Series
AI Runtime Security Immune System: AI Agent Security Immune System, AI Autonomous Runtime Security Immune System, AI autonomous workflow security, AI Agent Security Vulnerabilities Scanner
From AI-driven ransomware to zero-click prompt injection, real-world incidents show why protecting the model isn't enough—and why AI systems need security controls that work at runtime. AI is changing
Patrick Wardle's "not-a-mused" proof-of-concept reveals a new class of AI security risk: compromise the agent, and you may inherit the permissions the user already gave it.
An AI agent can be carefully isolated---and still inherit a much larger blast radius if its runtime boundary fails. That is the security lesson behind the reported pre-launch KVM-escape issues surroun
The most dangerous AI attack may not break the model. It may simply convince the AI to use a trusted tool against you. That's the security problem emerging around the Model Context Protocol (MCP). Mus
Your AI agent doesn't have to be hacked if it can be convinced to hack itself. That is the fundamental danger of indirect prompt injection. A traditional application generally treats a webpage as data
An AI agent can finish the task—and still violate the rules. AI agents can browse websites, execute code, call APIs, and interact with digital resources. But what happens when an agent encounters a r