Abstract---Agentic AI is shifting the cybersecurity landscape as attackers and defenders leverage AI agents to augment humans and automate common tasks. In this article, we examine the implications for cyber warfare and global politics as Agentic AI becomes more powerful and enables the broad proliferation of capabilities only available to the most well resourced actors today . As attacks increased in volume and attackers became more sophisticated, moving towards polymorphic malware, packers, and novel evasion techniques, defenders looked to machine learning to provide scalability (quickly analyze large volumes of data and automate repetitive tasks), pattern recognition (detect common attack patterns), and novelty detection (recognize abnormal behaviors that may indicate malicious actors or insider threats). Companies now use Large Language Models (LLMs) to provide analysts and reverse engineers with a rapid analysis of malicious code and best next steps when triaging alerts. But the real paradigm shift in cybersecurity for both attackers and defenders is still on the horizon: agentic artificial intelligence (agentic AI).

Our biggest undeclared war right now doesn't involve nuclear programs or any of the other technologies that usually take up headlines when it comes to this topic. In fact, our biggest war right now takes place on a completely different battlefield-Cyberspace. Cyberspace operations can be used to achieve strategic information warfare goals; an offensive cyberattack, for example, may be used to create psychological effects in a target population. There is a war on in cyberspace. Cyberspace is entirely human-made and has been designed, created, maintained, owned, and operated both by public and private stakeholders across nations. It is continually changing in response to technology transformation.

SonicWall President and CEO Bill Conner was featured as part of an exclusive group of cybersecurity thought-leaders at The Chertoff Group Security Series Event, "AI, Threat Intelligence and The Cyber Arms Race," on June 18. Conner was flanked by Christopher Krebs, Director of Cybersecurity and Infrastructure Security Agency (CISA) in the Department of Homeland Security; Dimitri Kusnezov, Deputy Under Secretary for Artificial Intelligence & Technology, Department of Energy; along with panel moderator Chad Sweet, Chief Executive Officer and Co-Founder, The Chertoff Group. Together, they took to the stage to discuss how AI solutions are being leveraged to prevent, detect and respond to the cyber threats attacking both critical public infrastructure and the private sector. The wide-ranging discussion took on everything from election cybersecurity to self-driving cars, but was grounded by a focus on how AI is increasingly growing in importance when running cyber defenses in both the public and private sectors. With this in mind, they looked at the increasing number of'have and have-nots' in these areas with Conner pointing out that an underfunded agency or a small company simply doesn't "have the resource -- capital or human" to defeat a major cyberattack without AI-based cyber defenses such as SonicWall Real-Time Deep Memory InspectionTM (RTDMI) that can both detect and prevent existing and never-before-seen cyberattacks as they appear.

In theory, the only technology capable of hacking a system run by artificial intelligence is another, more powerful AI system. That's one reason why the U.S. Army incorporated a powerful AI capabilities into its drone systems that is expected to provide the ultimate cybersecurity -- at least, for now. "It's an arms race," said Walter O'Brien, CEO of Scorpion Computer Services, whose AI system runs and protects the Army's UAV operations. "Now I have an AI protecting the data center, and now the enemy would have to have an AI to attack my AI, and now it's which AI is smarter."

This article was first published in the April 2016 issue of WIRED magazine. Be the first to read WIRED's articles in print before they're posted online, and get your hands on loads of additional content by subscribing online. Last year, probably for the first time, two fully autonomous artificial intelligences went to war in anger: an attacker and a defender. The battlefield was a corporate network. For the past two years, the most advanced cyber-defence systems have used machine learning.