Recent intrusions highlight adversaries weaponizing agentic frameworks for highly automated attacks. Threat actors are increasingly abusing open-source pentesting frameworks like ARTEX, Hexstrike, and CAIRN. This signals a shift towards machine-speed intrusions, exponentially scaling attack complexity. The mechanics of attacks remain similar, but autonomous frameworks present new defensive challenges. Security teams must rethink defenses against scalable, autonomous software. Mandiant suggests long-standing best practices for defense, including control-plane isolation and least privilege. Adversaries are leveraging these LLM-powered frameworks to automate various stages of intrusions. ARTEX, an autonomous LLM-driven pentesting platform, abstracts the attack lifecycle with specialized sub-agents. It translates high-level goals into machine commands, enabling automated reconnaissance and privilege escalation. Diverse threat actors, including financially motivated groups and suspected state-sponsored actors, have adopted ARTEX. These frameworks demonstrate rapid execution, achieving deep system access in minutes. ARTEX exhibits forensically noisy, iterative trial-and-error approaches to exploit vulnerabilities and achieve objectives.