Artificial Idiots (AI)

AI security isn’t heading toward one magic “AI firewall.” It’s turning into a layered stack where identity, permissions, audit logs, sandboxing, and human approval gates decide whether your AI agent is helpful or dangerous. We walk through the biggest signals from the week and translate them into practical guidance you can actually use, especially if you’re trying to secure AI tools inside a real business with real data.We start with a blunt shift: account takeover is now an AI security problem. As ChatGPT and coding assistants become as sensitive as email, GitHub, or cloud admin accounts, stronger authentication and safer recovery paths stop being optional. We also dig into why AI coding tools are evolving into security products that scan codebases for vulnerabilities and generate fixes, and what that means for your secure software development lifecycle, validation process, and vendor risk.Then we focus on the hot zone: agent security. The scariest risk isn’t a weird chatbot reply, it’s an agent with access to your inbox, files, repos, CRM, and cloud tools taking actions on your behalf. We break down OWASP LLM Top 10 themes like prompt injection, insecure output handling, sensitive data disclosure, and excessive agency, and we zoom in on indirect prompt injection where malicious instructions hide inside content an agent later retrieves and obeys. Finally, we cover how frameworks like NIST’s AI cybersecurity profile help operationalize AI risk, why cyber capable frontier models are being gated, and how defense adoption raises the stakes around supply chain security and vendor trust.Subscribe for weekly AI security news, share this with a teammate who’s rolling out agents, and leave a review with the one AI security question you want answered next.JoshJennaJack Randy