident it was safe.
A 2021 NYU study found roughly 40% of Copilot completions on security-relevant prompts contained exploitable flaws. Here's a field guide to catching them.
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