AI can only defend what it can see. Give it incomplete data, and it won't warn you. It quietly reports everything as healthy while real attacks slip through unseen.
Prompt injection hijacks an LLM by exploiting its inability to separate data from commands. Direct and indirect attacks require layered defenses, not one fix.
SBOMs improve software supply chain transparency, but sharing them carelessly creates risk. Learn how controlled disclosure balances trust and security.
Deeper AI integration in the framework core, modern authentication via OAuth / OIDC and WebAuthn passkeys driven from the system browser, and a few smaller additions.
A major GitHub breach showed how extension poisoning, Node ecosystem weaknesses, and insecure developer workstations can bypass traditional security defenses.
A practical checklist for evaluating AI data readiness, covering data quality, governance, lineage, access controls, retrieval systems, and ongoing monitoring.
LLMs can quickly generate web application code, but AI-written code may contain security vulnerabilities. This article reviews testing methods for LLM systems.
Three structural shifts enterprise data security teams should make in 2026, based on verifiable data and a decade of experience building protection products.