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AI Security

GenAI Code Assistants and Package Hallucination: 2026 Update

LLM-suggested package names that do not exist are a registered attack vector in 2026. Here is where hallucination rates sit today and how to contain them.

Mar 18, 20267 min read
AI Security

How to Secure Docker Containers: A Practical Hardening Guide

A working checklist to secure Docker containers, from non-root users and minimal base images to capability drops, read-only filesystems, and image scanning.

Mar 18, 20267 min read
AI Security

OWASP Top 10 Training: A Practical Guide for Developers

What OWASP Top 10 training actually needs to cover in 2026 now that the 2025 list has landed, plus where to find free, developer-focused courses that stick.

Mar 18, 20267 min read
AI Security

The GPL License Explained: What It Means for Software Security

A practitioner's walkthrough of what the GPL license actually requires, why it matters for your dependency tree, and how it intersects with software security and compliance.

Mar 18, 20266 min read
AI Security

How to Generate an SBOM From a Container Image

A practical walkthrough of how to generate an SBOM from a container image using Syft, Trivy, and Docker Scout, plus how to keep the output trustworthy.

Mar 18, 20267 min read
AI Security

Container Network Security: How to Lock Down Pod-to-Pod Traffic

Container network security is about controlling which workloads can talk to each other and blocking the rest by default. Here is how to build that in Kubernetes and beyond.

Mar 18, 20267 min read
AI Security

AI Bill of Materials (ML-BOM) Standards in 2026

A senior engineer's survey of AI-BOM and ML-BOM standards in 2026, from CycloneDX ML components to SPDX 3.0 AI profile, and what to actually ship.

Mar 18, 20267 min read
AI Security

AI Chips Explained: What They Are and How to Secure Them

AI chips are specialized processors built to run matrix math at scale, and the way you provision, share, and supply-chain-source them creates security risk most teams never model.

Mar 18, 20268 min read
AI Security

Cross-Vendor SBOM Normalization: Griffin AI vs Mythos

Your SBOMs come from a dozen vendors, three scanners, and two CI systems. Normalising them into one queryable graph is where SBOM programs actually succeed or fail.

Mar 17, 20264 min read

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