Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

235,000 installs per week. That’s how quickly developers are downloading AI agent skills — packages that give AI coding agents new capabilities like shell access, file system operations, cloud access, and deployment permissions. But unlike traditional npm packages, agent skills introduce a completely new security problem: natural language instructions that AI agents can interpret and execute autonomously.

On May 11, 2026, the TanStack namespace was hit by a "Mini Shai-Hulud" supply chain attack. Unlike typical attacks, this did not involve stolen credentials; instead, the threat group TeamPCP hijacked the legitimate GitHub Actions release pipeline. This video covers the technical details of the OIDC token extraction, the "Dead Man's Switch" that triggers a rm -rf / upon credential revocation, and the mandatory remediation order you must follow to save your data. We also discuss how to harden your workflow using release-age cooldowns and OIDC pinning.

Are you confused by the terminology surrounding AI coding tools? You aren't alone. In this video, we break down the four essential components that transform a basic LLM into a powerful coding agent: Rules, Skills, Hooks, and the Model Context Protocol (MCP).

GPT-5.5 vs Claude Opus 4.7 - two flagship AI models dropped one week apart, and both claim to be the best at agentic coding. We put that to the test by giving each model the exact same prompt: build a production-ready, secure note-taking application from scratch. But we didn't stop at reviewing the code. We actually tried to break it by running real security tests against each app to see whether AI-generated code can be trusted with user data. The results were not what we expected.